Sheng Li

Assistant Professor
Department of Computer Science 
University of Georgia

549 Boyd GSRC, University of Georgia, Athens, GA 30602
Email: sheng.li [AT] uga.edu

Research Interests: Machine learning (unsupervised learning, transfer learning, deep learning) with applications to big data analytics, computer vision, natural language processing, user modeling, causal inference, etc.

Education: Ph.D. in CE, Northeastern, 2017; M.S. in CS, NUPT, 2012; B.S. in CS, NUPT, 2010.

Openings: I am continuously looking for highly-motivated Ph.D. students and visiting students/scholars to work on machine learning, computer vision and causal inference. Please send me your CV if interested.

News [more...]

  • 05/10/2019, Three papers on graph neural networks, causal inference, and dictionary learning are accepted at IJCAI 2019 (Acceptance Rate: 17.9%).
  • 04/29/2019, Two papers on sequence modeling and adversarial training are accepted at KDD 2019 (Acceptance Rate: 14%).
  • 04/14/2019, One short paper on factorization machines is accepted at SIGIR 2019 (Acceptance Rate: 24.4%).
  • 04/01/2019, I gave an invited talk on machine learning and deep learning at the College of Education, The University of Iowa, IA.
  • 03/16/2019, I accepted the invitation to serve as Program Committee member of IEEE BigData 2019.
  • 03/11/2019, One paper on multi-view ensemble clustering is accepted by IEEE Trans. NNLS.
  • 03/06/2019, I received the Adobe Data Science Research Award.
  • 03/06/2019, I accepted the invitation to serve as Program Committee member of UAI 2019.
  • 03/05/2019, I am elevated to be Senior Member of IEEE.
  • 02/24/2019, One paper on scene graph generation is accepted at CVPR 2019 (Acceptance Rate: 25.2%).
  • 02/22/2019, I accepted the invitation to serve as Program Committee member of BMVC 2019.
  • 02/20/2018, I will co-organize the First International Workshop on Bringing Semantic Knowledge into Vision and Text Understanding, at IJCAI 2019.
  • 02/02/2019, I accepted the invitation to serve as Program Committee member of NeurIPS 2019.
  • 02/01/2019, One paper is accepted to ICASSP 2019.
  • 02/01/2019, I accepted the invitation to serve as Program Committee member of ICCV 2019.
  • 01/15/2019, I gave an invited talk on deep learning at the Kennesaw State University, Marietta, GA.
  • 01/13/2019, I accepted the invitation to serve as Program Committee member of KDD 2019.

Awards and Honors

  • Adobe Data Science Research Award, 2019
  • Baidu Research Fellowship, 2016-2017
  • Chinese Government Award for Outstanding Self-Financed Students Abroad, 2015-2016
  • The inaugural Adobe Research Fellowship Finalist, 2015
  • NEU Outstanding Graduate Student Award, 2014-2015
  • Best Paper Award, SDM 2014
  • Best Paper Award Candidate, ICME 2014
  • Best Student Paper Honorable Mention Award, FG 2013
  • Student Travel Awards for SDM 2014 / ICDM 2014 / CIKM 2015 / CVPR 2016 / CIKM 2016 / IJCAI 2016 / KDD 2016

Teaching

Services

  • Associate Editor: IEEE Computational Intelligence Magazine (2019 - ), Neurocomputing (2017 - ), IET Image Processing (2017 - ), Neural Computing and Applications (2017 - ), Journal of Electronic Imaging (2018 - )
  • Program Chair: IJCAI-Tusion (2019), CVPR-AMFG (2019)
  • Publicity Chair: ICMLA (2016), TCMFTL (2016), AMFG (2015-2017)
  • Special Session Co-Chair: VCIP (2017)
  • SPC Member: AAAI (2019)
  • PC Member: NeurIPS (2019), ICML (2019), CVPR (2019), ICCV (2019), IJCAI (2015-2019), KDD (2018-2019), ICLR (2019), UAI (2019), IEEE BigData(2019), BMVC (2019), NIPS (2018), AAAI (2017, 2018), ACM MM (2018), MIPR (2018-2019), PAKDD (2017-2018), IEEE BigData (2018), ICTAI (2018), AFFCON (2018), DSAA (2017), FG (2017), ACII (2017), NLPCC (2017)
  • Reviewer: IEEE TPAMI / TKDE / TIP / TNNLS / TMM / TBD / TC / TCSVT / TETCI, ACM CSUR / TKDD / TOSN / TIST / TOMM, Pattern Recognition, Neurocomputing, PLoS ONE, IJPRAI, JVCI, JEI, OE, etc.

