Dr. Tianming Liu is a Distinguished Research Professor (since 2017) and a Full Professor of Computer Science (since 2015) at UGA. Dr. Liu is also an affiliated faculty (by courtesy) with UGA Bioimaging Research Center (BIRC), UGA Institute of Bioinformatics (IOB), UGA Neuroscience PhD Program, and UGA Institute of Artificial Intelligence (IAI). Before he moved to UGA in 2008, Dr. Liu was a faculty member of Weill Medical College of Cornell University (Assistant Professor, 2007-2008) and Harvard Medical School (Instructor, 2005-2007). Dr. Liu was a postdoc in neuroimaging in the University of Pennsylvania (2002-2004) and Harvard Medical School (2004-2005). Dr. Liu received PhD in computer science from Shanghai Jiaotong University in 2002.

Dr. Liu is the recipient of the Microsoft Fellowship Award (2000-2002), the NIH Career Award (2007-2012) and the NSF CAREER Award (2012-2017). Dr. Liu is a Fellow of AIMBE (inducted in 2018) and was the General Chair of MICCAI 2019. 

Research Interests: Brain Imaging, Computational Neuroscience, Brain-inspired Artificial Intelligence (UGA Center for Brain-inspired Artificial Intelligence: https://braininspiredai.uga.edu), Artificial General Intelligence (AGI, e.g., Digital Brain) (UGA Generative AI Initiative: https://ai.uga.edu/genai), and Neuromorphic Computing (Neuromorphic Computing Meets Quantum Mechanics Conference: https://quantum.uga.edu/ncmqm-conference). UGA Data Science and AI Seminars: https://cps.uga.edu/index.php/data-science-and-ai-seminars.

Teaching Interests: Artificial General Intelligence, Biomedical Image Analysis, Biomedical Informatics, Computational Neuroscience, Signal/Image Processing.

Services (Selected): Journal Editorial Boards: Medical Image Analysis (since 2020), IEEE Transactions on Medical Imaging (since 2022), IEEE Transactions on Neural Networks and Learning Systems (since 2024), IEEE Reviews in Biomedical Engineering (since 2022), IEEE Transactions on Cognitive and Developmental Systems (since 2023), IEEE/ACM Transactions on Computational Biology and Bioinformatics (since 2013), IEEE Journal of Biomedical and Health Informatics (since 2021), IEEE Transactions on Neural Networks and Learning Systems (Guest Editor, 2022-2023), Frontiers in Radiology (Specialty Chief Editor for AI in Radiology, since 2020), Meta-Radiology (Editor-in-Chief, since 2023), Frontiers in Computational Neuroscience (since 2015), BMC Neuroscience (2016-2021), Psychoradiology (since 2020), Sensors (section of imaging sensors, since 2021), Intelligent Medicine (since 2020); Member of Board of Directors: MICCAI Society (2017-2021); Members: UGA Provost's Task Force of Academic Excellence (2019-2020) and UGA Faculty Admissions Committee (since 2020); Reviewers: 20+ NSF/NIH panels and study sections (since 2012), dozens of overseas grant proposals and dissertations (Europe and Asia), and 40+ journals/conferences (since 2002); Visitors: visits to 30+ universities and institutions (both domestic and overseas) to give talks/lectures and/or recruit students; Outreach: advisers of high-school students including UGA Young Dawgs students; tutorials on brain science for K12 students; volunteer judges for K12 science fairs/events; organizer of K12 summer camps on brain-inspired artificial intelligence; Asian Americans: volunteer to teach Asian Americans' Contribution to USA's Society (UGA first-year undergraduate course); Vice President of UGA's Association of Chinese American Professors (UGA-ACAP).

Students Mentoring: mentored 30+ PhD students/visiting scholars (since 2005); 15+ students secured tenure-track faculty positions in North America, Asia, Europe and Australia; 15+ students secured industrial jobs in leading companies such as Google, Apple, Meta, Siemens and etc; served on 50+ UGA graduate students thesis committees.  

Publications (Selected from 400+ Papers, Google Scholar: https://scholar.google.com/citations?user=92RPXm0AAAAJ&hl=en)

Recent Papers on NLP/LLM/CV/Knowledge Graph/Foundation Models/AIGC/Generative AI/AGI

Chong Ma, Hanqi Jiang, Wenting Chen, Zihao Wu, Xiaowei Yu, Fang Zeng, Lei Guo, Dajiang Zhu, Tuo Zhang, Dinggang Shen, Tianming Liu, Xiang Li, Eye-gaze Guided Multi-modal Alignment Framework for Radiology, arXiv: https://arxiv.org/abs/2403.12416. 2024.

Yiwei Li, Zihao Wu, Huaqin Zhao, Tianze Yang, Zhengliang Liu, Peng Shu, Jin Sun, Ramviyas Parasuraman, Tianming Liu, ALDM-Grasping: Diffusion-aided Zero-Shot Sim-to-Real Transfer for Robot Grasping, arXiv: https://arxiv.org/abs/2403.11459. 2024.

Xuansheng Wu, Haiyan Zhao, Yaochen Zhu, Yucheng Shi, Fan Yang, Tianming Liu, Xiaoming Zhai, Wenlin Yao, Jundong Li, Mengnan Du, Ninghao Liu, Usable XAI: 10 Strategies Towards Exploiting Explainability in the LLM Era, arXiv: https://arxiv.org/abs/2403.08946. 2024.

Qing Xiao, Siyeop Yoon, Hui Ren, Matthew Tivnan, Lichao Sun, Quanzheng Li, Tianming Liu, Yu Zhang, Xiang Li, Conditional Score-Based Diffusion Model for Cortical Thickness Trajectory Prediction, arXiv: https://arxiv.org/abs/2403.06940. 2024.

Zhengliang Liu, Jason Holmes, Wenxiong Liao, Chenbin Liu, Lian Zhang, Hongying Feng, Peilong Wang, Muhammad Ali Elahi, Hongmin Cai, Lichao Sun, Quanzheng Li, Xiang Li, Tianming Liu, Jiajian Shen, Wei Liu, The Radiation Oncology NLP Database, arXiv: https://arxiv.org/abs/2401.10995. 2024.

Shaochen Xu, Zihao Wu, Huaqin Zhao, Peng Shu, Zhengliang Liu, Wenxiong Liao, Sheng Li, Andrea Sikora, Tianming Liu, Xiang Li, Reasoning before Comparison: LLM-Enhanced Semantic Similarity Metrics for Domain Specialized Text Analysis, arXiv: https://arxiv.org/abs/2402.11398. 2024.

Peng Shu, Huaqin Zhao, Hanqi Jiang, Yiwei Li, Shaochen Xu, Yi Pan, Zihao Wu, Zhengliang Liu, Guoyu Lu, Le Guan, Gong Chen, Xianqiao Wang Tianming Liu, LLMs for Coding and Robotics Education, arXiv: https://arxiv.org/abs/2402.06116. 2024.

Jie Tian, Jixin Hou, Zihao Wu, Peng Shu, Zhengliang Liu, Yujie Xiang, Beikang Gu, Nicholas Filla, Yiwei Li, Ning Liu, Xianyan Chen, Keke Tang, Tianming Liu, Xianqiao Wang, Assessing Large Language Models in Mechanical Engineering Education: A Study on Mechanics-Focused Conceptual Understanding, arXiv: https://arxiv.org/abs/2401.12983. 2024.

Huaqin Zhao, Zhengliang Liu, Zihao Wu, Yiwei Li, Tianze Yang, Peng Shu, Shaochen Xu, Haixing Dai, Lin Zhao, Gengchen Mai, Ninghao Liu, Tianming Liu, Revolutionizing Finance with LLMs: An Overview of Applications and Insights, arXiv: https://arxiv.org/abs/2401.11641. 2024.

Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chao Zhang, Chaowei Xiao, Chunyuan Li, Eric Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, Willian Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao, TrustLLM: Trustworthiness in Large Language Models, arXiv: https://arxiv.org/abs/2401.05561. 2024.

Jiaqi Wang, Zihao Wu, Yiwei Li, Hanqi Jiang, Peng Shu, Enze Shi, Huawen Hu, Chong Ma, Yiheng Liu, Xuhui Wang, Yincheng Yao, Xuan Liu, Huaqin Zhao, Zhengliang Liu, Haixing Dai, Lin Zhao, Bao Ge, Xiang Li, Tianming Liu, Shu Zhang, Large Language Models for Robotics: Opportunities, Challenges, and Perspectives, arXiv: https://arxiv.org/abs/2401.04334. 2024.

Yiheng Liu, Hao He, Tianle Han, Xu Zhang, Mengyuan Liu, Jiaming Tian, Yutong Zhang, Jiaqi Wang, Xiaohui Gao, Tianyang Zhong, Yi Pan, Shaochen Xu, Zihao Wu, Zhengliang Liu, Xin Zhang, Shu Zhang, Xintao Hu, Tuo Zhang, Ning Qiang, Tianming Liu, Bao Ge, Understanding LLMs: A Comprehensive Overview from Training to Inference, arXiv: https://arxiv.org/abs/2401.02038. 2024.

Chenjiao Tan, Qian Cao, Yiwei Li, Jielu Zhang, Xiao Yang, Huaqin Zhao, Zihao Wu, Zhengliang Liu, Hao Yang, Nemin Wu, Tao Tang, Xinyue Ye, Lilong Chai, Ninghao Liu, Changying Li, Lan Mu, Tianming Liu, Gengchen Mai, On the Promises and Challenges of Multimodal Foundation Models for Geographical, Environmental, Agricultural, and Urban Planning Applications, arXiv: https://arxiv.org/abs/2312.17016. 2024.

Zhengliang Liu, Hanqi Jiang, Tianyang Zhong, Zihao Wu, Chong Ma, Yiwei Li, Xiaowei Yu, Yutong Zhang, Yi Pan, Peng Shu, Yanjun Lyu, Lu Zhang, Junjie Yao, Peixin Dong, Chao Cao, Zhenxiang Xiao, Jiaqi Wang, Huan Zhao, Shaochen Xu, Yaonai Wei, Jingyuan Chen, Haixing Dai, Peilong Wang, Hao He, Zewei Wang, Xinyu Wang, Xu Zhang, Lin Zhao, Yiheng Liu, Kai Zhang, Liheng Yan, Lichao Sun, Jun Liu, Ning Qiang, Bao Ge, Xiaoyan Cai, Shijie Zhao, Xintao Hu, Yixuan Yuan, Gang Li, Shu Zhang, Xin Zhang, Xi Jiang, Tuo Zhang, Dinggang Shen, Quanzheng Li, Wei Liu, Xiang Li, Dajiang Zhu, Tianming Liu, Holistic Evaluation of GPT-4V for Biomedical Imaging, arxiv: https://arxiv.org/abs/2312.05256. 2023.

Huan Zhao, Qian Ling, Yi Pan, Tianyang Zhong, Jin-Yu Hu, Junjie Yao, Fengqian Xiao, Zhenxiang Xiao, Yutong Zhang, San-Hua Xu, Shi-Nan Wu, Min Kang, Zihao Wu, Zhengliang Liu, Xi Jiang, Tianming Liu, Yi Shao, Ophtha-LLaMA2: A Large Language Model for Ophthalmology, arxiv: https://arxiv.org/abs/2312.04906. 2023.

Xinyu Gong, Jason Holmes, Yiwei Li, Zhengliang Liu, Qi Gan, Zihao Wu, Jianli Zhang, Yusong Zou, Yuxi Teng, Tian Jiang, Hongtu Zhu, Wei Liu, Tianming Liu, Yajun Yan, Evaluating the Potential of Leading Large Language Models in Reasoning Biology Questions, arXiv: https://arxiv.org/abs/2311.07582 . 2023.

Jason Holmes, Rui Peng, Yiwei Li, Jinyu Hu, Zhengliang Liu, Zihao Wu, Huan Zhao, Xi Jiang, Wei Liu, Hong Wei, Jie Zou, Tianming Liu, Yi Shao, Evaluating multiple large language models in pediatric ophthalmology, arXiv: https://arxiv.org/abs/2311.04368 . 2023.

Jason Holmes, Shuyuan Ye, Yiwei Li, Shi-Nan Wu, Zhengliang Liu, Zihao Wu, Jinyu Hu, Huan Zhao, Xi Jiang, Wei Liu, Hong Wei, Jie Zou, Tianming Liu, Yi Shao, Evaluating Large Language Models in Ophthalmology, arXiv: https://arxiv.org/abs/2311.04933 . 2023.

Zhengliang Liu, Yiwei Li, Qian Cao, Junwen Chen, Tianze Yang, Zihao Wu, John Gibbs, Khaled Rasheed, Ninghao Liu, Gengchen Mai, Tianming Liu, Transformation vs Tradition: Artificial General Intelligence (AGI) for Arts and Humanities, arXiv: https://arxiv.org/abs/2310.19626. 2023.

Tianyang Zhong, Wei Zhao, Yutong Zhang, Yi Pan, Peixin Dong, Zuowei Jiang, Xiaoyan Kui, Youlan Shang, Li Yang, Yaonai Wei, Longtao Yang, Hao Chen, Huan Zhao, Yuxiao Liu, Ning Zhu, Yiwei Li, Yisong Wang, Jiaqi Yao, Jiaqi Wang, Ying Zeng, Lei He, Chao Zheng, Zhixue Zhang, Ming Li, Zhengliang Liu, Haixing Dai, Zihao Wu, Lu Zhang, Shu Zhang, Xiaoyan Cai, Xintao Hu, Shijie Zhao, Xi Jiang, Xin Zhang, Xiang Li, Dajiang Zhu, Lei Guo, Dinggang Shen, Junwei Han, Tianming Liu, Jun Liu, Tuo Zhang, ChatRadio-Valuer: A Chat Large Language Model for Generalizable Radiology Report Generation Based on Multi-institution and Multi-system Data, arxiv: https://arxiv.org/abs/2310.05242 . 2023.

Yucheng Shi, Shaochen Xu, Zhengliang Liu, Tianming Liu, Xiang Li, Ninghao Liu, MedEdit: Model Editing for Medical Question Answering with External Knowledge Bases, arxiv: https://arxiv.org/abs/2309.16035. 2023.

Jason Holmes, Lian Zhang, Yuzhen Ding, Hongying Feng, Zhengliang Liu, Tianming Liu, William W. Wong, Sujay A. Vora, Jonathan B. Ashman, Wei Liu, Benchmarking a foundation LLM on its ability to re-label structure names in accordance with the AAPM TG-263 report, arxiv: https://arxiv.org/abs/2310.03874 . 2023.

Sekeun Kim, Kyungsang Kim, Jiang Hu, Cheng Chen, Zhiliang Lyu, Ren Hui, Sunghwan Kim, Zhengliang Liu, Aoxiao Zhong, Xiang Li, Tianming Liu, Quanzheng Li, MediViSTA-SAM: Zero-shot Medical Video Analysis with Spatio-temporal SAM Adaptation, arxiv: https://arxiv.org/abs/2309.13539. 2023.

Zhengliang Liu, Peilong Wang, Yiwei Li, Jason Holmes, Peng Shu, Lian Zhang, Chenbin Liu, Ninghao Liu, Dajiang Zhu, Xiang Li, Quanzheng Li, Samir H. Patel, Terence T. Sio, Tianming Liu, Wei Liu, RadOnc-GPT: A Large Language Model for Radiation Oncology, arxiv: https://arxiv.org/abs/2309.10160. 2023.

Chenhao Tang, Zhengliang Liu, Chong Ma, Zihao Wu, Yiwei Li, Wei Liu, Dajiang Zhu, Quanzheng Li, Xiang Li, Tianming Liu, Lei Fan, PolicyGPT: Automated Analysis of Privacy Policies with Large Language Models, arxiv: https://arxiv.org/abs/2309.10238. 2023.

Cheng Chen, Juzheng Miao, Dufan Wu, Zhiling Yan, Sekeun Kim, Jiang Hu, Aoxiao Zhong, Zhengliang Liu, Lichao Sun, Xiang Li, Tianming Liu, Pheng-Ann Heng, Quanzheng Li, MA-SAM: Modality-agnostic SAM Adaptation for 3D Medical Image Segmentation, arxiv: https://arxiv.org/abs/2309.08842. 2023.

Xiaowei Yu, Yao Xue, Lu Zhang, Li Wang, Tianming Liu, Dajiang Zhu, Exploring the Influence of Information Entropy Change in Learning Systems, arxiv: https://arxiv.org/abs/2309.10625. 2023.

Fei Dou, Jin Ye, Geng Yuan, Qin Lu, Wei Niu, Haijian Sun, Le Guan, Guoyu Lu, Gengchen Mai, Ninghao Liu, Jin Lu, Zhengliang Liu, Zihao Wu, Chenjiao Tan, Shaochen Xu, Xianqiao Wang, Guoming Li, Lilong Chai, Sheng Li, Jin Sun, Hongyue Sun, Yunli Shao, Changying Li, Tianming Liu, Wenzhan Song, Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges, arxiv: https://arxiv.org/abs/2309.07438. 2023.

Zhengliang Liu, Yiwei Li, Peng Shu, Aoxiao Zhong, Longtao Yang, Chao Ju, Zihao Wu, Chong Ma, Jie Luo, Cheng Chen, Sekeun Kim, Jiang Hu, Haixing Dai, Lin Zhao, Dajiang Zhu, Jun Liu, Wei Liu, Dinggang Shen, Tianming Liu, Quanzheng Li, Xiang Li, Radiology-Llama2: Best-in-Class Large Language Model for Radiology, arxiv: https://arxiv.org/abs/2309.06419. 2023.

Yaonai Wei, Tuo Zhang, Han Zhang, Tianyang Zhong, Lin Zhao, Zhengliang Liu, Chong Ma, Songyao Zhang, Muheng Shang, Lei Du, Xiao Li, Tianming Liu, Junwei Han, Chat2Brain: A Method for Mapping Open-Ended Semantic Queries to Brain Activation Maps, arxiv: https://arxiv.org/abs/2309.05021. 2023. Accepted by IEEE BIBM 2023.

Chenbin Liu, Zhengliang Liu, Jason Holmes, Lu Zhang, Lian Zhang, Yuzhen Ding, Peng Shu, Zihao Wu, Haixing Dai, Yiwei Li, Dinggang Shen, Ninghao Liu, Quanzheng Li, Xiang Li, Dajiang Zhu, Tianming Liu, Wei Liu, Artificial General Intelligence for Radiation Oncology, arxiv: https://arxiv.org/abs/2309.02590. 2023.

Xiaowei Yu, Lu Zhang, Dajiang Zhu, Tianming Liu, Robust Core-Periphery Constrained Transformer for Domain Adaptation, arxiv: https://arxiv.org/abs/2308.13515. 2023.

Chong Ma, Lin Zhao, Yuzhong Chen, Lei Guo, Tu Zhang, Xintao Hu, Dinggang Shen, Xi Jiang, Tianming Liu, Rectify ViT Shortcut Learning by Visual Saliency, in press, IEEE Transactions on Neural Networks and Learning Systems, 2023.

Zhengliang Liu, Lu Zhang, Zihao Wu, Xiaowei Yu, Chao Cao, Haixing Dai, Ninghao Liu, Jun Liu, Wei Liu, Quanzheng Li, Dinggang Shen, Xiang Li, Dajiang Zhu, Tianming Liu, Surviving ChatGPT in Healthcare, accepted, Frontiers in Radiology, 2023. PDF link. 

