Associate Professor, School of Data Science
178 Elson, University of Virginia, Charlottesville, VA 22903
Email: shengli [AT] virginia.edu
Research Interests: Trustworthy Representation Learning (e.g., Robustness, Fairness, Causality, Transferability); Computer Vision; Interdisciplinary Applications (Bioinformatics, Biomedical Informatics, Public Health, Ecology, Education, etc.)
Openings: I am continuously looking for highly-motivated Ph.D. students to work on machine learning, computer vision and causal inference. Please send me your CV if interested.
Short Bio: Sheng Li is an Associate Professor of Data Science at the University of Virginia (UVA). He was an Assistant Professor of Data Science at UVA from 2022 to 2023, an Assistant Professor of Computer Science at the University of Georgia from 2018 to 2022, and a Data Scientist at Adobe Research from 2017 to 2018. He received his PhD degree in Computer Engineering from Northeastern University in 2017 under the supervision of Prof. Yun Raymond Fu. He received his Master degree and Bachelor degree from School of Computer Science at Nanjing University of Posts and Telecommunications in 2012 and 2010, respectively. His recent research interests include trustworthy representation learning, graph neural networks, visual intelligence, and causal inference. He has published over 140 papers, and has received over 10 research awards, such as the INNS Aharon Katzir Young Investigator Award, Fred C. Davidson Early Career Scholar Award, Adobe Data Science Research Award, Cisco Faculty Research Award, and SDM Best Paper Award. He has served as Associate Editor for seven international journals such as IEEE Trans. Neural Networks and Learning Systems (TNNLS) and IEEE Trans. Circuits and Systems for Video Technology (TCSVT), and has served as an Area Chair for IJCAI, NeurIPS, ICML, and ICLR.