Selected Publications [Full List] [Google Scholar]

Journal Papers

  1. Sheng Li*, Zhiqiang Tao*, Kang Li, Yun Fu. Visual to Text: Survey of Image and Video Captioning. IEEE Trans. Emerging Topics in Computational Intelligence (T-ETCI), 2019. (* indicates equal contribution)
  2. Zhiqiang Tao, Hongfu Liu, Sheng Li, Zhengming Ding, and Yun Fu. Marginalized Multi-View Ensemble Clustering. IEEE Trans. Neural Networks and Learning Systems (TNNLS), 2019.
  3. Sheng Li, Ming Shao, Yun Fu: Person Re-identification by Cross-View Multi-Level Dictionary Learning. IEEE Trans. Pattern Analysis and Machine Intelligence (T-PAMI), 2018. [Code]
  4. Sheng Li, Kang Li, Yun Fu: Self-Taught Low-Rank Coding for Visual Learning. IEEE Trans. Neural Networks and Learning Systems (T-NNLS), 29(3): 645-656, 2018. [Code]
  5. Sheng Li, Kang Li, Yun Fu: Early Recognition of 3D Human Actions. ACM Trans. Multimedia Computing Communications and Applications (TOMM), 14(1s): 20:1-20:21, 2018.
  6. Sheng Li, Ming Shao, Yun Fu: Multi-View Low-Rank Analysis with Applications to Outlier Detection. ACM Trans. Knowledge Discovery from Data (TKDD) , 12(3): 32:1-32:22, 2018. [Code]
  7. Hongfu Liu, Ming Shao, Sheng Li, Yun Fu: Infinite Ensemble Clustering. Data Mining and Knowledge Discovery (DMKD), 32(2): 385-416, 2018.
  8. Chengcheng Jia, Ming Shao, Sheng Li, Handong Zhao, Yun Fu. Stacked Denoising Tensor Auto-Encoder for Action Recognition with Spatiotemporal Corruptions, IEEE Trans. Image Processing (T-IP), 27(4): 1878-1887, 2018.
  9. Zhiqiang Tao, Hongfu Liu, Sheng Li, Zhengming Ding, Yun Fu: Robust Spectral Ensemble Clustering via Rank Minimization. ACM Trans. Knowledge Discovery from Data (TKDD) , 2018.
  10. Yan Zhang, Zhao Zhang, Sheng Li, Jie Qin, Guangcan Liu, Meng Wang, Shuicheng Yan: Unsupervised Nonnegative Adaptive Feature Extraction for Data Representation. IEEE Trans. Knowledge and Data Engineering (T-KDE), 2018.
  11. Kai Li, Zhengming Ding, Sheng Li, Yun Fu: Towards Resolution-Invariant Person Re-identification via Projective Dictionary Learning. IEEE Trans. Neural Networks and Learning Systems (T-NNLS), 2018.
  12. Kang Li, Sheng Li, Sangmin Oh, Yun Fu. Videography based Unconstrained Video Analysis, IEEE Trans. Image Processing (T-IP), 26(5): 2261-2273, 2017.
  13. Guoqiang Zhong, Yan Zheng, Sheng Li, Yun Fu: SLMOML: Online Metric Learning with Global Convergence, IEEE Trans. Circuits and Systems for Video Technology (T-CSVT), 2017.
  14. Sheng Li, Yun Fu: Learning Robust and Discriminative Subspace with Low-Rank Constraints. IEEE Trans. Neural Networks and Learning Systems (T-NNLS), 27(11): 2160-2173, 2016. [Code]
  15. Sheng Li, Yun Fu: Learning Balanced and Unbalanced Graphs via Low-Rank Coding. IEEE Trans. Knowledge and Data Engineering (T-KDE), 27(5): 1274-1287, 2015. [Code]
  16. Liangyue Li*, Sheng Li*, Yun Fu: Learning Low-Rank and Discriminative Dictionary for Image Classification. Image and Vision Computing (IVC), 32(10): 814-823, 2014. (* indicates equal contribution) [Code]
  17. Ya Su, Sheng Li, Shengjin Wang, and Yun Fu, Submanifold Decomposition, IEEE Trans. Circuits and Systems for Video Technology (T-CSVT), 24(11): 1885-1897, 2014.
  18. Xiao-Yuan Jing, Sheng Li, David Zhang, Jian Yang, Jing-Yu Yang: Supervised and Unsupervised Parallel Subspace Learning for Large-Scale Image Recognition. IEEE Trans. Circuits System for Video Technology (T-CSVT), 22(10): 1497-1511, 2012.
  19. Xiao-Yuan Jing, Sheng Li, David Zhang, Chao Lan, Jingyu Yang: Optimal Subset-division based Discrimination and Its Kernelization for Face and Palmprint Recognition. Pattern Recognition (PR), 45(10): 3590-3602, 2012.
  20. Xiao-Yuan Jing, Sheng Li, Chao Lan, David Zhang, Jingyu Yang, Qian Liu: Color Image Canonical Correlation Analysis for Face Feature Extraction and Recognition. Signal Processing (SP), 91(8): 2132-2140, 2011.