Zhengliang Liu, Tianyang Zhong, Yiwei Li, Yutong Zhang, Yi Pan, Zihao Zhao, Peixin Dong, Chao Cao, Yuxiao Liu, Peng Shu, Yaonai Wei, Zihao Wu, Chong Ma, Jiaqi Wang, Sheng Wang, Mengyue Zhou, Zuowei Jiang, Chunlin Li, Shaochen Xu, Lu Zhang, Haixing Dai, Kai Zhang, Xu Liu, Lin Zhao, Peilong Wang, Pingkun Yan, Jun Liu, Bao Ge, Lichao Sun, Dajiang Zhu, Xiang Li, Wei Liu, Xiaoyan Cai, Xintao Hu, Xi Jiang, Shu Zhang, Xin Zhang, Tuo Zhang, Shijie Zhao, Quanzheng Li, Hongtu Zhu, Dinggang Shen, Tianming Liu, Evaluating Large Language Models for Radiology Natural Language Processing, arxiv: https://arxiv.org/abs/2307.13693. 2023.

Zhengliang Liu, Zihao Wu, Mengxuan Hu, Bokai Zhao, Lin Zhao, Tianyi Zhang, Haixing Dai, Xianyan Chen, Ye Shen, Sheng Li, Brian Murray, Tianming Liu, Andrea Sikora, PharmacyGPT: The AI Pharmacist, arxiv: https://arxiv.org/abs/2307.10432. 2023.

Haixing Dai, Mengxuan Hu, Qing Li, Lu Zhang, Lin Zhao, Dajiang Zhu, Ibai Diez, Jorge Sepulcre, Fan Zhang, Xingyu Gao, Manhua Liu, Quanzheng Li, Sheng Li, Tianming Liu, Xiang Li, Identification of Causal Relationship between Amyloid-beta Accumulation and Alzheimer's Disease Progression via Counterfactual Inference, arxiv: https://arxiv.org/abs/2307.01389. 2023.

Hongmin Cai, Xiaoke Huang, Zhengliang Liu, Wenxiong Liao, Haixing Dai, Zihao Wu, Dajiang Zhu, Hui Ren, Quanzheng Li, Tianming Liu, Xiang Li, Exploring Multimodal Approaches for Alzheimer's Disease Detection Using Patient Speech Transcript and Audio Data, arxiv: https://arxiv.org/abs/2307.02514. 2023.

Haixing Dai, Chong Ma, Zhengliang Liu, Yiwei Li, Peng Shu, Xiaozheng Wei, Lin Zhao, Zihao Wu, Dajiang Zhu, Wei Liu, Quanzheng Li, Tianming Liu, Xiang Li, SAMAug: Point Prompt Augmentation for Segment Anything Model, arxiv: https://arxiv.org/abs/2307.01187. 2023.

Jiaqi Wang, Zhengliang Liu, Lin Zhao, Zihao Wu, Chong Ma, Sigang Yu, Haixing Dai, Qiushi Yang, Yiheng Liu, Songyao Zhang, Enze Shi, Yi Pan, Tuo Zhang, Dajiang Zhu, Xiang Li, Xi Jiang, Bao Ge, Yixuan Yuan, Dinggang Shen, Tianming Liu, Shu Zhang, Review of Large Vision Models and Visual Prompt Engineering, arxiv: https://arxiv.org/abs/2307.00855. 2023.

Saed Rezayi, Zhengliang Liu, Zihao Wu, Chandra Dhakal, Bao Ge, Haixing Dai, Gengchen Mai, Ninghao Liu, Chen Zhen, Tianming Liu, Sheng Li, Exploring New Frontiers in Agricultural NLP: Investigating the Potential of Large Language Models for Food Applications, arxiv: https://arxiv.org/abs/2306.11892. 2023.

Lian Zhang, Zhengliang Liu, Lu Zhang, Zihao Wu, Xiaowei Yu, Jason Holmes, Hongying Feng, Haixing Dai, Xiang Li, Quanzheng Li, Dajiang Zhu, Tianming Liu, Wei Liu, Segment Anything Model (SAM) for Radiation Oncology, arxiv: https://arxiv.org/abs/2306.11730. 2023.

Haixing Dai, Yiwei Li, Zhengliang Liu, Lin Zhao, Zihao Wu, Suhang Song, Ye Shen, Dajiang Zhu, Xiang Li, Sheng Li, Xiaobai Yao, Lu Shi, Quanzheng Li, Zhuo Chen, Donglan Zhang, Gengchen Mai, Tianming Liu, AD-AutoGPT: An Autonomous GPT for Alzheimer's Disease Infodemiology, arxiv: https://arxiv.org/abs/2306.10095. 2023.

Lian Zhang, Jason M. Holmes, Zhengliang Liu, Sujay A. Vora, Terence T. Sio, Carlos E. Vargas, Nathan Y. Yu, Sameer R. Keole, Steven E. Schild, Martin Bues, Sheng Li, Tianming Liu, Jiajian Shen, William W. Wong, Wei Liu, Beam mask and sliding window-facilitated deep learning-based accurate and efficient dose prediction for pencil beam scanning proton therapy, arxiv: https://arxiv.org/abs/2305.18572. 2023.

Zhengliang Liu, Aoxiao Zhong, Yiwei Li, Longtao Yang, Chao Ju, Zihao Wu, Chong Ma, Peng Shu, Cheng Chen, Sekeun Kim, Haixing Dai, Lin Zhao, Dajiang Zhu, Jun Liu, Wei Liu, Dinggang Shen, Xiang Li, Quanzheng Li, Tianming Liu, Radiology-GPT: A Large Language Model for Radiology, arxiv: https://arxiv.org/abs/2306.08666. 2023.

Chong Ma, Lin Zhao, Yuzhong Chen, Sheng Wang, Lei Guo, Tuo Zhang, Dinggang Shen, Xi Jiang and Tianming Liu, Eye-gaze-guided Vision Transformer for Rectifying Shortcut Learning, in press, IEEE Transactions on Medical Imaging, 2023.

Xiang Li, Lu Zhang, Zihao Wu, Zhengliang Liu, Lin Zhao, Yixuan Yuan, Jun Liu, Gang Li, Dajiang Zhu, Pingkuan Yan, Quanzheng Li, Wei Liu, Tianming Liu, Dinggang Shen, Artificial General Intelligence for Medical Imaging, arxiv: https://arxiv.org/abs/2306.05480. 2023.

Zuowei Jiang, Xiaoyan Cai, Libin Yang, Dehong Gao, Wei Zhao, Junwei Han, Jun Liu, Dinggang Shen, Tianming Liu, Learning to Summarize Chinese Radiology Findings with a Pre-trained Encoder, in press, IEEE Transactions on Biomedical Engineering, 2023.

Xiao Yang, Haixing Dai, Zihao Wu, Ramesh Bist, Sachin Subedi, Jin Sun, Guoyu Lu, Changying Li, Tianming Liu, Lilong Chai, SAM for Poultry Science, arxiv: https://arxiv.org/abs/2305.10254. 2023.

Sheng Wang, Zixu Zhuang, Xi Ouyang, Lichi Zhang, Zheren Li, Chong Ma, Tianming Liu, Dinggang Shen, Qian Wang, Learning Better Contrastive View from Radiologist's Gaze, arxiv: https://arxiv.org/abs/2305.08826. 2023.

Yucheng Shi, Hehuan Ma, Wenliang Zhong, Gengchen Mai, Xiang Li, Tianming Liu, Junzhou Huang, ChatGraph: Interpretable Text Classification by Converting ChatGPT Knowledge to Graphs, arxiv: https://arxiv.org/abs/2305.03513. 2023.

Junwen Duan, Fangyuan Wei, Jin Liu, Hongdong Li, Tianming Liu and Jianxin Wang, CDA: A Contrastive Data Augmentation Method for Alzheimer's Disease Detection, ACL 2023.

Zhenxiang Xiao, Yuzhong Chen, Lu Zhang, Junjie Yao, Zihao Wu, Xiaowei Yu, Yi Pan, Lin Zhao, Chong Ma, Xinyu Liu, Wei Liu, Xiang Li, Yixuan Yuan, Dinggang Shen, Dajiang Zhu, Tianming Liu, Xi Jiang, Instruction-ViT: Multi-Modal Prompts for Instruction Learning in ViT, arxiv: https://arxiv.org/abs/2305.00201. 2023. Accepted by Information Fusion.

Jiaqi Wang, Enze Shi, Sigang Yu, Zihao Wu, Chong Ma, Haixing Dai, Qiushi Yang, Yanqing Kang, Jinru Wu, Huawen Hu, Chenxi Yue, Haiyang Zhang, Yiheng Liu, Xiang Li, Bao Ge, Dajiang Zhu, Yixuan Yuan, Dinggang Shen, Tianming Liu, Shu Zhang, Prompt Engineering for Healthcare: Methodologies and Applications, arxiv: https://arxiv.org/abs/2304.14670. 2023.

Ehsan Latif, Gengchen Mai, Matthew Nyaaba, Xuansheng Wu, Ninghao Liu, Guoyu Lu, Sheng Li, Tianming Liu, Xiaoming Zhai, Artificial General Intelligence (AGI) for Education, arxiv: https://arxiv.org/abs/2304.12479. 2023.

Wenxiong Liao, Zhengliang Liu, Haixing Dai, Shaochen Xu, Zihao Wu, Yiyang Zhang, Xiaoke Huang, Dajiang Zhu, Hongmin Cai, Tianming Liu, Xiang Li, Differentiate ChatGPT-generated and Human-written Medical Texts, arxiv: https://arxiv.org/abs/2304.11567. 2023. Accepted by Journal of Medical Internet Research. 2024.

Tianyang Zhong, Yaonai Wei, Li Yang, Zihao Wu, Zhengliang Liu, Xiaozheng Wei, Wenjun Li, Junjie Yao, Chong Ma, Xiang Li, Dajiang Zhu, Xi Jiang, Junwei Han, Dinggang Shen, Tianming Liu, Tuo Zhang, ChatABL: Abductive Learning via Natural Language Interaction with ChatGPT, arxiv: https://arxiv.org/abs/2304.11107. 2023.

Zihao Wu, Lu Zhang, Chao Cao, Xiaowei Yu, Haixing Dai, Chong Ma, Zhengliang Liu, Lin Zhao, Gang Li, Wei Liu, Quanzheng Li, Dinggang Shen, Xiang Li, Dajiang Zhu, Tianming Liu, Exploring the Trade-Offs: Unified Large Language Models vs Local Fine-Tuned Models for Highly-Specific Radiology NLI Task, arxiv: https://arxiv.org/abs/2304.09138. 2023.

Chong Ma, Zihao Wu, Jiaqi Wang, Shaochen Xu, Yaonai Wei, Zhengliang Liu, Lei Guo, Xiaoyan Cai, Shu Zhang, Tuo Zhang, Dajiang Zhu, Dinggang Shen, Tianming Liu, Xiang Li, ImpressionGPT: An Iterative Optimizing Framework for Radiology Report Summarization with ChatGPT, arxiv: https://arxiv.org/abs/2304.08448. 2023. Accepted by IEEE Transactions on Artificial Intelligence. 2024.  

Gengchen Mai, Weiming Huang, Jin Sun, Suhang Song, Deepak Mishra, Ninghao Liu, Song Gao, Tianming Liu, Gao Cong, Yingjie Hu, Chris Cundy, Ziyuan Li, Rui Zhu, Ni Lao, On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence, arxiv: https://arxiv.org/abs/2304.06798. 2023. Accepte by ACM Transactions on Spatial Algorithms and Systems. 2024.

Guoyu Lu, Sheng Li, Gengchen Mai, Jin Sun, Dajiang Zhu, Lilong Chai, Haijian Sun, Xianqiao Wang, Haixing Dai, Ninghao Liu, Rui Xu, Daniel Petti, Changying Li, Tianming Liu, AGI for Agriculture, arxiv: https://arxiv.org/abs/2304.06136. 2023.   

Jason Holmes, Zhengliang Liu, Lian Zhang, Yuzhen Ding, Terence T. Sio, Lisa A. McGee, Jonathan B. Ashman, Xiang Li, Tianming Liu, Jiajian Shen, Wei Liu, Evaluating Large Language Models on a Highly-specialized Topic, Radiation Oncology Physics, arxiv: https://arxiv.org/abs/2304.01938. Accepted by Frontiers in Oncology. 2023.

Yiheng Liu, Tianle Han, Siyuan Ma, Jiayue Zhang, Yuanyuan Yang, Jiaming Tian, Hao He, Antong Li, Mengshen He, Zhengliang Liu, Zihao Wu, Dajiang Zhu, Xiang Li, Ning Qiang, Dingang Shen, Tianming Liu, Bao Ge, Summary of ChatGPT/GPT-4 Research and Perspective Towards the Future of Large Language Models, arxiv: https://arxiv.org/abs/2304.01852. Accepted by Meta-Radiology. 2023.

Lin Zhao, Lu Zhang, Zihao Wu, Yuzhong Chen, Haixing Dai, Xiaowei Yu, Zhengliang Liu, Tuo Zhang, Xintao Hu, Xi Jiang, Xiang Li, Dajiang Zhu, Dinggang Shen, Tianming Liu, When Brain-inspired AI Meets AGI, https://arxiv.org/abs/2303.15935. Accepted by Meta-Radiology. 2023.  

Zhengliang Liu, Xiaowei Yu, Lu Zhang, Zihao Wu, Chao Cao, Haixing Dai, Lin Zhao, Wei Liu, Dinggang Shen, Quanzheng Li, Tianming Liu, Dajiang Zhu, Xiang Li, DeID-GPT: Zero-shot Medical Text De-Identification by GPT-4, arxiv: https://arxiv.org/abs/2303.11032. 2023.  

Haixing Dai, Zhengliang Liu, Wenxiong Liao, Xiaoke Huang, Zihao Wu, Lin Zhao, Wei Liu, Ninghao Liu, Sheng Li, Dajiang Zhu, Hongmin Cai, Quanzheng Li, Dinggang Shen, Tianming Liu, Xiang Li, ChatAug: Leveraging ChatGPT for Text Data Augmentation, arxiv: https://arxiv.org/abs/2302.13007. 2023.  

Wenxiong Liao, Zhengliang Liu, Haixing Dai, Zihao Wu, Yiyang Zhang, Xiaoke Huang, Yuzhong Chen, Xi Jiang, Dajiang Zhu, Tianming Liu, Sheng Li, Xiang Li, Hongmin Cai, Mask-guided BERT for Few Shot Text Classification, arxiv: https://arxiv.org/abs/2302.10447. 2023.

Hongmin Cai, Wenxiong Liao, Zhengliang Liu, Yiyang Zhang, Xiaoke Huang, Siqi Ding, Hui Ren, Zihao Wu, Haixing Dai, Sheng Li, Lingfei Wu, Ninghao Liu, Quanzheng Li, Tianming Liu, Xiang Li, Coarse-to-fine Knowledge Graph Domain Adaptation based on Distantly-supervised Iterative Training, arxiv: https://arxiv.org/abs/2211.02849. 2023.

Zhengliang Liu, Xinyu He, Lei Liu, Tianming Liu, Xiaoming Zhai, Context Matters: A Strategy to Pre-train Language Model for Science Education, AIED 2023. arxiv: https://arxiv.org/abs/2301.12031.

Xuansheng Wu, Xinyu He, Tianming Liu, Ninghao Liu, Xiaoming Zhai, Matching Exemplar as Next Sentence Prediction (MeNSP): Zero-shot Prompt Learning for Automatic Scoring in Science Education, AIED 2023. arxiv: https://arxiv.org/abs/2301.08771.

Zhengliang Liu, Mengshen He, Zuowei Jiang, Zihao Wu, Haixing Dai, Lian Zhang, Siyi Luo, Tianle Han, Xiang Li, Xi Jiang, Dajiang Zhu, Xiaoyan Cai, Bao Ge, Wei Liu, Jun Liu, Dinggang Shen, Tianming Liu. Survey on natural language processing in medical imaging analysis. Journal of Central South University. Medical Science, 2022, 47(8): 981- 993.

Saed Rezayi, Zhengliang Liu, Zihao Wu, Chandra Dhakal, Bao Ge, Chen Zhen, Tianming Liu, Sheng Li, AgriBERT: Knowledge-Infused Agricultural Language Models for Matching Food and Nutrition. In IJCAI-ECAI 2022 Special Track on AI for Good, 2022.

Saed Rezayi, Haixing Dai, Zhengliang Liu, Zihao Wu, Akarsh Hebbar, Andrew H. Burns, Lin Zhao, Dajiang Zhu, Xiang Li, Quanzheng Li, Wei Liu, Sheng Li and Tianming Liu. ClinicalRadioBERT: Knowledge-Infused Few Shot Learning for Clinical Notes Named Entity Recognition. In: The 13th International Workshop on Machine Learning in Medical Imaging (MLMI 2022), in conjunction with MICCAI 2022, 2022.

Xiaoyan Cai, Sen Liu, Junwei Han, Libin Yang, Zhenguo Liu and Tianming Liu, ChestXRayBERT: A Pretrained Language Model for Chest Radiology Report Summarization, in press, IEEE Transactions on Multimedia, 2021.

Xiaoyan Cai, Sen Liu, Junwei Han, Libin Yang, Xin Mei, Yan Lu, Dingang Shen and Tianming Liu, COVIDSum: A Linguistically Enriched SciBERT-based Summarization Model for COVID-19 Scientific Papers, in press, Journal of Biomedical Informatics, 2021.

Highlight Journal/Conference Papers on Brain Imaging, Computational Neuroscience, and Brain-inspired Artificial Intelligence

Xia-An Bi, Zhaoxu Xing, Zicheng Yang, Yangjun Huang, Luyun Xu, Zihao Wu, Zhengliang Liu, Xiang Li, and Tianming Liu, CE-GAN: Community Evolutionary Generative Adversarial Network for Alzheimer's Disease Risk Prediction, in press, IEEE Transactions on Medical Imaging, 2024.

Lin Zhao, Haixing Dai, Zihao Wu, Xi Jiang, Dajiang Zhu, Tuo Zhang, Tianming Liu, Hierarchical functional differences between gyri and sulci at different scales, in press, Cerebral Cortex, 2024.

Chao Cao, Xiaowei Yu, Lu Zhang, Tong Chen, Yanjun Lyu, Tianming Liu and Dajiang Zhu. Enhancing Group-Wise Consistency in 3-Hinge Gyrus Matching via Anatomical Embedding and Structural Connectivity Optimization. International Symposium on Biomedical Imaging (ISBI), 2024. 

Yanjun Lyu, Lu Zhang, Xiaowei Yu, Tianming Liu and Dajiang Zhu, Mild Cognitive Impairment Classification Using A Novel Finer-Scale Brain Connectome, International Symposium on Biomedical Imaging (ISBI), 2024. 

Yiheng Liu, Enjie Ge, Zili Kang, Ning Qiang, Tianming Liu, Bao Ge, Spatial-Temporal Convolutional Attention for Discovering and Characterizing Functional Brain Networks in Task fMRI, in press, NeuroImage, 2024.

Wei Mao, Yuzhong Chen, Zhibin He, Zifan Wang, Zhenxiang Xiao, Yusong Sun, Liang He, Jingchao Zhou, Weitong Guo, Chong Ma, Lin Zhao, Keith M Kendrick, Bo Zhou, Benjamin Becker, Tianming Liu, Tuo Zhang, Xi Jiang, Brain Structural Connectivity Guided Vision Transformers for Identification of Functional Connectivity Characteristics in Preterm Neonates, in press, IEEE Journal of Biomedical and Health Informatics, 2024.

Yuzhong Chen, Zhenxiang Xiao, Yu Du, Lin Zhao, Lu Zhang, Zihao Wu, Dajiang Zhu, Tuo Zhang, Dezhong Yao, Xintao Hu, Tianming Liu, Xi Jiang, A Unified and Biologically-Plausible Relational Graph Representation of Vision Transformers, in press, IEEE Transactions on Neural Networks and Learning Systems, 2023.  

Yiheng Liu, Enjie Ge, Mengshen He, Zhengliang Liu, Shijie Zhao, Xintao Hu, Ning Qiang, Dajiang Zhu, Tianming Liu, Bao Ge, Mapping Dynamic Spatial Patterns of Brain Function with Spatial-wise Attention, in press, Journal of Neural Engineering, 2023.

