Liming CAIPH.D. TEXAS A&M UNIVERSITY, 1994
My current research interests are in bioinformatics and data science, with the focuses on developing novel statistical learning methods and graph-theoretic algorithms to answer challenge questions in these areas. One of my recent works is a novel machine learning framework called Markov k-tree that is effective and efficient for mining global relationships in sequence data. One such ongoing application is to decode the information of higher-order residue interactions crucial to bio-molecular 3D structure prediction. My research projects range from algorithm design, user-interface development, programming, to in-depth investigations on information theory, algorithmic graph theory, and theory of computation. They provide rich opportunities for graduate and undergraduate students to conduct collaborative and independent research. My research is sponsored by National Institutes of Health (NIH) and National Science Foundation (NSF).Last updated: August 2017.
In Spring 2018, I will teach CSCI 8610 Special Topics in Theoretical Computer Science: Probabilistic Networks: Randomness, Algorithms and Learning.