Conference Papers

  1. Xiaodong Jiang, Pengsheng Ji and Sheng Li. CensNet: Convolution with Edge-Node Switching in Graph Neural Networks. IJCAI, 2019.
  2. Liuyi Yao, Sheng Li, Yaliang Li, Hongfei Xue, Jing Gao, Aidong Zhang. On the Estimation of Treatment Effect with Text Covariates. IJCAI, 2019.
  3. Zhao Zhang, Weiming Jiang, Zheng Zhang, Sheng Li, Guangcan Liu, Jie Qin. Scalable Block-Diagonal Locality-Constrained Projective Dictionary Learning. IJCAI, 2019.
  4. Xiaowei Jia, Sheng Li, Handong Zhao, Sungchul Kim and Vipin Kumar. Towards Robust and Discriminative Sequential Data Learning: When and How to Perform Adversarial Training? KDD, 2019.
  5. Zhiqiang Tao, Sheng Li, Zhaowen Wang, Chen Fang, Longqi Yang, Handong Zhao and Yun Fu. Log2Intent: Towards Interpretable User Modeling via Recurrent Semantics Memory Unit. KDD, 2019.
  6. Jiuxiang Gu, Handong Zhao, Zhe Lin, Sheng Li, Jianfei Cai and Mingyang Ling. Scene Graph Generation with External Knowledge and Image Reconstruction. CVPR, 2019.
  7. Xiaowei Jia, Sheng Li, Ankush Khandelwal, Guruprasad Nayak, Anuj Karpatne and Vipin Kumar. Spatial Context-Aware Networks for Mining Temporal Discriminative Period in Land Cover Detection. SDM, 2019.
  8. Zheng Zhang, Guosen Xie, Yang Li, Sheng Li and Zi Huang. SADIH: Semantic-Aware DIscrete Hashing. AAAI, 2019.
  9. Donghyun Kim, Sungchul Kim, Handong Zhao, Sheng Li, Ryan Rossi and Eunyee Koh. Domain Switch-Aware Holistic Recurrent Neural Network for Modeling Multi-Domain User Behavior, WSDM, 2019.
  10. Xueyu Mao, Saayan Mitra and Sheng Li. Training Streaming Factorization Machines with Alternating Least Squares. SIGIR, 2019.
  11. Liuyi Yao, Sheng Li, Yaliang Li, Mengdi Huai, Jing Gao and Aidong Zhang. Representation Learning for Treatment Effect Estimation from Observational Data, NIPS, 2018. [Code]
  12. Kai Li, Sheng Li, Zhengming Ding, Weidong Zhang, and Yun Fu. Latent Discriminant Subspace Representations for Multi-view Outlier Detection. AAAI, 2018.
  13. Kai Li, Zhengming Ding, Sheng Li, and Yun Fu. Discriminative Semi-coupled Projective Dictionary Learning for Low-Resolution Person Re-Identification. AAAI, 2018.
  14. Shumin Jing, Sheng Li. Contextual Collaborative Filtering for Student Response Prediction in Mixed-Format Tests. AAAI, 2018. (Poster)
  15. Zhengming Ding, Sheng Li, Ming Shao and Yun Fu. Graph Adaptive Knowledge Transfer for Unsupervised Domain Adaptation. ECCV, 2018.
  16. Tuan Manh Lai, Trung Bui, Sheng Li. A Review on Deep Learning Techniques Applied to Answer Selection. COLING, 2018.
  17. Sheng Li, Yun Fu. Matching on Balanced Nonlinear Representations for Treatment Effects Estimation. NIPS, 2017.