Lu Zhang, Li Wang, Tianming Liu, and Dajiang Zhu, Disease2Vec: Representing Alzheimer’s Progression via Disease Embedding Tree, in press, Pharmacological Research, 2023.

Xintao Hu, Yang Yang, Shijie Zhao, Xi Jiang, Lei Guo, Junwei Han, Tianming Liu, Frequency-specific Functional Difference between Gyri and Sulci in Naturalistic Paradigm fMRI, in press, Brain Structure and Function, 2023.

Enze Shi, Sigang Yu, Yanqing Kang, Jinru Wu, Lin Zhao, Dajiang Zhu, Jinglei Lv, Tianming Liu, Xintao Hu, Shu Zhang, MEET: A Multi-band EEG Transformer for Brain States Decoding, in press, IEEE Transactions on Biomedical Engineering, 2023.

Songyao Zhang, Tuo Zhang, Guannan Cao, Jingchao Zhou, Zhibin He, Xiao Li, Yudan Ren, Xi Jiang, Lei Guo, Junwei Han & Tianming Liu. Species-Shared and Species-Unique Gyral Peaks between Human and Macaque Brain. eLife, in press. 2023.

Songyao Zhang, Tuo Zhang, Zhibin He, Xiao Li, Lu Zhang, Dajiang Zhu, Xi Jiang, Tianming Liu, Junwei Han & Lei Guo. Gyral Peaks and Patterns in Human Brains. Cerebral Cortex, 33.11: 6708-6722, 2023.

Xia-an Bi, Yangjun Huang, Ke Chen, Siyu Jiang, Zhaoxu Xing, Luyun Xu, Zhengliang Liu, Xiang Li, Tianming Liu, Structure Mapping Generative Adversarial Network for Multi-view Information Mapping Pattern Mining, in press, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023.

Liting Wang; Yudan Ren; Jinglei Lv; Shijie Zhao; Lei Guo; Tianming Liu; Junwei Han, Xintao Hu, Arousal Modulates the Amygdala-insula Reciprocal Connectivity during Naturalistic Emotional Movie Watching, in press, NeuroImage. 2023.

Ying Huang, Tuo Zhang, Songyao Zhang, Weihan Zhang, Li Yang, Dajiang Zhu, Tianming Liu, Xi Jiang, Junwei Han, Lei Guo, Genetic Influence on Gyral Peaks, in press, NeuroImage, 2023.

Qiyu Wang, Shijie Zhao, Tianming Liu, Junwei Han, Cirong Liu, Temporal fingerprints of cortical gyrification in marmosets and humans, in press, Cerebral Cortex, 2023.

Lin Zhao, Zihao Wu, Haixing Dai, Zhengliang Liu, Tuo Zhang, Dajiang Zhu, Tianming Liu, A Generic Framework for Embedding Human Brain Function with Temporally Correlated Autoencoder, in press, Medical Image Analysis, 2023.

Shu Zhang, Enze Shi, Lin Wu, Ruoyang Wang, Sigang Yu, Zhengliang Liu, Shaochen Xu, Tianming Liu, Shijie Zhao, Differentiating brain states via multi-clip random fragment strategy-based interactive bidirectional recurrent neural network, in press, Neural Networks. 2023.

Fenqiang Zhao, Zhengwang Wu, Dajiang Zhu, Tianming Liu, John Gilmore, Weili Lin, Li Wang, Gang Li, Disentangling Site Effects with Cycle-Consistent Adversarial Autoencoder for Multi-site Cortical Data Harmonization, in press, MICCAI 2023.

Tianyang Zhong, Xiaozheng Wei, Enze Shi, Jiaxing Gao, Chong Ma, Yaonai Wei, Songyao Zhang, Lei Guo, Junwei Han, Tianming Liu, Tuo Zhang, A Small-Sample Method with EEG Signals Based on Abductive Learning for Motor Imagery Decoding, in press, MICCAI 2023.

Lu Zhang, Saiyang Na, Tianming Liu, Dajiang Zhu, Junzhou Huang, Multimodal Deep Fusion in Hyperbolic Space for Mild Cognitive Impairment Study, accepted, MICCAI 2023.

Zhengwang Wu, Jiale Chen, Fengqiang Zhao, Ya Wang, Yue Sun, Dajiang Zhu, Tianming Liu, Valerie Jewells, Weili Lin, Li Wang, Gang Li, Weakly Supervised Cerebellar Cortical Surface Parcellation with Self-Visual Representation Learning, accepted, MICCAI 2023.

Jiaxing Gao, Lin Zhao, Tianyang Zhong, Changhe Li, Zhibin He, Yaonai Wei, Shu Zhang, Lei Guo, Tianming Liu, Junwei Han, Tuo Zhang, Prediction of Cognitive Scores by Joint Use of Movie-watching fMRI Connectivity and Eye Tracking via Attention-CensNet, accepted, MICCAI 2023.

Lin Zhao, Haixing Dai, Zihao Wu, Zhe Xiao, Lu Zhang, Xintao Hu, Xi Jiang, Sheng Li, Dajiang Zhu, Tianming Liu, Coupling Visual Semantics of Artificial Neural Networks and Human Brain Function via Synchronized Activations, in press, IEEE Transactions on Cognitive and Developmental Systems, 2023.

Poorya Chavoshnejad, Liangjun Chen, Xiaowei Yu, Jixin Hou, Nicholas Filla, Dajiang Zhu, Tianming Liu, Gang Li, Mir Jalil Razavi, Xianqiao Wang, An Integrated Finite Element Method and Machine Learning Algorithm for Brain Morphology Prediction, in press, Cerebral Cortex, 2023.

Yifan Lv, Zili Kang, Tianle Han, Mengshen He, Ruhai Du, Tuo Zhang, Tianming Liu, Bao Ge, Cerebral Cortical Regions Always Connect with Each Other via the Shortest Paths, in press, Cerebral Cortex, 2023.

Mengyue Zhou, Xu Liu, Zihao Wu, Zhengliang Liu, Lin Zhao, Dajiang Zhu, Lei Guo, Junwei Han, Tianming Liu and Xintao Hu, Fine-grained Artificial Neurons in Audio-transformers for Disentangling Neural Auditory Encoding, ACL 2023.

Xia-An Bi, Sheng Luo, Yu Wang, Siyu Jiang, Wenyan Zhou, Zhengliang Liu, Luyun Xu, and Tianming Liu, Community Graph Convolution Neural Network for Alzheimer's Disease Classification and Pathogenetic Factors Identification, in press, IEEE Transactions on Neural Networks and Learning Systems, 2023.  

Zhenwei Wang, Mengshen He, Yifan Lv, Enjie Ge, Shu Zhang, Ning Qiang, Tianming Liu, Fan Zhang, Xiang Li, Bao Ge, Accurate Corresponding Fiber Tract Segmentation via FiberGeoMap Learner with Application to Autism, in press, Cerebral Cortex, 2023.

Lin Zhao, Hexin Dong, Ping Wu, Jiaying Lu, Le Lu, Jingren Zhou, Tianming Liu, Li Zhang, Ling Zhang, Yuxing Tang, Chuantao Zuo, MetaViT: Metabolism-Aware Vision Transformer for Differential Diagnosis of Parkinsonism with 18F-FDG PET, IPMI 2023.

Li Yang, Songyao Zhang, Weihan Zhang, Jingchao Zhou, Tianyang Zhong, Yaonai Wei, Yixuan Yuan, Xi Jiang, Junwei Han, Tianming Liu, Tuo Zhang, Species-Shared and -Specific Brain Functional Connectomes Revealed by Shared-Unique Variational Autoencoder, IPMI 2023.

Linus Manubens-Gil, Zhi Zhou, Hanbo Chen, Arvind Ramanathan, Xiaoxiao Liu, Yufeng Liu, Alessandro Bria, Todd Gillette, Zongcai Ruan, Jian Yang, Miroslav Radojevic, Ting Zhao, Li Cheng, Lei Qu, Siqi Liu, Kristofer Bouchard, Lin Gu, Weidong Cai, Shuiwang Ji, Badrinath Roysam, Ching-Wei Wang, Hongchuan Yu, Amos Sironi, Daniel Maxim Iascone, Jie Zhou, Erhan Bas, Eduardo Conde-Sousa, Paulo Aguiar, Xiang Li, Yujie Li, Sumit Nanda, Yuan Wang, Leila Muresan, Pascal Fua, Bing Ye, Haiyan He, Jochen F. Staiger, Manuel Peter, Daniel N. Cox, Michel Simonneau, Marcel Oberlaender, Gregory Jefferis, Kei Ito, Paloma Gonzalez-Bellido, Jinhyun Kim, Edwin Rubel, Hollis T. Cline, Hongkui Zeng, Aljoscha Nern, Ann-Shyn Chiang, Jane Roskams, Rick Livesey, Janine Stevens, Tianming Liu, Chinh Dang, Yike Guo, Ning Zhong, Georgia Tourassi, Sean Hill, Michael Hawrylycz, Christof Koch, Erik Meijering, Giorgio A. Ascoli, Hanchuan Peng, BigNeuron: A resource to benchmark and predict best-performing algorithms for automated reconstruction of neuronal morphology, accepted, Nature Methods, 2023.

Xu Liu, Mengyue Zhou, Gaosheng Shi, Yu Du, Lin Zhao, Zihao Wu, Tianming Liu, Xintao Hu, Coupling Artificial Neurons in BERT and Biological Neurons in the Human Brain, AAAI 2023.

Xi Jiang, Jiadong Yan, Yu Zhao, Mingxin Jiang, Yuzhong Chen, Jingchao Zhou, Zhenxiang Xiao, Zifan Wang, Rong Zhang, Benjamin Becker, Dajiang Zhu, Keith M. Kendrick*, and Tianming Liu*. Characterizing Functional Brain Networks via Spatio-Temporal Attention 4D Convolutional Neural Networks (STA-4DCNNs). *Joint corresponding authors, Neural Networks, in press, 2022.

Lu Zhang, Lin Zhao, Zihao Wu, Xianqiao Wang, Tianming Liu*, Dajiang Zhu*, Cortex2vector: Anatomical Embedding of Cortical Folding, *Joint corresponding authors, Cerebral Cortex, in press, 2022. 

Jiadong Yan, Yuzhong Chen, Shimin Yang, Shu Zhang, Mingxin Jiang, Zhongbo Zhao, Tuo Zhang, Jinglei Lv, Benjamin Becker, Junwei Han, Keith M. Kendrick, Tianming Liu, Xi Jiang, Modeling Spatio-Temporal Patterns of Holistic Functional Brain Networks via Multi-Head Guided Attention Graph Neural Networks (Multi-Head GAGNNs), in press, Medical Image Analysis, 2022.

Tianji Pang, Junwei Han, Shijie Zhao, Shu Zhang, Lei Guo, Tianming Liu, Gumbel-Softmax based Neural Architecture Search for Optimal Decomposition of Hierarchical Brain Networks, in press, Medical Image Analysis, 2022.

Qiyu Wang, Junwei Han, Shijie Zhao, Zhibin He, Shu Zhang, Xi Jiang, Tuo Zhang, Cirong Liu, Tianming Liu, Modeling Functional Difference between Gyri and Sulci within Intrinsic Connectivity Networks, in press, Cerebral Cortex, 2022.

Jing Yuan, Senquan Ji, Liao Luo, Jinglei Lv, Tianming Liu, Control Energy Assessment of Spatial Interactions among Macro-Scale Brain Networks, in press, Human Brain Mapping, 2022.

Shengfeng Liu, Fangfei Ge, Lin Zhao, Tianfu Wang, Dong Ni, Tianming Liu, NAS-optimized Topology-preserving Transfer Learning for Differentiating Cortical Folding Patterns, in press, Medical Image Analysis, 2021.

Qing Li, Wei Zhang, Lin Zhao, Xia Wu, and Tianming Liu, Evolutional Neural Architecture Search for Optimization of Spatiotemporal Brain Network Decomposition, in press, IEEE Transactions on Biomedical Engineering, 2021.

Mir Jalil Razavi, Tianming Liu, and Xianqiao Wang, Mechanism Exploration of 3-Hinge Gyral Formation and Pattern Recognition, in press, Cerebral Cortex Communications, 2021.

Xi Jiang, Tuo Zhang, Shu Zhang, Keith M Kendrick, Tianming Liu, Fundamental Functional Differences between Gyri and Sulci: Implications for Brain Function, Cognition and Behavior, in press, Psychoradiology, 2021.

Qing Li, Xia Wu, Tianming Liu, Differentiable Neural Architecture Search for Optimal Spatial/Temporal Brain Function Network Decomposition, in press, Medical Image Analysis, 2021.

Xiao Li, Tao Liu, Yujie Li, Qing Li, Xianqiao Wang, Xintao Hu, Lei Guo, Tuo Zhang, Tianming Liu, Marmoset Brain ISH Data Revealed Molecular Difference Between Cortical Folding Patterns, in press, Cerebral Cortex, 2020.

Liting Wang, Xintao Hu, Huan Liu, Shijie Zhao, Lei Guo, Junwei Han, Tianming Liu, Functional Brain Networks underlying Auditory Saliency during Naturalistic Listening Experience, in press, IEEE Transactions on Cognitive and Developmental Systems, 2020.

Tuo Zhang, Ying Huang, Lin Zhao, Zhibin He, Xi Jiang, Lei Guo, Xiaoping Hu, Tianming Liu, Identifying Cross-individual Correspondences of 3-hinge Gyri, Medical Image Analysis, 2020.

Qinglin Dong, Fangfei Ge, Qiang Ning, Yu Zhao, Jinglei Lv, Heng Huang, Jing Yuan, Xi Jiang, Dinggang Shen, and Tianming Liu, Modeling Hierarchical Brain Networks via Volumetric Sparse Deep Belief Network (VS-DBN), IEEE Transactions on Biomedical Engineering, 2019.

Shu Zhang, Qinglin Dong, Wei Zhang, Heng Huang, Dajiang Zhu, Tianming Liu, Discovering Hierarchical Common Brain Networks via Multimodal Deep Belief Network, Medical Image Analysis, 2019.

Yu Zhao, Xiang Li, Heng Huang, Wei Zhang, Shijie Zhao, Milad Makkie, Mo Zhang, Quanzheng Li, Tianming Liu, 4D Modeling of fMRI Data via Spatio-Temporal Convolutional Neural Networks (ST-CNN), IEEE Transactions on Cognitive and Developmental Systems, 2019.

Han Wang, Shijie Zhao, Qinglin Dong, Yan Cui, Yaowu Chen, Junwei Han, Li Xie, Tianming Liu, Recognizing Brain States Using Deep Sparse Recurrent Neural Network, IEEE Transactions on Medical Imaging, 2018.

Tuo Zhang, Hanbo Chen, Mir Jalil Razavi, Yujie Li, Fangfei Ge, Lei Guo, Xianqiao Wang, Tianming Liu, Exploring 3-hinge Gyral Folding Patterns among HCP Q3 868 Human Subjects, Human Brain Mapping, 2018.

Huan Liu, Shu Zhang, Xi Jiang, Tuo Zhang, Heng Huang, Fangfei Ge, Lin Zhao, Xiao Li, Xintao Hu, Junwei Han, Lei Guo, Tianming Liu, The Cerebral Cortex is Bisectionally Segregated into Two Fundamentally Different Functional Units of Gyri and Sulci, Cerebral Cortex, 2018.

Yu Zhao, Fangfei Ge, Tianming Liu, Automatic Recognition of Holistic Functional Brain Networks Using Iteratively Optimized Convolutional Neural Networks (IO-CNN) with Weak Label Initialization, Medical Image Analysis, 2018.

Han Wang, Kun Xie, Zhichao Lian, Yan Cui, Yaowu Chen, Jing Zhang, Li Xie, Joe Tsien, Tianming Liu, Large-scale Circuitry Interactions upon Earthquake Experiences Revealed by Recurrent Neural Networks, IEEE Transactions on Neural Systems & Rehabilitation Engineering, 2018. 

Jing Yuan, Xiang Li, Jinhe Zhang, Liao Luo, Qinglin Dong, Jinglei Lv, Yu Zhao, Xi Jiang, Shu Zhang, Wei Zhang, Tianming Liu, Spatio-temporal Modeling of Connectome-Scale Brain Network Interactions via Time-evolving Graphs, NeuroImage, 2017.

Fangfei Ge*, Xiao Li*, Mir Jalil Razavi*, Hanbo Chen, Tuo Zhang, Shu Zhang, Lei Guo, Xiaoping Hu, Xianqiao Wang**, Tianming Liu**, Denser Growing Fiber Connections Induce 3-hinge Gyral Folding, *Joint first authors, **Joint correspondence authors, Cerebral Cortex, 2017.

Hanbo Chen*, Yujie Li*, Fangfei Ge, Gang Li, Dinggang Shen, Tianming Liu, Gyral Net: A New Representation of Cortical Folding Organization, Medical Image Analysis, 2017.

Yu Zhao, Qinglin Dong, Hanbo Chen, Armin Iraji, Yujie Li, Milad Makkie, Zhifeng Kou, Tianming Liu, Constructing Fine-granularity Functional Brain Network Atlases via Deep Convolutional Autoencoder, Medical Image Analysis, 2017.

Tuo Zhang*, Mir Jalil Razavi*, Hanbo Chen, Yujie Li, Xiao Li, Longchuan Li, Lei Guo, Xiaoping Hu, Tianming Liu**, Xianqiao Wang**, Mechanisms of Gyral Convolution in Circumferential Direction of Primate Brains, *These authors contributed equally to this work, **Joint correspondence authors, Journal of Computational Neuroscience, 2017.

Heng Huang, Xintao Hu, Yu Zhao, Milad Makkie, Qinglin Dong, Shijie Zhao, Lei Guo, Tianming Liu, Modeling Task fMRI Data via Deep Convolutional Autoencoder, IEEE Transactions on Medical Imaging, 2017.

Xiang Li*, Milad Makkie*, Binbin Lin, Mojtaba Sedigh Fazli, Ian Davidson, Jieping Ye#, Tianming Liu#, Shannon Quinn#, Scalable Fast Rank-1 Dictionary Learning for fMRI Big Data Analysis, *Equal contributions; #Joint corresponding authors. pp. 511-519, ACM KDD, 2016.

Xiao Li*, Hanbo Chen*, Tuo Zhang*, Xiang Yu, Xi Jiang, Kaiming Li, Longchuan Li, Mir Jalil Razavi, Xianqiao Wang, Xintao Hu, Junwei Han, Lei Guo, Xiaoping Hu**, Tianming Liu**, Commonly-Preserved and Species-Specific Gyral Folding Patterns across Primate Brains, *Co-first authors; **Joint corresponding authors. Brain Structure and Function, 2016.

Tuo Zhang*, Mir Jalil Razavi*, Xiao Li, Hanbo Chen, Tianming Liu**, Xianqiao Wang**, Mechanism of Consistent Gyrus Formation: an Experimental and Computational Study, *These authors contributed equally to this work. **Joint correspondence authors. Scientific Reports, 2016.

Jinglei Lv, Binbin Lin, Qingyang Li, Wei Zhang, Yu Zhao, Xi Jiang, Lei Guo, Junwei Han, Xintao Hu, Christine Guo, Jieping Ye, Tianming Liu, Task FMRI Data Analysis Based on Supervised Stochastic Coordinate Coding, Medical Image Analysis, 2016.

Nian Liu, Junwei Han, Tianming Liu, Xuelong Li, Learning to Predict Eye Fixations via Multiresolution Convolutional Neural Networks, IEEE Transactions on Neural Networks and Learning Systems, pp. 362-370, 2016.

Sidi Liu, Yimin Hou, Ting Xiao, Qinglin Dong, Jinglei Lv, Tianming Liu, What Makes a Good Movie Trailer? Interpretation from Simultaneous EEG and Eyetracker Recording, ACM Multimedia, pp. 82-86, 2016.

