Tao Jiang

Tao Jiang is a Distinguished Professor in the Department of Computer Science and Engineering at the University of California, Riverside (UCR). He holds academic affiliations with the Algorithms and Computational Biology Lab, Genetics Graduate Program, Institute for Integrative Genome Biology, and Center for Plant Cell Biology. His research focuses on algorithm design, computational molecular biology, and finite automata complexity. He has held visiting positions at Tsinghua University and the Shanghai Center for Bioinformation Technology.

Education: B.S. from University of Science and Technology of China (1984), Ph.D. from University of Minnesota (1988). Former faculty at McMaster University (1989–2001).

Research Interests: Algorithmic techniques for string/tree/graph problems, approximation algorithms, Kolmogorov complexity applications, computational genomics, isoform inference, metagenomics, and algorithmic bioinformatics tools like PedPhase, TISHunter, MSOAR, and IsoLasso.

Grants: Funded by NSF (EAGER, ABI) and NIH (NIDDK). Collaborations with Frances Sladek, Thomas Girke, and James Borneman.

Teaching: CS 141 (Intermediate Data Structures), CS 238 (Algorithmic Techniques in Computational Biology), CS 150 (Automata/Formal Languages), and CS 260 (Bioinformatics Seminar). Office hours in Winston Chung Hall.

Professional Contributions: Editorial board roles at Journal of Combinatorial Optimization, BMC Bioinformatics, and Algorithmica. Recent conference involvement at RECOMB 2023 and ISMB/ECCB 2023.