  18. Sheng Li, Yun Fu. Robust Multi-Label Semi-Supervised Classification. IEEE BigData, 2017.
  19. Sheng Li, Hongfu Liu, Zhiqiang Tao, and Yun Fu. Multi-View Graph Learning with Adaptive Label Propagation. IEEE BigData, 2017. [Code]
  20. Zhiqiang Tao, Hongfu Liu, Sheng Li, Zhengming Ding, and Yun Fu. From Ensemble Clustering to Multi-View Clustering. IJCAI, 2017.
  21. Sheng Li, Nikos Vlassis, Jaya Kawale and Yun Fu. Matching via Dimensionality Reduction for Estimation of Treatment Effects in Digital Marketing Campaigns. IJCAI, 2016.
  22. Sheng Li. Learning Robust Representations for Data Analytics. IJCAI, 2016. (Poster)
  23. Sheng Li, Yaliang Li and Yun Fu. Multi-View Time Series Classification: A Discriminative Bilinear Projection Approach. CIKM, 2016.
  24. Sheng Li, Yun Fu. Unsupervised Transfer Learning via Low-Rank Coding for Image Clustering, IJCNN, 2016. [Code]
  25. Zhiqiang Tao, Hongfu Liu, Sheng Li and Yun Fu. Robust Spectral Ensemble Clustering. CIKM, 2016.
  26. Hongfu Liu, Ming Shao, Sheng Li and Yun Fu. Infinite Ensemble for Image Clustering. KDD, 2016.
  27. Sheng Li, Kang Li and Yun Fu. Temporal Subspace Clustering for Human Motion Segmentation. ICCV, 2015. [Code]
  28. Sheng Li, Ming Shao and Yun Fu. Cross-View Projective Dictionary Learning for Person Re-identification. IJCAI, 2015. [Code]
  29. Ming Shao, Sheng Li, Zhengming Ding and Yun Fu. Deep Linear Coding for Fast Graph Clustering. IJCAI, 2015.
  30. Sheng Li, Jaya Kawale and Yun Fu. Deep Collaborative Filtering via Marginalized Denoising Auto-encoder. CIKM, 2015.
  31. Sheng Li, Jaya Kawale and Yun Fu. Predicting User Behavior in Display Advertising via Dynamic Collective Matrix Factorization, SIGIR, 2015.
  32. Sheng Li, Ming Shao and Yun Fu. Multi-view Low-Rank Analysis for Outlier Detection. SDM, 2015. [Code]
  33. Sheng Li, Yun Fu, Robust Subspace Discovery through Supervised Low-Rank Constraints, SDM, 2014. (Best Paper Award) [Code]
  34. Kang Li, Sheng Li, and Yun Fu, Early Classification of Ongoing Observation, ICDM, 2014.
  35. Ming Shao, Sheng Li, Tongliang Liu, Dacheng Tao, Thomas S. Huang, and Yun Fu, Learning Relative Features Through Adaptive Pooling for Image Classification, ICME, 2014. (Best Paper Award Candidate)
  36. Sheng Li, Ming Shao, and Yun Fu, Locality Linear Fitting One-class SVM with Low-Rank Constraints for Outlier Detection, IJCNN, 2014.
  37. Sheng Li, Yun Fu. Low-Rank Coding with b-Matching Constraint for Semi-supervised Classification, IJCAI, 2013. [Code]
  38. Liangyue Li, Sheng Li, and Yun Fu. Discriminative Dictionary Learning with Low-Rank Regularization for Face Recognition. IEEE FG, 2013. (Best Student Paper Honorable Mention Award) [Code]

Sponsors