Xi Jiang, Xiang Li, Jinglei Lv, Shijie Zhao, Shu Zhang, Wei Zhang, Tuo Zhang, Junwei Han, Lei Guo, Tianming Liu, Temporal Dynamics Assessment of Spatial Overlap Pattern of Functional Brain Networks Reveals Novel Functional Architecture of Cerebral Cortex, IEEE Transactions on Biomedical Engineering, 2016.

Gong Cheng, Junwei Han, Lei Guo, Tianming Liu, Learning Coarse-to-Fine Sparselets for Efficient Object Detection and Scene Classification, pp. 1173-1181, CVPR 2015.

Nian Liu, Junwei Han, Dingwen Zhang, Shifeng Wen, Tianming Liu, Predicting Eye Fixations using Convolutional Neural Networks, pp. 362-370, CVPR 2015.

Xi Jiang, Xiang Li, Jinglei Lv, Tuo Zhang, Shu Zhang, Lei Guo, Tianming Liu, Sparse Representation of HCP Grayordinate Data Reveals Novel Functional Architecture of Cerebral Cortex, Human Brain Mapping, 2015.

Hanbo Chen, Tao Liu, Yu Zhao, Tuo Zhang, Yujie Li, Meng Li, Hongmiao Zhang, Hui Kuang, Lei Guo, Joe Tsien*, Tianming Liu*, Optimization of Large-scale Mouse Brain Connectome via Joint Evaluation of DTI and Neuron Tracing Data, *Joint corresponding authors, NeuroImage, 2015.

Shijie Zhao, Junwei Han, Jinglei Lv, Xi Jiang, Xintao Hu, Yu Zhao, Bao Ge, Lei Guo, Tianming Liu, Supervised Dictionary Learning for Inferring Concurrent Brain Networks, IEEE Transactions on Medical Imaging, 2015.

Junwei Han, Xiang Ji, Xintao Hu, Lei Guo, and Tianming Liu, Arousal Recognition Using Audio-Visual Features and FMRI-based Brain Response, IEEE Transactions on Affective Computing, 6(4):337-347, 2015.

Junwei Han, Dingwen Zhang, Shifeng Wen, Lei Guo, Tianming Liu, and Xuelong Li, Two-stage Learning to Predict Human Eye Fixations via Stacked Denoising Autoencoders, IEEE Transactions on Cybernatics, 46(2):487-498, 2015.

Xintao Hu, Cheng Lv, Gong Cheng, Jinglei Lv, Lei Guo, Junwei Han, Tianming Liu, Sparsity Constrained fMRI Decoding of Visual Saliency in Naturalistic Video Streams, IEEE Transactions on Autonomous Mental Development, 7(2):65-75, 2015. 

Xintao Hu, Lei Guo, Junwei Han*, Tianming Liu*, Decoding Semantics Categorization during Natural Viewing of Video Streams, IEEE Transactions on Autonomous Mental Development, 7(3):201-210, 2015. *Co-corresponding authors.

Jinglei Lv*, Xi Jiang*, Xiang Li*, Dajiang Zhu*, Shu Zhang, Shijie Zhao, Hanbo Chen, Tuo Zhang, Xintao Hu, Junwei Han, Jieping Ye, Lei Guo,  Tianming Liu, Holistic Atlases of Functional Networks and Interactions Reveal Reciprocal Organizational Architecture of Cortical Function, *These authors contributed equally to this work, IEEE Transactions on Biomedical Engineering, 2014.

Jinglei Lv*, Xi Jiang*, Xiang Li*, Dajiang Zhu, Hanbo Chen, Tuo Zhang, Shu Zhang, Xintao Hu, Junwei Han, Heng Huang, Jing Zhang, Lei Guo, Tianming Liu, Sparse Representation of Whole-brain FMRI Signals for Identification of Functional Networks, *These authors contributed equally to this work, Medical Image Analysis, 2014.

Junwei Han, Changyuan Chen, Xintao Hu, Lei Guo and Tianming Liu, Learning Computational Models of Video Memorability from FMRI Brain Imaging, IEEE Transactions on Cybernetics, 2014.

Jinli Ou*, Zhichao Lian*, Li Xie, Xiang Li, Peng Wang, Yun Hao, Dajiang Zhu, Rongxin Jiang, Yufeng Wang, Yaowu Chen, Jing Zhang**, Tianming Liu**, Atomic Dynamic Functional Interaction Patterns for Characterization of ADHD, *Joint first authors, **Joint corresponding authors, Human Brain Mapping, 35(10):5262-5278, 2014.

Tuo Zhang, Hanbo Chen, Lei Guo, Kaiming Li, Longchuan Li, Shu Zhang, Dinggang Shen, Xiaoping Hu, Tianming Liu, Characterization of U-shape Streamline Fibers: Methods and Applications, Medical Image Analysis. 2014.

Junwei Han, Changyuan Chen, Xintao Hu, Lei Guo and Tianming Liu, Learning Computational Models of Video Memorability from FMRI Brain Imaging, IEEE Transactions on Cybernetics, 45(8):1692-1703, 2014.

Jing Zhang*, Xiang Li, Cong Li, Zhichao Lian, Xiu Huang, Guocheng Zhong,  Dajiang Zhu, Kaiming Li, Changfeng Jin, Xintao Hu, Junwei Han,  Lei Guo, Xiaoping Hu, Lingjiang Li, Tianming Liu*, Inferring Functional Interaction and Transition Patterns via  Dynamic Bayesian Variable Partition Models, *Joint corresponding authors, Human Brain Mapping, 2013.

Hanbo Chen, Kaiming Li, Dajiang Zhu, Xi Jiang, Yixuan Yuan, Peili Lv, Tuo Zhang, Lei Guo, Dinggang Shen*, Tianming Liu*, Inferring Group-wise Consistent Multimodal Brain Networks via Multi-view Spectral Clustering, *Joint corresponding authors, IEEE Transactions on Medical Imaging, 2013.

Junwei Han, Xiang Ji, Xintao Hu, Dajiang Zhu, Kaiming Li, Xi Jiang, Guangbin Cui, Lei Guo, and Tianming Liu, Representing and Retrieving Video Shots in Human-Centric Brain Imaging Space, IEEE Transactions on Image Processing, 2013.

Tuo Zhang, Dajiang Zhu, Xi Jiang, Bao Ge, Xintao Hu, Junwei Han, Lei Guo, Tianming Liu, Predicting Cortical ROIs via Joint Modeling of Anatomical and Connectional Profiles, Medical Image Analysis, 2013.

Tianming Liu, Xintao Hu, Xiaojin Li, Mo Chen, Junwei Han, Lei Guo, Merging Neuroimaging and Multimedia: Methods, Opportunities and Challenges, IEEE Transactions on Human-Machine Systems, 44(2):270-280, 2013.

Xiang Li, Dajiang Zhu, Xi Jiang, Changfeng Jin, Xin Zhang, Lei Guo, Jing Zhang, Xiaoping Hu, Jingjiang Li, Tianming Liu, Dynamic Functional Connectomics Signatures for Characterization and Differentiation of PTSD Patients, Human Brain Mapping, 2013.

Fan Deng, Xi Jiang, Dajiang Zhu, Tuo Zhang, Kaiming Li, Lei Guo, Tianming Liu, A functional model of cortical gyri and sulci, Brain Structure and Function, 2013.

Hanbo Chen*, Tuo Zhang*, Lei Guo, Kaiming Li, Xiang Yu, Longchuan Li, Xintao Hu, Junwei Han, Xiaoping Hu**, Tianming Liu**, Coevolution of Gyral Folding and Structural Connection Patterns in Primate Brains, *Joint first authors, **Joint corresponding authors, Cerebral Cortex, 2012.

Dajiang Zhu*, Kaiming Li*, Lei Guo, Xi Jiang, Tuo Zhang, Degang Zhang, Hanbo Chen, Fan Deng, Carlos Faraco, Changfeng Jin, Chong-Yaw Wee, Yixuan Yuan, Peili Lv, Yan Yin, Xiaolei Hu, Lian Duan, Xintao Hu, Junwei Han, Lihong Wang, Dinggang Shen, L Stephen Miller, Lingjiang Li, Tianming Liu, DICCCOL: Dense Individualized and Common Connectivity-based Cortical Landmarks, *Joint first authors, Cerebral Cortex, 2012.

Kaiming Li*, Dajiang Zhu*, Lei Guo, Zhihao Li, Mary Ellen Lynch, Claire Coles, Xiaoping Hu**, Tianming Liu**, Connectomics Signatures of Prenatal Cocaine Exposure Affected Adolescent Brains, *Joint first authors, **Joint corresponding authors, Human Brain Mapping, 2012.

Xintao Hu, Kaiming Li, Junwei Han, Xian-Sheng Hua, Lei Guo, Tianming Liu, Bridging the Semantic Gap via Functional Brain Imaging, IEEE Transactions on Multimedia, 2012.

Jingxin Nie, Lei Guo, Kaiming Li, Yonghua Wang, Guojun Chen, Longchuan Li, Hanbo Chen, Fan Deng, Xi Jiang, Tuo Zhang, Ling Huang, Carlos Faraco, Degang Zhang, Cong Guo, Pew-Thian Yap, Xintao Hu, Gang Li, Jinglei Lv, Yixuan Yuan, Dajiang Zhu, Junwei Han, Dean Sabatinelli, Qun Zhao, L Stephen Miller, Bingqian Xu, Ping Shen, Simon Platt, Dinggang Shen, Xiaoping Hu, Tianming Liu, Axonal Fiber Terminations Concentrate on Gyri, Cerebral Cortex, 2011.

Dajiang Zhu, Kaiming Li, Carlos Faraco, Fan Deng, Degang Zhang, Xi Jiang, Hanbo Chen, Lei Guo, Stephen Miller, Tianming Liu, Optimization of Functional Brain ROIs via Maximization of Consistency of Structural Connectivity Profiles, NeuroImage, 2011.

Tuo Zhang, Lei Guo, Kaiming Li, Changfeng Jing, Yan Yin, Dajing Zhu, Guangbin Cui, Lingjiang Li, Tianming Liu, Predicting Functional Cortical ROIs via DTI-derived Fiber Shape Models, Cerebral Cortex, 2011.

Xintao Hu, Fan Deng, Kaiming Li, Tuo Zhang, Hanbo Chen, Xi Jiang, Jinglei Lv, Dajiang Zhu, Li Xie, Carlos, Faraco, Degang Zhang, Arsham Mesbah, Junwei Han, Xian-Sheng Hua, Stephen Miller, Lei Guo, Tianming Liu, Bridging Low-level Features and High-level Semantics via fMRI Brain Imaging for Video Classification, ACM Multimedia, 2010.

Kaiming Li, Lei Guo, Carlos  Faraco, Dajiang  Zhu, Fan  Deng, Tuo  Zhang, Xi  Jiang, Degang  Zhang, Hanbo  Chen, Xintao  Hu, L. Stephen  Miller, Tianming  Liu, Individualized ROI Optimization via Maximization of Group-wise Consistency of Structural and Functional Profiles, NIPS 2010.

Gang Li, Lei Guo, Jingxin Nie, Tianming Liu, An Automated Pipeline for Cortical Sulcal Fundi Extraction, Medical Image Analysis, Volume 14, Issue 3, Pages 343-359, 2010.

Jingxin Nie, Lei Guo, Gang Li, Carlos Faraco, Stephen Miller, Tianming Liu, A Computational Model of Cerebral Cortex Folding, Journal of Theoretical Biology, 264(2):467-78, 2010.

Kaiming Li, Lei Guo, Gang Li, Jingxin Nie, Carlos Faraco, Guangbin Cui, Qun Zhao, Stephen Miller, Tianming Liu, Gyral folding pattern analysis via surface profiling, NeuroImage, 2010.

Gang Li, Lei Guo, Jingxin Nie, Tianming Liu, Automatic Cortical Sulcal Parcellation Based on Surface Principal Direction Flow Field Tracking, Neuroimage, 2009.

Tianming Liu, Jingxin Nie, Ashley Tarokh, Lei Guo, Stephen TC Wong, Reconstruction of Central Cortical Surface from MRI Brain Images: Method and Application. NeuroImage, 40(3):991-1002, 2008.

Tianming Liu, Hai Li, Kelvin Wong, Ashley Tarokh, Lei Guo, Stephen Wong, Brain Tissue Segmentation Based on DTI Data, NeuroImage, 38(1):114-23, 2007.

Tianming Liu, Geoffrey Young, Ling Huang, Nan-Kuei Chen, Stephen Wong. 76-space Analysis of Grey Matter Diffusivity: Methods and Applications. Neuroimage. 2006;15(31):51-65.

Tianming Liu, Dinggang Shen, and Christos Davatzikos. Deformable Registration of Cortical Structures via Hybrid Volumetric and Surface Warping. NeuroImage. 2004;22(4):1790-801.

IEEE/ACM Technology Journals:

Sheng Wang, Xi Ouyang, Tianming Liu, Qian Wang, Dinggang Shen, Follow My Eye: Using Gaze to Supervise Computer-Aided Diagnosis, in press, IEEE Transactions on Medical Imaging, 2022.

Xiaoyan Cai, Sen Liu, Junwei Han, Libin Yang, Zhenguo Liu and Tianming Liu, ChestXRayBERT: A Pretrained Language Model for Chest Radiology Report Summarization, in press, IEEE Transactions on Multimedia, 2021.

Guangyu Guo, Zhuoyan Liu, Shijie Zhao, Junwei Han, Lei Guo, Tianming Liu, Eliminating Indefiniteness of Clinical Spectrum for Better Screening COVID-19, in press, IEEE Journal of Biomedical and Health Informatics, 2021.

Ning Qiang, Qinglin Dong, Fangfei Ge, Hongtao Liang, Bao Ge, Shu Zhang, Yifei Sun, Jie Gao and Tianming Liu, Deep Variational Autoencoder for Mapping Functional Brain Networks, IEEE Transactions on Cognitive and Developmental Systems, in press, 2020.

Yan Cui, Shijie Zhao, Yaowu Chen, Junwei Han, Lei Guo, Li Xie, Tianming Liu, Modeling Brain Diverse and Complex Hemodynamic Response Patterns via Deep Recurrent Autoencoder, in press, IEEE Transactions on Cognitive and Developmental Systems, 2019.

Yan Cui, Shijie Zhao, Han Wang, Li Xie, Yaowu Chen, Junwei Han, Lei Guo, Fan Zhou, Tianming Liu, Identifying Brain Networks at Multiple Time Scales via Deep Recurrent Neural Network, IEEE Journal of Biomedical and Health Informatics, 2018.

Yujie Li, Heng Huang, Hanbo Chen, Tianming Liu, Deep Neural Networks for Exploration of Transcriptome of Adult Mouse Brain, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2018.

Shu Zhang, Huan Liu, Heng Huang, Yu Zhao, Xi Jiang, Brook Bowers, Lei Guo, Xiaoping Hu, Mar Sanchez, Tianming Liu, Deep Learning Models Unveiled Functional Difference between Cortical Gyri and Sulci, IEEE Transactions on Biomedical Engineering, 2018.

Milad Makkie, Xiang Li, Shannon Quinn, Binbin Lin, Jieping Ye, Geoffrey Mon, Tianming Liu, A Distributed Computing Platform for fMRI Big Data Analytics, IEEE Transactions on Big Data, 2018.

Wei Zhang, Jinglei Lv, Xiang Li, Dajiang Zhu, Xi Jiang, Shu Zhang, Yu Zhao, Lei Guo, Jieping Ye, Dewen Hu, Tianming Liu, Experimental Comparisons of Sparse Dictionary Learning and Independent Component Analysis for Brain Network Inference from fMRI Data, IEEE Transactions on Biomedical Engineering, 2018.

Yu Zhao, Qinglin Dong, Shu Zhang, Wei Zhang, Hanbo Chen, Xi Jiang, Lei Guo, Xintao Hu, Junwei Han, Tianming Liu, Automatic Recognition of fMRI-derived Functional Networks using 3D Convolutional Neural Networks, IEEE Transactions on Biomedical Engineering, 2017.

Junhui Gong, Xiaoyan Liu, Tianming Liu, Jiansong Zhou, Gang Sun, Juanxiu Tian, Dual Temporal and Spatial Sparse Representation for Inferring Group-wise Brain Networks from Resting-state fMRI Dataset, IEEE Transactions on Biomedical Engineering. 2017.

Yimin Hou, Ting Xiao, Shu Zhang, Xi Jiang, Xiang Li, Xintao Hu, Junwei Han, Lei Guo, L Stephen Miller, Richard Neupert, and Tianming Liu, Predicting Movie Trailer Viewer’s “Like/Dislike” via Learned Shot Editing Patterns, IEEE Transactions on Affective Computing, 7(1):29-44, 2015.

Xi Jiang, Tuo Zhang, Dajiang Zhu, Kaiming Li, Hanbo Chen, Jinglei Lv, Xintao Hu, Junwei Han, Dinggang Shen, Lei Guo, Tianming Liu, Anatomy-guided Dense Individualized and Common Connectivity-based Cortical Landmarks (A-DICCCOL), IEEE Transactions on Biomedical Engineering, 62(4):1108-1119, 2014.

Anirban Mukhopadhyay, Zhen Qian, Suchendra M. Bhandarkar, Tianming Liu, Szilard Voros, and Sarah Rinehart, Morphological Analysis of the Left Ventricular Endocardial Surface Using a Bag-of-Features Descriptor, IEEE Journal of Biomedical and Health Informatics,  19(4):1483-1493, 2014.

Bin He, Todd Coleman, Guy M. Genin, Gary Glover, Xiaoping Hu, Nessa Johnson, Tianming Liu, Scott Makeig, Paul Sajda, Kaiming Ye, Grand Challenges in Mapping the Human Brain: NSF Workshop Report, IEEE Transactions on Biomedical Engineering,  60(11):2983-2992, 2013

Fan Deng, Dajiang Zhu, Lei Guo and Tianming Liu, FMRI Signal Analysis Using Empirical Mean Curve Decomposition, IEEE Transactions on Biomedical Engineering, 60(1):42-54, 2012.

Junwei Han, Sheng He, Tianming Liu, and Lei Guo, An object-oriented saliency detection framework based on sparse coding representations, IEEE Transactions on Circuits and Systems for Video Technology, 23(12):2009-2021, 2012.

Tianming Liu and A Docef. Eval-Ware: Medical Imaging Resources. IEEE Signal Processing Magazine. 2006, 23(4):136-137.

Tianming Liu. A quantitative zebrafish phenotyping tool for developmental biology and disease modeling. IEEE Signal and Processing Magazine. 2007, 24(1):126-129.

Tianming Liu, Hong-Jiang Zhang, and Feihu Qi. A Systematic Rate Controller for MPEG-4 FGS Video Streaming. ACM/Springer Multimedia Systems. 2004, 8(5):369-379.

Tianming Liu, Hong-Jiang Zhang, and Feihu Qi. A Novel Video Key Frame Extraction Algorithm based on Perceived Motion Energy Model. IEEE Transactions on Circuits and Systems for Video Technology. 2003;13(10):1006-1013.

Brain Imaging and Computational Neuroscience Journals:

Shu Zhang, Junxin Wang, Sigang Yu, Ruoyang Wang, Junwei Han, Tianming Liu, Jinglei Lv, and Shijie Zhao, An Explainable Deep Learning Framework for Characterizing and Interpreting Human Brain States, in press, Medical Image Analysis, 2022.

Songyao Zhang, Poorya Chavoshnejad, Xiao Li, Lei Guo, Xi Jiang, Junwei Han, Li Wang, Gang Li, Xianqiao Wang, Tianming Liu, Mir Jalil Razavi, Shu Zhang, Tuo Zhang, Gyral Peaks and Patterns in Developing Macaque Brains, in press, Human Brain Mapping, 2022.

Ning Qiang, Qinglin Dong, Hongtao Liang, Bao Ge, Shu Zhang, Yifei Sun, Wei Zhang, Jie Gao and Tianming Liu, Modeling and Augmenting of fMRI Data using Deep Recurrent Variational Auto-encoder, in press, Journal of Neural Engineering, 2021.

Qing Li, Qinglin Dong, Fangfei Ge, Ning Qiang, Xia Wu, and Tianming Liu, Simultaneous Spatial-temporal Decomposition of Connectome-scale Brain Networks by Deep Sparse Recurrent Auto-encoders, in press, Brain Imaging and Behavior, 2021.

Ning Qiang, Qinglin Dong, Wei Zhang, Bao Ge, Fangfei Ge, Hongtao Liang, Yifei Sun, Jie Gao, Tianming Liu, Modeling Task-based fMRI Data via Deep Belief Network with Neural Architecture Search, in press, Computerized Medical Imaging and Graphics, 2020.

Lin Zhao, Tuo Zhang, Lei Guo, Tianming Liu, Xi Jiang, Gyral-Sulcal Contrast in Intrinsic Functional Brain Networks across Task Performances, Brain Imaging and Behavior, in press, 2020.

Wei Zhang, Shijie Zhao, Xintao Hu, Qinglin Dong, Heng Huang, Shu Zhang, Yu Zhao, Haixing Dai, Fangfei Ge, Lei Guo, Tianming Liu, Hierarchical Organization of Functional Brain Networks Revealed by Hybrid Spatiotemporal Deep Learning, Brain Connectivity, in press, 2020.

Tuo Zhang, Xiao Li, Xi Jiang, Fangfei Ge, Shu Zhang, Lin Zhao, Huan Liu, Ying Huang, Xianqiao Wang, Jian Yang, Lei Guo, Xiaoping Hu, Tianming Liu, Cortical 3-hinges Could Serve as Hubs in Cortico-cortical Connective Network, Brain Imaging and Behavior, 2019.

Bao Ge, Huan Wang, Panpan Wang, Yin Tian, Xin Zhang, Tianming Liu, Discovering and Characterizing Dynamic Functional Brain Networks in Task FMRI, Brain Imaging and Behavior, 2019.

Bing Ji, Silun Wang, Zhou Liu, Brent D Weinberg, Xiaofeng Yang, Tianming Liu, Hui Mao, Revealing Hemodynamic Heterogeneity of Gliomas Based on Signal Profile Features of Dynamic Susceptibility Contrast Enhanced MRI, NeuroImage: Clinical, 2019.

Cutter A. Lindbergh, Jinglei Lv, Yu Zhao, Catherine M. Mewborn, Antonio N. Puente, Douglas P. Terry, Lisa M. Renzi-Hammond, Billy R. Hammond, Tianming Liu, L. Stephen Miller, The effects of lutein and zeaxanthin on resting state functional connectivity in older Caucasian adults: A randomized controlled trial, Brain Imaging and Behavior, 2019.  

Shu Zhang*, Xi Jiang*, Wei Zhang*, Tuo Zhang, Hanbo Chen, Yu Zhao, Jinglei Lv, Lei Guo, Brittany R Howell, Mar M. Sanchez**, Xiaoping Hu**, Tianming Liu**, *Co-first authors. **Corresponding authors, Joint Representation of Connectome-scale Structural and Functional Profiles for Identification of Consistent Cortical Landmarks in Macaque Brain, Brain Imaging and Behavior, 2018.

Tuo Zhang, Jun Kong, Ke Jing, Hanbo Chen, Xi Jiang, Longchuan Li, Lei Guo, Jianfeng Lu, Xiaoping Hu, Tianming Liu, Optimization of Macaque Brain DMRI Connectome by Neuron Tracing and Myelin Stain Data, Computerized Medical Imaging and Graphics, 2018.

Xintao Hu, Heng Huang, Bo Peng, Junwei Han, Nian Liu, Jinglei Lv, Lei Guo, Christine Guo, Tianming Liu, Latent Source Mining in FMRI via Restricted Boltzmann Machine, Human Brain Mapping, 2018.

Shu Zhang, Yu Zhao, Xi Jiang, Dinggang Shen#, Tianming Liu#, Joint Representation of Consistent Structural and Functional Profiles for Identification of Common Cortical Landmarks, #Co-corresponding authors, Brain Imaging and Behavior, 2017.

Qinghua Zhao, Will X. Y. Li, Xi Jiang, Jinglei Lv, Jianfeng Lu*, Tianming Liu*, Functional Brain Networks Reconstruction Using Group Sparsity-Regularized Learning, *Joint corresponding authors, Brain Imaging and Behavior, 2017.

Shijie Zhao, Junwei Han*, Xintao Hu, Xi Jiang, Jinglei Lv, Tuo Zhang, Shu Zhang, Lei Guo, Tianming Liu*, Extendable Supervised Dictionary Learning for Exploring Diverse and Concurrent Brain Activities in Task-based fMRI, Brain Imaging and Behavior, 2017.

Changfeng Jin, Hao Jia, Pradyumna Lanka, D Rangaprakash, Lingjiang Li, Tianming Liu, Xiaoping Hu, and Gopikrishna Deshpande, Dynamic Brain Connectivity Is a Better Predictorof PTSD than Static Connectivity, Human Brain Mapping, 2017.

Armin Iraji+, Hanbo Chen+, Natalie Wiseman, Tuo Zhang, Robert Welch, Brian O'Neil, Andrew Kulek, Syed Imran Ayaz, Xiao Wang, Conor Zuk, E Mark Haacke, Tianming Liu*, Zhifeng Kou*, Connectome-scale Assessment of Structural and Functional Connectivity in Mild Traumatic Brain Injury at the Acute Stage, +Authors made equal contributions. *Joint correspondence authors, Neuroimage: Clinical, 12:100-115, 2016.

Yudan Ren, Jun Fang, Jinglei Lv, Xintao Hu, Cong Christine Guo, Lei Guo, Jiansong Xu, Marc N. Potenza*, Tianming Liu*, Assessing the Effects of Cocaine Dependence and Pathological Gambling Using Group-wise Sparse Representation of Natural Stimulus FMRI Data, *Joint correspondence authors, Brain Imaging and Behavior, 1-13, 2016.

Yu Zhao, Hanbo Chen, Yujie Li, Jinglei Lv, Xi Jiang, Fangfei Ge, Tuo Zhang, Shu Zhang, Bao Ge, Cheng Lyu, Shijie Zhao, Junwei Han, Lei Guo, Tianming Liu, Connectome-scale Group-wise Consistent Resting-state Network Analysis in Autism Spectrum Disorder, Neuroimage: Clinical, pp. 23-33, 2016.

Bao Ge, Milad Makkie, Jin Wang, Junwei Han, Shijie Zhao, Xi Jiang, Xiang Li, Jinglei Lv, Shu Zhang, Lei Guo, Tianming Liu, Signal Sampling for Efficient Sparse Representation of Resting State FMRI Data, Brain Imaging and Behavior, 10(4):1206-1222, 2015.

Xintao Hu, Lei Guo, Junwei Han, Tianming Liu, Decoding Power-spectral Profiles by FMRI Brain Activities during Naturalistic Auditory Experience, Brain Imaging and Behavior, 1-11, 2016.

Tuo Zhang, Dajiang Zhu, Xi Jiang, Shu Zhang, Zhifeng Kou, Lei Guo, Tianming Liu, Group-wise Consistent Cortical Parcellation Based on Connectional Profiles, Medical Image Analysis, 32:32-45 2016.

Gang Li, Tianming Liu, Dong Ni, Weili Lin, John H. Gilmore, Dinggang Shen Spatiotemporal Patterns of Cortical Fiber Density in Developing Infants, and Their Relationship with Cortical Thickness, Human Brain Mapping, 36(12):5183-5195, 2015.

Jinglei Lv, Xi Jiang, Xiang Li, Dajiang Zhu, Shijie Zhao, Tuo Zhang, Xintao Hu, Junwei Han, Lei Guo, Zhihao Li, Claire Coles, Xiaoping Hu*, Tianming Liu*, Assessing Effects of Prenatal Alcohol Exposure Using Group-wise Sparse Representation of FMRI Data, *Joint correspondence authors. Psychiatry Research: Neuroimaging, 233(2):254-268, 2015.

Shu Zhang, Xiang Li, Jinglei Lv, Xi Jiang, Lei Guo, Tianming Liu, Characterizing and Differentiating Task-based and Resting State FMRI Signals via Two-stage Sparse Representations, Brain Imaging and Behavior, 10(1):21-32, 2014.

Jinli Ou, Li Xie, Changfeng Jin, Xiang Li, Dajiang Zhu, Rongxin Jiang, Yaowu Chen,  Jing Zhang, Lingjiang Li, and Tianming Liu, Characterizing and Differentiating Brain State Dynamics via Hidden Markov Models, Brain Topography, 28(5):666-679,2014.

Jinli Ou, Li Xie, Xiang Li, Dajiang Zhu, Douglas P. Terry, A. Nicholas Puente, Rongxin Jiang, Yaowu Chen, Lihong Wang, Dinggang Shen, Jing Zhang, L. Stephen Miller, Tianming Liu, Atomic Connectomics Signatures for Characterization and Differentiation of Mild Cognitive Impairment, Brain Imaging and Behavior, 9(4):663-677, 2014.

Tao Zeng, Hanbo Chen, Ahmed Fakhry, Xiaoping Hu, Tianming Liu*, Shuiwang Ji*, Allen Mouse Brain Atlases Reveal Different Neural Connection and Gene Expression Patterns in Cerebellum Gyri and Sulci, *Joint-correspondence authors. Brain Structure and Function, 220(5):2691-2703, 2014.

Jun Fang, Xintao Hu, Junwei Han, Xi Jiang, Dajiang Zhu, Lei Guo, Tianming Liu, Data-driven Analysis of Functional Brain Interactions during Free Listening to Music and Speech, Brain Imaging and Behavior, 9(2):162-177, 2014.

Xin Zhang, Xiang Li, Changfeng Jin, Hanbo Chen, Kaiming Li, Dajiang Zhu, Xi Jiang, Tuo Zhang, Jinglei Lv, Xintao Hu, Junwei Han, Qun Zhao, Lei Guo, Lingjiang Li, Tianming Liu, Identifying and Characterizing Resting State Networks in Temporally Dynamic Functional Connectomes, Brain Topography, 27(6):747-765, 2014.

Xi Jiang, Dajiang Zhu, Kaiming Li, Tuo Zhang, Lihong Wang, Dinggang Shen, Lei Guo, Tianming Liu, Predictive Models of Resting State Networks for Assessment of Altered Functional Connectivity in Mild Cognitive Impairment, Brain Imaging and Behavior, 8(4):542-557, 2013.

Dajiang Zhu, Tuo Zhang, Xi Jiang, Xintao Hu, Ning Yang, Jinglei Lv,  Junwei Han, Lei Guo, Tianming Liu, Fusing DTI and FMRI Data: A Survey of Methods and Applications, NeuroImage, 102:184-191, 2013

Mo Chen, Junwei Han, Xintao Hu, Xi Jiang, Lei Guo, Tianming Liu, Survey of Encoding and Decoding of Visual Stimulus via FMRI:  An Image Analysis Perspective, Brain Imaging and Behavior. 8(1):7-23, 2013.

Xin Zhang, Lei Guo, Xiang Li, Tuo Zhang, Dajiang Zhu, Kaiming Li, Hanbo Chen, Jinglei Lv, Changfeng Jin, Qun Zhao, Lingjiang Li, Tianming Liu, Characterization of Task-free and Task-performance Brain States via Functional Connectome Patterns, Medical Image Analysis, 17(8):1106-1122, 2013.

Dajiang Zhu, Kaiming Li, Douglas Terry, Lihong Wang, Dinggang Shen, L. Stephen Miller, Tianming Liu, Connectome-scale Assessments of Structural and Functional Connectivity in MCI, Human Brain Mapping, 35(7):2911-2923, 2013.

Xiaojin Li, Xintao Hu, Changfeng Jin, Junwei Han, Tianming Liu, Lei Guo, Wei Hao, and Lingjiang Li, A Comparative Study of Theoretical Graph Models for Characterizing Structural Networks of Human Brain, International Journal of Biomedical Imaging, 2013. 

Jiehuan Sun*, Xintao Hu*, Xiu Huang, Yang Liu, Kaiming Li, Xiang Li, Junwei Han, Lei Guo, Tianming Liu**, Jing Zhang**, Inferring Consistent Functional Interaction Patterns from Natural Stimulus FMRI Data, *Joint first authors, **Joint corresponding authors, NeuroImage, 61(4):987-999, 2012.

Kaiming Li; Lei Guo; Carlos Faraco; Dajiang Zhu; Hanbo Chen; Yixuan Yuan; Jinglei Lv; Fan Deng; Xi Jiang; Tuo Zhang; Xintao Hu; Degang Zhang; Lloyd Miller, Tianming Liu, Visual Analytics of Brain Networks, NeuroImage, 61(1):82-97, 2012.

Degang Zhang, Lei Guo, Xintao Hu, Kaiming Li, Qun Zhao, Tianming Liu, Increased cortico-subcortical functional connectivity in schizophrenia, Brain Imaging and Behavior, 6(1):27-35, 2012.

Tianming Liu, A few thoughts on brain ROIs, Brain Imaging and Behavior, 5(3):189-202, 2011.

Faraco CC, Unsworth N, Langley J, Terry D, Li K, Zhang D, Tianming Liu, Miller LS., Complex span tasks and hippocampal recruitment during working memory, NeuroImage, 55(2):773-87, 2011.

Gang Li, Lei Guo, Tianming Liu. Deformation invariant attribute vector for deformable registration of longitudinal brain MR images, Computerized Medical Imaging and Graphics, Volume 33, Issue 5, July 2009, Pages 384-398.

Jingxin Nie, Zhong Xue, Tianming Liu, Geoffrey S. Young, Kian Setayesh, Lei Guo, Stephen T.C. Wong, Automated brain tumor segmentation using spatial accuracy-weighted hidden Markov Random Field, Computerized Medical Imaging and Graphics, Volume 33, Issue 6, Pages 431-441, 2009.

Kaiming Li, Lei Guo, Jingxin Nie, Gang Li, Tianming Liu, Review of Methods for Functional Brain Connectivity Detection Using fMRI. Computerized Medical Imaging and Graphics, Volume 33, Issue 2, Pages 131-139. 2008.

Tianming Liu, Winnie CW Chu, Geoffrey Young, Kaiming Li, Benson HY Yeung, Lei Guo, Gene CW Man, Wynnie WM Lam,Stephen TC Wong, Jack CY Cheng, MR analysis of Regional Brain Volume in Adolescent Idiopathic Scoliosis – neurological manifestation of a systemic disease, Journal of Magnetic Resonance Imaging, 27:732–736, 2008.

Jingxin Nie, Tianming Liu, Gang Li, Geoffrey Young, Ashley Tarokh, Lei Guo, Stephen TC Wong, Least-Square Conformal Brain Mapping with Spring Energy, Computerized Medical Imaging and Graphics, 31(8):656-664, 2007.

Neuroscience, Brain Disease, and Neuroinformatics Journals:

Sigang Yu, Enze Shi, Ruoyang Wang, Shijie Zhao, Tianming Liu, Xi Jiang, Shu Zhang, A Hybrid Learning Framework for Fine-grained Interpretation of Brain Spatio-temporal Patterns during Naturalistic fMRI, Frontiers in Human Neuroscience, in press, 2022.

Poorya Chavoshnejad, Xiao Li, Songyao Zhang, Weiying Dai, Lana Vasung, Tianming Liu, Tuo Zhang, Xianqiao Wang, Mir Jalil Razavi, Role of Axonal Fibers in the Cortical Folding Patterns: A Tale of Variability and Regularity, in press, Brain Multiphysics, 2021.

Ning Liu, Poorya Chavoshnejad, Mir Jalil Razavi, Tianming Liu, Ramana M. Pidaparti, Xianqiao Wang, Geometrical Nonlinear Elasticity of Axon Under Tension: A Coarse-grained Computational Study, Biophysical Journal, in press, 2021.

Lu Zhang, Li Wang, Jean Gao, Shannon L. Risacher, Jingwen Yan, Gang Li, Tianming Liu, Dajiang Zhu, and the Alzheimer’s Disease Neuroimaging Initiative, Deep Fusion of Brain Structure-Function in Mild Cognitive Impairment, in press, Medical Image Analysis, 2021.

Shimin Yang, Zhongbo Zhao, Han Cui, Tuo Zhang, Lin Zhao, Zhibin He, Huan Liu, Lei Guo, Tianming Liu, Benjamin Becker, Keith Maurice Kendrick, Xi Jiang, Temporal Variability of Cortical Gyral-Sulcal Resting State Functional Activity Correlates with Fluid Intelligence, Frontiers in Neural Circuits, 2019.

Cutter A. Lindbergh, Yu Zhao, Jinglei Lv, Catherine M. Mewborn, Antonio N. Puente, Douglas P. Terry, Lisa M. Renzi-Hammond, Billy R. Hammond, Tianming Liu, L. Stephen Miller, Intelligence moderates the relation between age and inter-connectivity of resting state networks in older adults, Neurobiology of Aging, 2019.

Milad Makkie, Heng Huang, Yu Zhao, Athanasios V. Vasilakos, Tianming Liu, Fast and Scalable Distributed Deep Convolutional Autoencoder for fMRI Big Data Analytics, Neurocomputing, 2018.

Han Wang, Kun Xie, Li Xie, Xiang Li, Meng Li, Cheng Lyu, Hanbo Chen, Yaowu Chen, Xuesong Liu, Joe Tsien, Tianming Liu, Functional Brain Connectivity Revealed by Sparse Coding of Large-Scale Local Field Potential Dynamics, Brain Topography, 2018.

Xi Jiang, Lin Zhao, Huan Liu, Lei Guo, Keith M Kendrick, Tianming Liu, A Cortical Folding Pattern-Guided Model of Intrinsic Functional Brain Networks in Emotion Processing, Frontiers in Neuroscience, 2018.

Jun Liu, Cheng Lyu, Meng Li, Tianming Liu, Sen Song, Joe Tsien, Neural coding of food experiences in the amygdala, Neurobiology of Learning and Memory, 2018.

Bao Ge, Xiang Li, Xi Jiang, Yifei Sun, Tianming Liu, A Dictionary Learning Approach for Signal Sampling in Task-based fMRI for Reduction of Big Data, Frontiers in Neuroinformatics, 2018.

Shijie Zhao, Junwei Han; Xi Jiang; Heng Huang; Huan Liu; Jinglei Lv; Lei Guo, Tianming Liu, Decoding Auditory Saliency from Brain Activity Patterns during Free Listening to Naturalistic Audio Excerpts, Neuroinformatics, 2018.

Huan Liu; Xi Jiang; Tuo Zhang; Rudan Ren; Xintao Hu; Lei Guo; Junwei Han; Tianming Liu, Elucidating Functional Differences between Cortical Gyri and Sulci via Sparse Representation HCP Grayordinate fMRI Data, Brain Research, 2017.

Mir Jalil Razavi*, Tuo Zhang*, Hanbo Chen, Yujie Li, Simon Platt, Yu Zhao, Lei Guo, Xiaoping Hu, Xianqiao Wang** and Tianming Liu**, Radial Structure Scaffolds the Convolution Patterns of Developing Cerebral Cortex, *Co-first authors, **Corresponding authors, Frontiers in Computational Neuroscience. 2017.

Yujie Li, Hanbo Chen, Xi Jiang, Xiang Li, Jinglei Lv, Hanchuan Peng, Joe Z. Tsien, Tianming Liu, Discover Mouse Gene Co-expression Landscapes Using Dictionary Learning and Sparse Coding, Brain Structure and Function, 2017.

Wei Zhang*, Xi Jiang*, Shu Zhang*, Brittany R Howell*, Yu Zhao, Tuo Zhang, Lei Guo, Mar M. Sanchez**, Xiaoping Hu**, Tianming Liu**, Connectome-scale Functional Intrinsic Connectivity Networks in Macaques, *Co-first authors. **Corresponding authors, Neuroscience, 2017.

Yujie Li, Hanbo Chen, Xi Jiang, Xiang Li, Jinglei Lv, Meng Li, Hanchuan Peng, Joe Z. Tsien, Tianming Liu, Transcriptome architecture of adult mouse brain revealed by sparse coding of genome-wide in situ hybridization images, Neuroinformatics, 2017.

Hanbo Chen, Daniel M. Iascone, Nuno Macarico da Costa, Ed S. Lein, Tianming Liu, Hanchuan Peng, Fast Assembling of Neuron Fragments in Serial 3D Sections, Brain Informatics, 2017.

Kun Xie†, Grace E. Fox†, Jun Liu†, Cheng Lyu†, Jason Lee†, Hui Kuang†, Stephanie Jacobs, Meng Li, Tianming Liu, Sen Song and Joe Z. Tsien, Brain computation is organized via power-of-two-based permutation logic, †Equal contribution, Frontiers in Systems Neuroscience, 10, 2016.

Milad Makkie, Shijie Zhao, Xi Jiang, Jinglei Lv, Yu Zhao, Bao Ge, Xiang Li, Junwei Han, Tianming Liu, HAFNI-Enabled Largescale Platform for Neuroimaging Informatics (HELPNI), Brain Informatics, 2(4):225-238, 2015.

Armin Iraji, Hanbo Chen, Natalie Wiseman, E. Mark Haacke, Tianming Liu and Zhifeng Kou, Connectome-scale assessment of structure and function connectivity in mild traumatic brain injury at the acute stage, Neural Plasticity, 12:100-115, 2015.

Hanbo Chen, Hang Xiao, Tianming Liu, Hanchuan Peng, SmartTracing: Self-learning based Neuron Reconstruction, Brain Informatics, 2(3):135-144, 2015.

Armin Iraji, Randall R Benson, Robert D. Welch, Brian J. O’Neil, John L. Woodard, Syed Imran Ayaz, Andrew Kulek, Patrick Medado, Hamid Soltanian-Zadeh, Tianming Liu, E Mark Haacke, Zhifeng Kou, Resting State Functional Connectivity in Mild Traumatic Brain Injury at the Acute Stage, Journal of Neurotrauma, 32(14):1031-1045, 2014.

Schaeffer DJ, Krafft CE, Schwarz NF, Chi L, Weinberger AL, Pierce JE, Rodrigue AL, Allison JD, Yanasak NE, Liu Tianming, Davis CL, and McDowell JE, The Relationship between Uncinate Fasciculus White Matter Integrity and Verbal Memory Proficiency in Children, NeuroReport, 25(12):921-925, 2014.

Junwei Han, Shijie Zhao, Xintao Hu, Lei Guo, Tianming Liu, Encoding Brain Network Response to Free Viewing of Videos, Cognitive Neurodynamics. 8(5):389-397, 2014.

Jinglei Lv, Lei Guo, Dajiang Zhu, Tuo Zhang, Xintao Hu, Junwei Han, Tianming Liu, Group-wise FMRI Activation Detection on DICCCOL Landmarks, Neuroinformatics, 12(4):513-534, 2014.

Schaeffer DJ, Krafft CE, Schwarz NF, Chi L, Weinberger AL, Pierce JE, Rodrigue AL, Allison JD, Yanasak NE, Liu Tianming, Davis CL, and McDowell JE, An 8-month Exercise Intervention Alters Fronto-temporal White Matter Integrity in  Overweight Children, Psychophysiology, 51(8):728-733, 2014.

Junwei Han, Xiang Ji, Xintao Hu, Jungong Han and Tianming Liu, Clustering and Retrieval of Video Shots based on Natural Stimulus FMRI, Neurocomputing, 144:128-137, 2013.

Krafft CE, Schaeffer DJ, Schwarz NF, Chi L, Weinberger AL, Pierce JE, Rodrigue AL, Allison JD, Yanasak NE, Liu Tianming, Davis CL, and McDowell JE, Improved Fronto-Parietal White Matter Integrity in Overweight Children is Associated with Attendance in an After-School Exercise Program, Developmental Neuroscience, 36(1):1-9, 2013.

C.E. Krafft, J.E. Pierce, N.F. Schwarz, L. Chi, A.L. Weinberger, D.J. Schaeffer, A.L. Rodrigue, J. Camchong, J. D. Allison, N.E. Yanasak, Tianming. Liu, C.L. Davis, J.E. McDowell, An Eight Month Exercise Intervention Alters Resting State Synchrony in Overweight Children, Neuroscience, 256:445-455, 2013.

Joe Z. Tsien, Meng Li, Remus Osan, Guifen Chen, Longian Lin, Phillip Lei Wang, Sabine Frey, Julietta Frey, Dajiang Zhu, Tianming Liu, Fang Zhao, Hui Kuang, On initial Brain Activity Mapping of associative memory code in the hippocampus, Neurobiology of Learning and Memory, 105:200-210, 2013.

Peili Lv, Xintao Hu, Jinglei Lv, Junwei Han, Lei Guo, Tianming Liu, A Linear Model for Characterization of Synchronization Frequencies of Neural Networks, Cognitive Neurodynamics, 8(1):55-69, 2013.

Xintao Hu; Dajiang Zhu; Peili Lv; Kaiming Li; Junwei Han; Lihong Wang; Dinggang Shen; Lei Guo, Tianming Liu, Fine-Granularity Functional Interaction Signatures for Characterization of Brain Conditions, Neuroinformatics, 11(3):301-317,2013.

Yixuan Yuan; Xi Jiang; Dajiang Zhu; Hanbo Chen; Kaiming Li; Peili Lv; Xiang Yu; Xiaojin Li; Shu Zhang; Tuo Zhang; Xintao Hu; Junwei Han; Lei Guo, Tianming Liu, Meta-analysis of Functional Roles of DICCCOLs, Neuroinformatics. 11(1):47-63, 2012.

Bao Ge; Lei Guo; Tuo Zhang; Xintao Hu; Junwei Han, Tianming Liu, Resting State fMRI-guided Fiber Clustering: Methods and Applications, Neuroinformatics, 11(1):119-133, 2012.

Degang Zhang, Lei Guo, Dajiang Zhu, Kaiming Li, Longchuan Li, Hanbo Chen, Qun Zhao, Xiaoping Hu**, and Tianming Liu**, Diffusion Tensor Imaging Reveals Evolution of Primate Brain Architectures, **Joint corresponding authors, Brain Structure and Function, 218(6):1429-1450, 2012.

Xiang Li*, Chulwoo Lim*, Kaiming Li, Lei Guo, Tianming Liu, Detecting Brain State Changes via Fiber-Centered Functional Connectivity Analysis, *Joint first authors, Neuroinformatics, 11(2):193-210 2012.

Kaiming Li, Lei Guo, Dajiang Zhu, Xintao Hu, Junwei Han, Tianming Liu, Individual Functional ROI Optimization via Maximization of Group-wise Consistency of Structural and Functional Profiles, Neuroinformatics, pp. 1369-1377, 2012.

Walker LM, Katzir T, Liu T, Ly J, Corriveau K, Barzillai M, Chu F, O'Connor MG, Hackney DB, Chang BS. Gray matter volumes and cognitive ability in the epileptogenic brain malformation of periventricular nodular heterotopia. Epilepsy Behav, Volume 15, Issue 4, Pages 456-460, 2009.

Tianming Liu, Gang Li, Jingxin Nie, Ashley Tarokh, Xiaobo Zhou, Lei Guo, Jarema Malicki, Weiming Xia, Stephen TC Wong, An Automated Cell Detection Method for Cell Detection in Zebrafish, Neuroinformatics, 6(1):5-21, 2008.

Bernard S. Chang, M.D.* Tami Katzir, Ph.D.* Tianming Liu, Kathleen Corriveau, Mirit Barzillai, Kira A Apse, Adria Bodell, David Hackney, David Alsop, Stephen Wong, Christopher A. Walsh, A structural basis for reading fluency:  White matter fiber tracts and reading disability in a neuronal migration disorder *These authors contributed equally to this work, Neurology, 69: 2146-2154, 2007.

V Mok, Tianming Liu, W.W.M. Lam, A Wong, X Hu, L Guo; XY Chen, KS Wong, S Wong, Neuroimaging predictors for cognitive impairment in confluent white matter lesion: Volumetric analyses of 99 brain regions, Dementia and Geriatric Cognitive Disorders, 25(1):67-73, 2007.

Tianming Liu, J Lu, Y Wang, William A Campbell, Ling Huang, J Zhu, Weiming Xia, Stephen Wong. Computerized Image Analysis for Quantitative Neuronal Phenotyping in Zebrafish. Journal of Neuroscience Methods. 2006, 153(2):190-202.

William A. Campbell, Henrik Zetterberg, Stephanie Baulac, Tianming Liu, Stephen TC Wong, Tao Zhong, Weiming Xia. Zebrafish lacking Alzheimer presenilin enhancer 2 (Pen-2) demonstrate excessive p53-dependent apoptosis and neuronal loss. Journal of Neurochemistry. 2006, 96:1423-40.

Lei Guo, Tianming Liu, and Junwei Han. Adaptive Self-excitation Groups in Visual Curve Integration. Neurocomputing. 43(1):277-306. 2002.

Biomedical and Healthcare Journals:

Lian Zhang, Zhengliang Liu, Lu Zhang, Zihao Wu, Xiaowei Yu, Jason Holmes, Hongying Feng, Haixing Dai, Xiang Li, Quanzheng Li, Dajiang Zhu, Tianming Liu, Wei Liu, Generalizable and Promptable Artificial Intelligence Model to Augment Clinical Delineation in Radiation Oncology, in press, Medical Physics, 2024.

Lian Zhang, Jason M. Holmes, Zhengliang Liu, Sujay A. Vora, Terence T. Sio, Carlos E. Vargas, Nathan Y. Yu, Sameer R. Keole, Steven E. Schild, Martin Bues, Sheng Li, Tianming Liu, Jiajian Shen, William W. Wong, Wei Liu, Beam mask and sliding window-facilitated deep learning-based accurate and efficient dose prediction for pencil beam scanning proton therapy, in press, Medical Physics, 2023.

Zhengliang Liu, Mengshen He, Zuowei Jiang, Zihao Wu, Haixing Dai, Lian Zhang, Siyi Luo, Tianle Han, Xiang Li, Xi Jiang, Dajiang Zhu, Xiaoyan Cai, Bao Ge, Wei Liu, Jun Liu, Dinggang Shen, Tianming Liu. Survey on natural language processing in medical imaging analysis. Journal of Central South University. Medical Science, 2022, 47(8): 981- 993.

Xuyang Cao, Houjin Chen, Yanfeng Li, Yahui Peng, Yue Zhou, Lin Cheng, Tianming Liu, Dinggang Shen, Auto-DenseUNet: Searchable Neural Network Architecture for Mass Segmentation in 3D Automated Breast Ultrasound, in press, Medical Image Analysis, 2022.

Ning Qiang, Qinglin Dong, Hongtao Liang, Jin Li, Shenmin Zhang, Cheng Zhang, Bao Ge, Yifei Sun, Jie Gao, Tianming Liu, Huiji Yue, Shijie Zhao, Learning brain representation using recurrent Wasserstein generative adversarial net. In press, Computer Methods and Programs in Biomedicine. 2022.  

Yunze Yang, Samir Patel, Jidapa Bridhikitti, William Wong, Michele Halyard, Lisa McGee, Jean-Claude Rwigema, Steven Schild, Sujay Vora, Tianming Liu, Martin Bues, Mirek Fatyga, Robert Foote, and Wei Liu, Seed spots analysis to characterize dose and linear energy transfer effect in adverse event initialization of pencil beam scanning proton therapy, in press, Medical Physics, 2022.

Tianming Liu, Eliot Siege and Dinggang Shen, Review of Deep Learning and Medical Image Analysis for COVID-19 Diagnosis and Prediction, in press, Annual Review of Biomedical Engineering, 2022.

Xiaoyan Cai, Sen Liu, Junwei Han, Libin Yang, Xin Mei, Yan Lu, Dingang Shen and Tianming Liu, COVIDSum: A Linguistically Enriched SciBERT-based Summarization Model for COVID-19 Scientific Papers, in press, Journal of Biomedical Informatics, 2021.

Tianming Liu and Xiang Xiao, A Framework of AI Approaches to Improving eHealth Literacy and Combating Infodemic, Frontiers in Public Health, in press, 2021.

Tianming Liu, Dinggang Shen, Yue Gao, Hayit Greenspan, Wiro Niessen, Islem Rekik, Julia Schnabel and James Thrall, Intelligent Analysis of COVID-19 Imaging Data (editorial), in press, Medical Image Analysis, 2021.   

Tianming Liu, Grand Challenges in AI in Radiology, in press, Frontiers in Radiology, 2021.

Yunze Yang, Carlos E. Vargas, Ronik S. Bhangoo, William W. Wong, Steven E. Schild, Thomas B. Daniels, Sameer R. Keole, Jean-Claude M. Rwigema, Jennifer L. Glass, Jiajian Shen, Todd A. DeWees, Tianming Liu, Martin Bues, Mirek Fatyga, Wei Liu, Exploratory Investigation of Dose-Linear Energy Transfer (LET) Volume Histogram (DLVH) for Adverse Events Study in Intensity-Modulated Proton Therapy (IMPT), International Journal of Radiation Oncology, Biology, Physics, in press, 2021.

Shijie Zhao, Yan Cui, Linwei Huang, Li Xie, Yaowu Chen, Junwei Han, Lei Guo, Shu Zhang, Jinglei Lv, Tianming Liu, Identifying Diverse Functional Brain Networks Using DRNN Driven Supervised Dictionary Learning, IEEE Access, in press, 2020.

Wenyu Li, Qinglin Dong, Hao Jia, Shijie Zhao, Yongchen Wang, Li Xie, Qiang Pan, Feng Duan, Tianming Liu, Training a Camera to Perform Long-Distance Eye Tracking by another Eye-Tracker, IEEE Access, 2019.

Mir Jalil Razavi, Tuo Zhang, Tianming Liu*, and Xianqiao Wang*, Cortical Folding Pattern and its Consistency Induced by Biological Growth, Scientific Reports, 5, 2015. *Joint corresponding authors.

Mir Jalil Razavi, Tuo Zhang, Xiao Li, Tianming Liu*, and Xianqiao Wang*, Role of Mechanical Factors on the Cortical Folding Development, Physical Review E, 92(3):032701, 2015. *Joint corresponding authors. 

Junwei Han, Kaiming Li, Xintao Hu, Sheng He, Lei Guo, Tianming Liu. Video abstraction based on fMRI-driven visual attention model, Information Sciences, 281:781-796, 2014.

Tao Wu, Jianfeng Lu, Yanting Lu, Tianming Liu, Jingyu Yang, Embryo Zebrafish Segmentation Using an Improved Hybrid Method, Journal of Microscopy, 250(1):68-75, 2013.

Junwei Han, Ming Xu, Xin Li, Lei Guo, Tianming Liu, Interactive Object-based Image Retrieval and Annotation on iPad, Multimedia Tools and Applications. 72(3):2275-2297, 2013.

Jianfeng Lu, Tao Wu, Tianming Liu, Chen Chen,  Chunxia Zhao, Jingyu Yang, Automated Quantification of Zebrafish Somites, Journal of Microscopy, 248(2):156-162, 2012.

Yanting Lu, Jianfeng Lu, Tianming Liu, Jingyu Yang, Automated Gene Oscillation Phase Classification for Zebrafish Presomitic Mesoderm Cells, Cytometry, A, 9(9):727-35, 2011.

Tianming Liu, Jingxin Nie, Gang Li, Lei Guo, Stephen Wong, ZFIQ: a software package for zebrafish biology, Bioinformatics, 24(3):438-439, 2008.

Gang Li, Tianming Liu, Jingxin N, Guo L, Andrew M, Holley S, Zhu J, Chen J, Wong STC. Segmentation of touching cell nuclei using gradient flow tracking, Journal of Microscopy, 231(Pt 1):47-58, 2008.

Sibel Kantarci, Lihadh Al-Gazali, Robert S. Hill, Dian Donnai, Graeme C.M. Black, Eric Bieth,  Nicolas Chassaing, Didier Lacombe, Koen Devriendt, Ahmad Teebi, Maria Loscertales, Caroline Robson, Tianming Liu, David T. MacLaughlin, Kristin M. Noonan, Meaghan K. Russell, Christopher A. Walsh, Patricia K. Donahoe, Barbara R. Pober, Mutations in megalin, a multi-ligand receptor, cause Donnai-Barrow syndrome characterized by corpus callosum, ocular, neurosensory, craniofacial, and diaphragmatic defects, Nature Genetics, 39(8):957-959, 2007.

Gang Li, Tianming Liu, Jingxin Nie, Lei Guo, Jarema Malicki, Andrew Mara, Scott Holley, Weiming Xia, Stephen Wong. Detection of Blob Objects in Microscopic Zebrafish Images Based on Gradient Vector Diffusion. Cytometry A., 71(10):835-45, 2007.

Gang Li, Tianming Liu, Ashley Tarokh, Jingxin Nie, Lei Guo, Andrew Mara, Scott Holley, Stephen TC Wong, 3D Cell Segmentation Based on Gradient Flow Tracking, BMC Cell Biology, 8(1):40, 2007.

Full-length Conference Papers:

MICCAI/IPMI/ISBI:

Tianming Liu, Dinggang Shen, and Christos Davatzikos, Deformable Registration of Cortical Structures via Hybrid Volumetric and Surface Warping, Medical Image Computing and Computer-Assisted Intervention (MICCAI), Montreal, Canada, 2003, pp. 780-787.

Tianming Liu, Dinggang Shen, and Christos Davatzikos, Predictive Modeling of Anatomic Structures Using Canonical Correlation Analysis, International Symposium on Biomedical Imaging (ISBI), Washington DC, 2004, pp. 1279-1282.

Tianming Liu, Dinggang Shen, and Christos Davatzikos, Deformable Registration of Tumor-diseased Brain Images, Medical Image Computing and Computer-Assisted Intervention (MICCAI), St. Malo, France, 2004, pp. 720-728.

Tianming Liu, Geoffrey Young, Ling Huang, Nan-Kuei Chen, Stephen TC Wong, 76-space Analysis of Grey Matter Diffusivity: Methods and Applications, Medical Image Computing and Computer-Assisted Intervention (MICCAI), Palm Springs, 2005, pp. 148-155.

Jingxin Nie, Tianming Liu, Geoffrey Young, Lei Guo, and Stephen TC Wong, Least square conformal mapping with spring energy, International Symposium on Biomedical Imaging (ISBI), Washington DC, 2006, pp. 1308 - 1311.

Hai Li, Tianming Liu, Geoffrey Young, Lei Guo, and Stephen TC Wong, Brain tissue segmentation based on DWI/DTI data, International Symposium on Biomedical Imaging (ISBI), Washington DC, 2006, pp. 442 - 445.

Gang Li, Tianming Liu, Geoffrey Young, Lei Guo, and Stephen TC Wong, Deformation invariant attribute vector for 3D medical image registration, International Symposium on Biomedical Imaging (ISBI), Washington DC, 2006, pp. 1308 - 1311.

Li H, Tianming Liu, Guo L, Stephen TC Wong, Deformable registration of DTI and SPGR images, International Symposium of Biomedical Imaging (ISBI), Washington DC, April 2007.

Li G, Tianming Liu, Nie J, Guo L, Stephen TC Wong, Segmentation of touching cells using gradient flow tracking, International Symposium of Biomedical Imaging (ISBI), Washington DC, April 2007.

Nie J, Tianming Liu, Guo L, Stephen TC Wong, Reconstruction of central cortical surface from brain MRI images: Method and Application, International Symposium of Biomedical Imaging (ISBI), Washington DC, April 2007.

Gang Li, Tianming Liu, Jingxin Nie, Lei Guo, Stephen Wong, A Novel Method for Cortical Sulcal Fundi Extraction, Medical Image Computing and Computer-Assisted Intervention (MICCAI), September. 2008.

Gang Li, Lei Guo, Jingxin Nie and Tianming Liu, Automatic Cortical Sulcal Parcellation Based on Surface Principal Direction Flow Field Tracking, Information Processing in Medical Imaging (IPMI), 2009.

Jingxin Nie, Lei Guo, Tianming Liu, A computational model of cerebral cortex folding, Medical Image Computing and Computer Assisted Intervention (MICCAI) 2009.

Tuo Zhang, Lei Guo, Gang Li, Jingxin Nie, Tianming Liu, Parametric representation of cortical surface folding via polynomials, Medical Image Computing and Computer Assisted Intervention (MICCAI) 2009.

Kaiming Li, Lei Guo, Gang Li, Jingxin Nie, Carlos Faraco, Qun Zhao, L. Stephen Miller, Tianming Liu, Gyral folding pattern analysis via surface profiling, Medical Image Computing and Computer Assisted Intervention (MICCAI) 2009.

Kaiming Li, Lei Guo, Gang Li, Jingxin Nie, Carlos Faraco, Qun Zhao, Stephen Miller, Tianming Liu, Cortical surface based identification of brain networks using high spatial resolution resting state fMRI data, International Symposium of Biomedical Imaging (ISBI) 2010.

Degang Zhang, Lei Guo, Gang Li, Jingxin Nie, Xi Jiang, Fan Deng, Kaiming Li, Dajiang Zhu, Qun Zhao, Tianming Liu, Automatic cortical surface parcellation based on fiber density information, International Symposium of Biomedical Imaging (ISBI) 2010.

Yixuan Yuan, Lei Guo, Gang Li, Tuo Zhang, Xintao Hu, Tianming Liu, Joint anlaysis of cortical folding pattern, thickness and fiber density using structural and DTI data, International Symposium of Biomedical Imaging (ISBI), 2010.

Tuo Zhang, Lei Guo, Xintao Hu, Gang Li, Jingxin Nie, Xi Jiang, Degang Zhang, Tianming Liu, Joint analysis of fiber shape and cortical folding patterns, International Symposium of Biomedical Imaging (ISBI), 2010.

Jinglei Lv, Lei Guo, Xintao Hu, Tuo Zhang, Kaiming Li, Tianming Liu, Fiber-centered Analysis of Brain Connectivities Using DTI and Resting State FMRI Data, MICCAI 2010.

Hanbo Chen, Lei Guo, Jingxin Nie, Tuo Zhang,  Xintao Hu, Tianming Liu,  A dynamic skull model for simulation of cerebral cortex folding, MICCAI 2010.

Dajiang Zhu, Kaiming Li, Carlos Faraco, Fan Deng, Degang Zhang, Xi Jiang, Hanbo Chen, Lei Guo, Stephen Miller, Tianming Liu, Fine Granularity Parcellation of Gyrus via Fiber Shape and Connectivity Based Features, ISBI 2011.

Dajiang Zhu, Kaiming Li, Carlos Faraco, Fan Deng, Degang Zhang, Xi Jiang, Hanbo Chen, Lei Guo, Stephen Miller, Tianming Liu, Optimization of Functional Brain ROIs via Maximization of Consistency of Structural Connectivity Profiles, ISBI 2011.

Chulwoo Lim, Xiang Li, Kaiming Li, Lei Guo, Tianming Liu, Brain State Change Detection via Fiber-centered Functional Connectivity Analysis, ISBI 2011.

Xintao Hu, Lei Guo, Degang Zhang, Kaiming Li, Tuo Zhang, Jinglei Lv, Junwei Han, Tianming Liu, Assessing the Dynamics on Functional Brain Networks using Spectral Graph Theory, ISBI 2011.

Yixuan Yuan, Lei Guo, Peili Lv, Xintao Hu, Degang Zhang, Junwei Han, Li Xie, Tianming Liu, Assessing Graph Models for Description of Brain Networks, ISBI 2011.

Bao Ge, Lei Guo, Tuo Zhang, Xintao Hu, Junwei Han, Tianming Liu, Resting state fMRI-guided fiber clustering, MICCAI 2011.

Xiang Li, Chuwoo Lim, Kaiming Li, Lei Guo, Tianming Liu, Fiber-centered Granger Causality Analysis, MICCAI 2011.

Hanbo Chen, Lei Guo, Kaiming Li, Xintao Hu, Tianming Liu, Assessment of Regularity and Variability of Cortical Folding Patterns of Working Memory ROIs, MICCAI 2011.

Tuo Zhang, Lei Guo, Xintao Hu, Kaiming Li, Tianming Liu, Predicting Functional Cortical ROIs based on Fiber Shape Models, MICCAI 2011.

Dajiang Zhu, Kaiming Li, Carlos Faraco, Fan Deng, Degang Zhang, Xi Jiang, Hanbo Chen, Lei Guo, Stephen Miller, Tianming Liu, Discovering Dense and Consistent Landmarks in the Brain, IPMI 2011.

Jinglei Lv, Lei Guo, Xintao Hu, Kaiming Li, Tianming Liu, Activated Fibers: Fiber-centered Activation Detection in Task-based FMRI, IPMI 2011.

Hanbo Chen, Kaiming Li, Dajiang Zhu, Tuo Zhang, Changfeng Jin, Lei Guo, Lingjiang Li, Tianming Liu. Inferring Group-wise Consistent Multimodal Brain Networks via Multi-view Spectral Clustering, 32(9):1576-1586, MICCAI 2012.

Hanbo Chen, Xiao Cai, Dajiang Zhu, Feiping Nie, Tianming Liu, Heng Huang, Group-wise Consistent Parcellation of Gyri via Adaptive Multi-view Spectral Clustering of Fiber Shapes, pp. 271-279, MICCAI 2012.

Fan Deng, Dajiang Zhu, Lei Guo, Tianming Liu, Optimization of fMRI-derived ROIs based on Coherent Functional Interaction Patterns. pp. 214-222, MICCAI 2012.

Bao Ge, Lei Guo, Dajiang Zhu, Kaiming Li, Xintao Hu, Junwei Han, Tianming Liu, Group-wise Consistent Fiber Clustering Based on Multimodal Connectional and Functional Profiles, pp. 485-492, MICCAI 2012.

Xin Zhang, Lei Guo, Xiang Li, Dajiang Zhu, Kaiming Li, Zhenqiang Sun, Changfeng Jin, Xintao Hu, Junwei Han, Qun Zhao, Lingjiang Li, Tianming Liu, Characterization of Task-free/Task-performance Brain States, pp. 237-245, MICCAI 2012.

Anirban Mukhopadhyay, Zhen Qian, Suchi Bhandarkar, Tianming Liu, Sarah Rienhart, Morphological analysis of the left ventricular endocardial surface and its clinical implications, pp. 502-510, MICCAI 2012.

Dajiang Zhu, Xiang Li, Xi Jiang, Hanbo Chen, Dinggang Shen, Tianming Liu, Exploring High-Order Functional Interactions via Structurally-Weighted LASSO Models, pp. 13-24, IPMI 2013.

Bao Ge, Lei Guo, Tuo Zhang, Dajiang Zhu, Xintao Hu, Junwei Han, Tianming Liu,  Construction of Multi-scale Common Brain Network Via DICCCOL, pp. 692-704, IPMI 2013.

Dajiang Zhu, Dinggang Shen, Tianming Liu, Inferring Functional Network-based Signatures via Structurally-weighted LASSO Model, pp. 970-973, ISBI 2013.

Xiang Yu*, Hanbo Chen*, Tuo Zhang, Xintao Hu, Lei Guo, Tianming Liu, Joint Analysis of Gyral Folding and Fiber Shape Patterns, pp. 85-88, ISBI 2013. *Joint first authors.

Hanbo Chen, Kaiming Li, Dajiang Zhu, Tianming Liu, Identifying Consistent Brain Networks via Maximizing Predictability of Functional Connectome from Structural Connectome, pp. 978-981, ISBI 2013.

Xiang Li, Dajiang Zhu, Xi Jiang, Changfeng Jin, Lei Guo, Lingjiang Li, Tianming Liu, Discovering Common Functional Connectomics Signatures, pp. 620-623, ISBI 2013.

Tuo Zhang, Dajiang Zhu, Xi Jiang, Lei Guo, Tianming Liu, Predicting Functional Cortical ROIs via Joint Modeling of Anatomical and Connectional Profiles, pp. 516-519, ISBI 2013.

Shu Zhang, Jinglei Lv, Xiang LI, Xi Jiang, Lei Guo, Tianming Liu, Activated Cliques: Network-based Activation Detection in Task-based FMRI, pp. 274-277, ISBI 2013.

Xintao Hu, Tuo Zhang, Junwei Han, Lei Guo, Tianming Liu, Functional Brain Interactions During Free Viewing of Video Stream, pp. 1082-1085, ISBI 2013.

Yingjie Zhang, Junwei Han, Xintao Hu, Lei Guo, Tianming Liu, Data-driven Evaluation of Functional Connectivity Metrics, pp. 532-535, ISBI 2013.

Jia Chen, Jianfeng Lu, Hanbo Chen, Dajiang Zhu, Tianming Liu, Assessing Regularity and Variability of Cortical Folding Patterns of DICCCOLs, pp. 974-977, ISBI 2013.

Bao Ge, Lei Guo, Tuo Zhang, Dajiang Zhu, Xintao Hu, Junwei Han, Tianming Liu, Construction of Multi-scale Brain Networks via DICCCOL Landmarks, pp. 680-683, ISBI 2013.

Peng Wang*, Dajiang Zhu*, Hanbo Chen, Xi Jiang, Li Sun, Qingjiu Cao, An Li, Tianming Liu, Yufeng Wang, Identifying Functional Connectomics Abnormality in Attention Deficit Hyperactivity Disorder, *Joint first authors. pp. 544-547, ISBI 2013.

Peili Lv, Lei Guo, Xintao Hu, Xiang Li, Changfeng Jin, Junwei Han, Lingjiang Li, Tianming Liu, Modeling Dynamic Functional Information Flows on Large-scale Brain Networks, pp. 698-705, MICCAI 2013.

Shu Zhang, Xiang Li, Jinglei Lv, Xi Jiang, Dajiang Zhu, Hanbo Chen, Tuo Zhang, Lei Guo, Tianming Liu, Sparse Representation of Higher-order Functional Interaction Patterns in Task-based FMRI Data, pp. 626-634, MICCAI 2013.

Jinglei Lv, Dajiang Zhu, Xintao Hu, Xin Zhang, Lei Guo, Tianming Liu, Group-wise FMRI Activation Detection on Corresponding Cortical Landmarks, pp. 665-673, MICCAI 2013.

Jinglei Lv, Xiang Li, Dajiang Zhu, Xi Jiang, Xin Zhang, Lei Guo, Tianming Liu, Sparse Representation of Group-wise FMRI Signals, pp. 608-616, MICCAI 2013.

Hanbo Chen, Tuo Zhang, Tianming Liu, Identifying Group-wise Consistent White Matter Landmarks via Novel Fiber Shape Descriptor, pp. 66-73, MICCAI 2013.

Xi Jiang, Tuo Zhang, Dajiang Zhu, Kaiming Li, Jinglei Lv, Lei Guo, Tianming Liu, Anatomy-guided Discovery of Large-scale Consistent Connectivity-based Cortical Landmarks, pp. 617-625, MICCAI 2013

Xi Jiang, Dajiang Zhu, Kaiming Li, Tuo Zhang, Dinggang Shen, Lei Guo, Tianming Liu, Predictive Models of Resting State Networks for Assessment of Altered Functional Connectivity in MCI, pp. 674-681, MICCAI 2013.

Jinglei Lv, Tuo Zhang, Xintao Hu, Dajiang Zhu, Kaiming Li, Lei Guo, Tianming Liu, Group-wise connection activation detection based on DICCCOL, pp. 681-684, ISBI 2014.

Shu Zhang, Xintao Hu, Jinglei Lv, Tuo Zhang, Xiang LI, Xi Jiang, Lei Guo, Tianming Liu, Learning fMRI-guided predictor of video shot changes, pp. 1210-1213, ISBI 2014.

Dajiang Zhu, Dinggang Shen, Tianming Liu, Connectomics signature for characterization of mild cognitive impairment and schizophrenia, pp. 325-328, ISBI 2014.

Dajiang Zhu, Tianming Liu, Sparse representation of working memory processes based on fMRI data, pp. 584-587, ISBI 2014.

Tuo Zhang, Dajiang Zhu, Xi Jiang, Lei Guo, Tianming Liu, Group-wise consistent cortical parcellation based on DTI-derived connectional profiles, pp. 826-829, ISBI 2014.

Xi Jiang, Jinglei Lv, Dajiang Zhu, Tuo Zhang, Xiang LI, Xintao Hu, Lei Guo, Tianming Liu, Discovery network-level functional interactions from working memory fMRI data, pp. 13-16, ISBI 2014.

Xi Jiang, Jinglei Lv, Dajiang Zhu, Tuo Zhang, Xintao Hu, Lei Guo, Tianming Liu, Inferring group-wise functional brain activities via point processes, pp. 669-672, ISBI 2014.

Zhichao Lian, Xiang LI, Jianchuan Xing, Jinglei Lv, Xi Jiang, Dajiang Zhu, Jiansong Xu, Marc N. Potenza, Tianming Liu, Jing Zhang, Exploring functional brain dynamics via a Bayesian connectivity change point model, pp. 600-603, ISBI 2014.

Zhichao Lian, Jinglei Lv, Jianchuan Xing, Xiang LI, Xi Jiang, Dajiang Zhu, Jiansong Xu, Marc N. Potenza, Tianming Liu, Jing Zhang. Generalized fMRI activation detection via Bayesian magnitude change point model, pp. 21-24, ISBI 2014.

Hanbo Chen, Xiang Yu, Xi Jiang, Kaiming li, Longchuan Li, Xintao Hu, Junwei Han, Lei Guo, Xiaoping Hu, Tianming Liu, Evolutionarily-preserved consistent gyral folding patterns across primate brains, pp. 1218-1221, ISBI 2014.

Hanbo Chen, kaiming li, Dajiang Zhu, Lei Guo, Tianming Liu, Group-wise optimization and individualization prediction of structural connectomes, pp. 742-745, ISBI 2014.

Zhichao Lian, Xiang Li, thomas young, Yun Hao, Jianchuan Xing, Jinglei Lv, Xi Jiang, Dajiang Zhu, Tianming Liu, Jing Zhang, Dynamic network partition via Bayesian connectivity bi-partition change point model, pp. 545-548, ISBI 2014.

Zhichao Lian, Xiang Li, Hongmiao Zhang, Hui Kuang, Kun Xie, Jianchuan Xing, Dajiang Zhu, Joe Z. Tsien, Tianming Liu, Jing Zhang, Detecting cell assembly interaction patterns via Bayesian based change-point detection and graph inference model, pp. 17-20, ISBI 2014.

Cheng Lv, Xintao Hu, Junwei Han, Gong Cheng, Lei Guo, Tianming Liu, Exploring consistent functional brain networks during free viewing of videos via sparse representation, pp. 349-352, ISBI 2014.

Dajiang Zhu, Jinglei Lv, Tianming Liu, Group-wise Optimization of Common Brain Landmarks with Joint Structural and Functional Regulations, pp. 716-723, MICCAI 2014.

Hanbo Chen, Yu Zhao, Tuo Zhang, Hongmiao Zhang, Hui Kuang, Meng Li,  Joe Z. Tsien, Tianming Liu, Construct and Assess Multimodal Mouse Brain Connectomes via Joint Modeling of Multi-scale DTI and Neuron Tracer Data, pp. 273-280,  MICCAI 2014.

Bao Ge, Jin Wang, Jinglei Lv, Shu Zhang, Shijie Zhao, Wei Zhang, Qinghua Zhao, Xiang Li,  Xi Jiang, Junwei Han, Lei Guo, Tianming Liu, Signal sampling for efficient sparse representation of resting state fMRI data, pp. 1360-1363, ISBI 2015.

Fangfei Ge, Jinglei Lv, Xintao Hu, Lei Guo, Junwei Han, Tianming Liu, Deriving ADHD biomarkers with sparse coding based network analysis, pp. 22-25, ISBI 2015.

Shu Zhang, Xiang Li, Jinglei Lv, Xi Jiang, Lei Guo, Tianming Liu, Characterizing and Differentiating Task-based and Resting State FMRI Signals via Two-stage Sparse Representations, 10(1):21-32, ISBI 2015. 

Ke Jing, Tuo Zhang, Jianfeng Lu, Hanbo Chen, Lei Guo, Longchuan Li, Xiaoping Hu, Tianming Liu, Multiscale and multimodal fusion of tract-tracing and DTI-derived fibers in macaque brains, pp. 938-942, ISBI 2015.

Tuo Zhang, Hanbo Chen, Xi Jiang, Lei Guo, Tianming Liu, Group-wise consistent sulcal fundi segmentation on dMRI-derived ODF features, pp. 638-641, ISBI 2015.

Xiang Li, Zhi Zhou, Philipp Keller, Hongkui Zeng, Tianming Liu, Hanchuan Peng, Interactive exemplar-based segmentation toolkit for biomedical image analysis, pp. 168-171, ISBI 2015.

Heng Huang, Xintao Hu, Junwei Han, Jinglei Lv, Nian Liu, Lei Guo, Tianming Liu, Latent Source mining in fmri data via deep neural network, pp. 638-641, ISBI 2016.

Xiao Li, Tuo Zhang, Xintao Hu, Lei Guo, Tianming Liu, A data-driven method to study brain structural connectivities via joint analysis of microarray data and dMRI data, pp. 829-832, ISBI 2016.

Xiang Li, Qinglin Dong, Xi Jiang, Jinglei Lv, Tianming Liu, Multiple-demand system identification and characterization via sparse representations of fMRI data, pp. 70-73,ISBI 2016.

Xiang Li, Binbin  Lin, Jieping Ye, Tianming Liu, Modeling functional network dynamics via multi-scale dictionary learning and network continuums, pp. 66-69, ISBI 2016.

Cheng Lyu, Xiang Li, Jinglei Lv, Xintao Hu, Junwei Han, Lei Guo, Tianming Liu, Identifying group-wise consistent sub-networks via spatial sparse representation of natural stimulus fMRI data, pp. 62-65, ISBI 2016.

Yudan Ren, Xintao Hu, Jinglei Lv, Lei Guo, Junwei Han, Tianming Liu, Identifying autism biomarkers in default mode network using sparse representation of resting-state fMRI data, pp. 1278-1281, ISBI 2016.

Jinglei Lv,  Armin Iraji, Hanbo Chen, Fangfei Ge, Lei Guo, Zhifeng Kou, Tianming Liu, Group-wise sparse representation of brain states reveal network abnormalities in mild traumatic brain injury, pp. 58-61, ISBI 2016.

Jinglei Lv, Armin Iraji, Fangfei Ge, Shijie Zhao, Xintao Hu, Tuo Zhang, Junwei Han, Lei Guo, Zhifeng Kou, Tianming Liu. Temporal Concatenated Sparse Coding of Resting State fMRI Data Reveal Network Interaction Changes in mTBI, pp. 46-54, MICCAI 2016.

Shijie Zhao, Junwei Han, Jinglei Lv, Xi Jiang, Xintao Hu, Shu Zhang, Mary Ellen Lynch, Claire Coles, Lei Guo, Xiaoping Hu, Tianming Liu, A Multi-Stage Sparse Coding Framework to Explore the Effects of Prenatal Alcohol Exposure, pp. 28-36, MICCAI 2016.

Qinghua Zhao, Jianfeng Lu, Jinglei Lv, Xi Jiang, Shijie Zhao, Tianming Liu, Exploring Brain Networks via Structured Sparse Representation of FMRI Data, pp. 55-62, MICCAI 2016.  

Xi Jiang, Xiang Li, Jinglei Lv, Shijie Zhao, Shu Zhang, Wei Zhang, Tuo Zhang, Tianming Liu, Modeling Functional Dynamics of Cortical Gyri and Sulci, pp. 19-27, MICCAI, 2016.

Yujie Li*, Hanbo Chen*, Xi Jiang, Xiang Li, Jinglei Lv, Hanchuan Peng**, Joe Z. Tsien**, Tianming Liu**, Discover Mouse Gene Coexpression Landscape Using Dictionary Learning and Sparse Coding, pp. 63-71, MICCAI, 2016. *Co-first Authors, **Joint Corresponding Authors.

Xiao Li, Lei Du, Tuo Zhang, Xintao Hu, Xi Jiang, Lei Guo, Tianming Liu, Species Preserved and Exclusive Structural Connections Revealed by Sparse CCA, pp. 123-131, MICCAI, 2016.

Dehua Ren, Yu Zhao, Hanbo Chen, Qinglin Dong, Jinglei Lv, Tianming Liu, 3D functional brain network classification using convolutional neural networks, ISBI 2017.

Hanbo Chen, Yujie Li, Yu Zhao, Jinglei Lv, Tianming Liu, Inter-subject fMRI registration based on functional networks, ISBI 2017.

Shu Zhang, Xiang LI, Lei Guo, Tianming Liu, Exploring human brain activation via nested sparse coding and functional operators, ISBI 2017.

Lin Yuan, Tianming Liu, Dewen Hu, Group-wise sparse representation of resting-state fMRI data for better understanding of schizophrenia, ISBI 2017.

Yu Zhao, Xiang LI, Milad Makkie, Shannon Quinn, Binbin Lin, Jieping Ye, Tianming Liu, Template-guided Functional Network Identification via Supervised Dictionary Learning, ISBI 2017.

Yu Zhao, Shu Zhang, Hanbo Chen, Wei Zhang, Jinglei Lv, Xi Jiang, Dinggang Shen*, Tianming Liu*, A novel framework for groupwise registration of fMRI images based on common functional networks, *Joint correspondence authors, ISBI 2017. 

Huan Liu, Mianzhi Zhang, Xintao Hu, Yudan Ren, Junwei Han, Lei Guo, Tianming Liu, FMRI data classification based on hybrid temporal and spatial sparse representation, accepted, ISBI 2017.

Liting Wang, Xintao Hu, Meng Wang, Junwei Han, Shijie Zhao, Lei Guo, Tianming Liu, Decoding dynamic auditory attention during naturalistic experience, ISBI 2017.

Xiao Li, Tuo Zhang, Xintao Hu, Lei Du, Lei Guo, Tianming Liu, Predicting cortical 3-hinge locations via structural connective features, ISBI 2017.

Heng Huang, Xintao Hu, Qinglin Dong, Junwei Han, Lei Guo, Tianming Liu, Modeling fMRI Data via Deep Convolutional Auto-Encoder, IPMI 2017.

Shu Zhang, Xi Jiang, Tianming Liu, Joint Representation of Connectome-scale Structural and Functional Profiles for Identification of Consistent Cortical landmarks in Human Brains, MICCAI 2017.

Tuo Zhang, Xiao Li, Lin Zhao, Xintao Hu, Tianming Liu, Lei Guo, Multi-way Regression Method Reveal Backbone of Macaque Brain Connectivity in Longitudinal Datasets, MICCAI 2017. 

Fangfei Ge, Hanbo Chen, Tuo Zhang, Xianqiao Wang, Lin Yuan, Xintao Hu, Lei Guo, Tianming Liu, A Novel Framework for Analyzing Cortical Folding Patterns based on Sulcal Baselines and Gyral Crestlines. ISBI 2018.

Huan Liu*, Shijie Zhao, Xi Jiang, Xintao Hu, Lei Guo, Tianming Liu, Characterizing Task-evoked and Intrinsic Functional Networks from Task-based fMRI Data via Two-stage Sparse Dictionary Learning, ISBI 2018.

Fangfei Ge, Jinglei Lv, Xintao Hu, Lei Guo, Junwei Han, Tianming Liu, Exploring Intrinsic Networks and Their Interactions Using Group Wise Temporal Sparse Coding, ISBI 2018.

Shu Zhang*, Tuo Zhang, Xiao Li, Lei Guo, Tianming Liu, Joint Representation of Cortical Folding, Structural Connectivity and Functional Networks, ISBI 2018.

Qinghua Zhao*, Xi Jiang, Shijie Zhao, Xintao Hu, Junwei Han, Jianfeng Lu, Tianming Liu, Identifying Consistent Functional Brain Landmarks via Group-wise Sparse Representation of Concatenated Multitask fMRI Data, ISBI 2018.

Lei Li, Xintao Hu*, Heng Huang, Chunlin He, Liting Wang, Junwei Han, Lei Guo, Tianming Liu, Latent Source Mining of fMRI Data via Deep Belief Network, ISBI 2018.

Heng Huang*, Xintao Hu, Qinglin Dong, Yu Zhao, Shu Zhang, Lei Guo, Tianming Liu, Modeling Task fMRI Data via Mixture of Deep Expert Networks, ISBI 2018.

Wei Zhang, Jinglei Lv, Shu Zhang, Yu Zhao, Tianming Liu, Modeling Resting State FMRI Data via Longitudinal Supervised Stochastic Coordinate Coding, ISBI 2018.

Tuo Zhang, Xiao Li, Lin Zhao, Ying Huang, Lei Guo, Tianming Liu, Identification of Species-Preserved Cortical Landmarks, MICCAI 2018.

Shu Zhang, Tianming Liu, Dajiang Zhu, Exploring Fiber Skeletons via Joint Representation of Functional Networks and Structural Connectivity, MICCAI 2018.

Yu Zhao, Shu Liao, Yimo Guo, Liang Zhao, Zhennan Yan, Gerardo Hermosillo, Tianming Liu, Xiang Zhou, Yiqiang Zhan, Towards MR-Only Radiotherapy Treatment Planning: Synthetic CT Generation Using Multi-view Deep Convolutional Neural Networks, MICCAI 2018.

Yu Zhao, Fangfei Ge, Tianming Liu, 3D Deep Convolutional Neural Network Revealed the Value of Brain Network Overlap in Differentiating Autism Spectrum Disorder from Healthy Controls, MICCAI 2018.

Yu Zhao, Xiang Li, Wei Zhang, Shijie Zhao, Milad Makkie, Mo Zhang, Quanzheng Li, Tianming Liu, Modeling 4D fMRI Data via Spatio-Temporal Convolutional Neural Networks (ST-CNN), MICCAI 2018.

Yan Cui, Shijie Zhao, Han Wang, Leo Xie, Yaowu Chen, Junwei Han, Lei Guo, Fan Zhou, Tianming Liu, Identifying Brain Networks of Multiple Time Scales via Deep Recurrent Neural Network, MICCAI 2018.

Yu Zhao, Haixing Dai, Wei Zhang, Fangfei Ge, Tianming Liu, Two-stage Spatial Temporal Deep Learning Framework for Functional Brain Network Modeling, ISBI 2019.

Liting Wang, Xintao Hu, Huan Liu, Heng Huang, Lei Guo, Tianming Liu, Explore the Hierarchical Auditory Information Processing via Deep Convolutional Audoencoder, ISBI 2019.

Fangfei Ge, Shu Zhang, Heng Huang, Xi Jiang, Lei Guo, Xianqiao Wang, Tianming Liu, Exploring Intrinsic Functional Differences of Gyri, Sulci and 2-hinge, 3-hinge Joints on Cerebral Cortex, ISBI 2019.

Lin Zhao, Huan Liu, Xi Jiang, Shijie Zhao, Zhibin He, Tianming Liu, Lei Guo, Tuo Zhang, A Task Performance-guided Model of Functional Networks Identification, ISBI 2019.

Yin Zhang, Xintao Hu, Chunlin He, Yudan Ren, Huan Liu, Liting Wang, Lei Guo, Tianming Liu, A Two-stage DBN-based Method to Exploring Functional Brain Networks in Naturalistic Paradigm fMRI, ISBI 2019.

Qing Li, Qinglin Dong, Fangfei Ge, Ning Qiang, Yu Zhao, Han Wang, Heng Huang, Xia Wu, and Tianming Liu, Simultaneous Spatial-temporal Decomposition of Connectome-scale Brain Networks by Deep Sparse Recurrent Auto-encoders, IPMI 2019.

Ying Huang, Zhibin He, Lei Guo, Tianming Liu, Tuo Zhang, Multi-view Graph Matching of Cortical Landmarks. MICCAI 2019.

Tuo Zhang, Xiao Li, Lin Zhao, Ying Huang, Zhibin He, Lei Guo, Tianming Liu, Group-wise Graph Matching of Cortical Gyral Hinges. MICCAI 2019.

Wei Zhang, Lin Zhao, Qing Li, Shijie Zhao, Qinglin Dong, Xi Jiang, Tuo Zhang, Tianming Liu, Identify Hierarchical Structures from Task-based fMRI Data via Hybrid Spatiotemporal Neural Architecture Search Net, MICCAI 2019. 

Huan Wang, Ning Qiang, Bao Ge, Tianming Liu, Task fMRI guided fiber clustering via a deep clustering method, ISBI 2020.

Ning Qiang, Qinglin Dong, Bao Ge, Tianming Liu, Deep Variational Autoencoder for Modeling Functional Brain Networks and ADHD Identification, ISBI 2020.

Haixing DAI, Fangfei Ge, Qing Li, Wei Zhang, Tianming Liu, Optimize CNN model for fMRI signal classification via Adanet-based neural architecture search, ISBI 2020.

Tuo Zhang, Zhibin He, Xi Jiang, Lei Guo, Xiaoping Hu, Tianming Liu, Lei Du. Species-Shared and -Specific Structural Connections Revealed by Dirty Multi-Task Regression. MICCAI 2020.

Qinglin Dong, Ning Qiang, Jinglei Lv, Xiang Li, Tianming Liu, Quanzheng Li, Spatiotemporal Attention Autoencoder (STAAE) for ADHD Classification, MICCAI 2020.

Qing Li, Wei Zhang, Jinglei Lv, Xia Wu and Tianming Liu, Neural Architecture Search for Optimization of Spatial-temporal Brain Network Decomposition, MICCAI 2020.

Qinglin Dong, Ning Qiang, Jinglei Lv, Xiang Li, Tianming Liu, Quanzheng Li, Discovering Functional Brain Networks with 3D Residual Autoencoder (ResAE). MICCAI 2020.

Yudan Ren, Zeyang Tao, Wei Zhang, Tianming Liu, Modeling Hierarchical Spatial and Temporal Patterns of Naturalistic fMRI Volume via Volumetric Deep Belief Network with Neural Architecture Search, in press, ISBI 2021.

Lin Zhao, Haixing Dai, Xi Jiang, Tuo Zhang, Dajiang Zhu, Tianming Liu, Exploring the functional difference of gyri/sulci via hierarchical interpretable autoencoders, in press, MICCAI 2021.

Jiadong Yan, Yuzhong Chen, Shimin Yang, Shu Zhang, Mingxin Jiang, Zhonbo Zhao, Tuo Zhang, Yu Zhao, Benjamin Becker, Tianming Liu, Keith M Kendrick, Xi Jiang, Multi-Head GANNN: A Multi-Head Guided Attention Graph Neural Network for Modeling Spatio-Temporal Patterns of Holistic Brain Functional Networks, in press, MICCAI 2021. 

Xiaowei Yu, Dan Hu, Lu Zhang, Ying Huang, Zhengwang Wu, Tianming Liu, Li Wang, Weili Lin, Dajiang Zhu, Gang Li, Longitudinal Infant Functional Connectivity Prediction via Conditional Intensive Triplet Network, accepted, MICCAI 2022.

Lin Zhao, Haixing Dai, Zihao Wu, Tuo Zhang, Dajiang Zhu, Tianming Liu, Embedding Human Brain Function via Transformer, accepted, MICCAI 2022.

Shijie Zhao, Tianji Pang, Junwei Han, Tianming Liu, Dajiang Zhu, Hierarchical Brain Networks Decomposition via Prior Knowledge Guided Deep Belief Network, accepted, MICCAI 2022.

Xiaowei Yu, Lu Zhang, Yanjun Lyu, Tianming Liu, and Dajiang Zhu. Supervised Deep Tree in Alzheimer's Disease, In 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI). 2023.

Lu Zhang, Xiaowei Yu, Yanjun Lyu, Tianming Liu, and Dajiang Zhu. Representative Functional Connectivity Learning for Multiple Clinical Groups in Alzheimer's Disease, In 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI). 2023.

Yu Du, Liting Wang, Lei Guo, Junwei Han, Tianming Liu, Xintao Hu. Topological Similarity Between Artificial and Biological Neural Networks, In 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI). 2023.

Zili Kang, Yifan Lv, Mengshen He, Yiheng Liu, Tianming Liu, Bao Ge, Brain surface can predict fiber connections, In 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI). 2023.

Yiheng Liu, Enjie Ge, Ning Qiang, Tianming Liu and Bao Ge, Spatial-temporal convolutional attention for mapping functional brain networks, In 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI). 2023.

IEEE/ACM and AI Conferences:

Tianming Liu, Wei Qi, Hong-Jiang Zhang, and Feihu Qi, A Content-aware Rate Controller for Streamed Delivery of MPEG-4 FGS Video, IEEE International Conference on Multimedia and Expo (ICME), Tokyo Japan, 2001, pp. 669- 672.

Tianming Liu, Wei Qi, Hong-Jiang Zhang, and Feihu Qi, A Systematic Rate Controller for MPEG-4 FGS Video Streaming, IEEE International Conference on Image Processing (ICIP), Greece, 2001, pp. 985-988.

Tianming Liu, Hong-Jiang Zhang, and Feihu Qi, A Novel Video Key Frame Extraction Algorithm, IEEE International Symposium on Circuits and Systems (ISCAS), Arizona, 2002, pp. 149-152.

Tianming Liu, Hong-Jiang Zhang, and Feihu Qi, Perceptual Frame Dropping in Adaptive Video Streaming, IEEE International Symposium on Circuits and Systems, Arizona, 2002. pp. Special section on Multimedia.

Gang Li, Lei Guo, Tianming Liu, Grouping of Brain MR Images via Affinity Propagation, IEEE International Symposium on Circuits and Systems (ISCAS) 2009.

Yanting Lu, Jingfeng Lu, Tianming Liu, Jingyu Yang, Automated Cell Phase Classification for Zebrafish Fluorenscence Microscope Images, ICPR 2010.

Gang Li, Lei Guo, Jingxin Nie, Kaiming Li, Tianming Liu, Direction Field Diffusion on Cortical Surface via Graph Cuts, CVPR Mathematical Methods in Biomedical Image Analysis (MMBIA) 2010.

Kaiming Li, Tuo Zhang, Xintao Hu, Dajiang Zhu, Hanbo Chen, Xi Jiang, Fan Deng, Jinglei Lv, Carlos, Faraco, Degang Zhang, Arsham Mesbah, Junwei Han, Lie Lu, Xian-Sheng Hua, Lei Guo, Stephen Miller, Tianming Liu, Human-friendly Attention Models for Video Summarization, ACM 12th International Conference on Multimodal Interfaces (ICMI), 2010.

Xiang Ji, Junwei Han, Xintao Hu, Kaiming Li, Fan Deng, Jun Fang, Lei Guo and Tianming Liu, Retrieving Video Shots in Semantic Brain Imaging Space Using Manifold-Ranking, ICIP 2011.

Anirban Mukhopadhyay, Zhen Qian, Suchendra Bhandarkar, Tianming Liu, Szilard Voros, Shape analysis of left ventricular endocardial surface and its application in detecting coronary artery disease, Sixth International Conference on Functional Imaging and Modeling of the Heart (FIMH), 2011.

Sheng He, Junwei Han, Xintao Hu, Ming Xu, Lei Guo, Tianming Liu, A Biologically Inspired Computational Model for Image Saliency Detection, ACM Multimedia, 2011.

Xi Jiang, Tuo Zhang, Xintao Hu, Lie Lu, Junwei Han, Lei Guo, Tianming Liu. Music/Speech Classification Using High-level Features Derived from fMRI Brain Imaging, pp. 825-828, ACM Multimedia, 2012.

Jinli Ou, Li Xie, Peng Wang, Xiang Li, Dajiang Zhu, Yufeng Wang, Yaowu Chen, Jing Zhang, Tianming Liu, Modeling Brain Functional Dynamics via Hidden Markov Models, IEEE EMBS Conference on Neural Engineering, pp. 569-572, 2013.

Jianchuan Xing, Jinglei Lv, Zhichao Lian, Xiang Li, Dajiang Zhu, Tianming Liu, Jing Zhang, Group-wise Change Point Detection in Task FMRI Data by Bayesian Methods, IEEE EMBS Conference on Neural Engineering, pp. 597-600, 2013.

Jinglei Lv, Xi Jiang, Xiang Li, Dajiang Zhu, Hanbo Chen, Tuo Zhang, Shu Zhang, Xintao Hu, Junwei Han, Heng Huang, Jing Zhang, Lei Guo, Tianming Liu, Identifying Functional Networks via Sparse Representation of  Whole-brain FMRI Signals, IEEE EMBS Conference on Neural Engineering, pp. 778-781, 2013.

Shijie Zhao, Xi Jiang, Junwei Han, Xintao Hu, Dajiang Zhu, Jinglei Lv, Tuo Zhang, Lei Guo and Tianming Liu, Decoding Auditory Saliency from FMRI Brain Imaging, ACM Multimedia, pp. 873-876, 2014.

Shijie Zhao, Junwei Han, Xi Jiang, Xintao Hu, Jinglei Lv, Shu Zhang, Bao Ge, Lei Guo, Tianming Liu, Exploring auditory network composition during free listening to audio excerpts via group-wise spare representation, pp. 1-6, ICME 2016.

Saed Rezayi, Zhengliang Liu, Zihao Wu, Chandra Dhakal, Bao Ge, Chen Zhen, Tianming Liu, Sheng Li, AgriBERT: Knowledge-Infused Agricultural Language Models for Matching Food and Nutrition. In IJCAI-ECAI 2022 Special Track on AI for Good, in press, 2022.

Saed Rezayi, Haixing Dai, Zhengliang Liu, Zihao Wu, Akarsh Hebbar, Andrew H. Burns, Lin Zhao, Dajiang Zhu, Xiang Li, Quanzheng Li, Wei Liu, Sheng Li and Tianming Liu. ClinicalRadioBERT: Knowledge-Infused Few Shot Learning for Clinical Notes Named Entity Recognition. In: The 13th International Workshop on Machine Learning in Medical Imaging (MLMI 2022), in conjunction with MICCAI 2022, 2022.

Haixing Dai, Qing Li, Lin Zhao, Liming Pan, Cheng Shi, Zhengliang Liu, Zihao Wu, Lu Zhang, Shijie Zhao, Xia Wu, Dajiang Zhu, Tianming Liu. "Graph Representation Neural Architecture Search for Optimal Spatial/Temporal Functional Brain Network Decomposition." In International Workshop on Machine Learning in Medical Imaging (MLMI 2022), in conjunction with MICCAI 2022, 2022.