Sheng Li

Assistant Professor, School of Data Science

178 Elson, University of Virginia, Charlottesville, VA 22903
Email: shengli [AT]

Research Interests: Trustworthy Representation Learning (e.g., Robustness, Fairness, Causality, Transferability); Visual Intelligence; User Modeling; Natural Language Understanding; Bioinformatics; Biomedical Informatics.

Background: Sheng Li is an Assistant Professor of Data Science at the University of Virginia (UVA). Prior to joining UVA, he was an Assistant Professor of Computer Science at the University of Georgia from 2018 to 2022, and a Data Scientist in 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.

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.

News [more...]

  • 09/2022, I will co-organize a tutorial (Machine Learning for Causal Inference) and a workshop (AI for Web Ads) at AAAI 2023.
  • 09/2022, Received the Adobe Data Science Research Award.
  • 09/2022, One paper on causality guided model interpretation is accepted by IEEE Trans. Knowledge and Data Engineering (TKDE).
  • 08/2022, Received a HHS R01 Grant (as Co-I; PI: Prof. Andrea Sikora) to develop AI based health IT tools to assist critical care pharmacists.
  • 08/2022, I accepted the invitations to serve as Tutorial Co-Chair and Senior PC member for SDM 2023, and Area Chair for ICLR 2023.
  • 08/2022, Two papers are accepted at ACM CIKM 2022; One paper is accepted at MICCAI-MLMI 2022.
  • 07/2022, Received an NIH U01 Grant (as Co-I; PI: Prof. Natarajan Kannan) to annotate dark ion-channel functions by language modeling.
  • 06/2022, Received an NIH R01 Supplement Grant (as Co-I; PI: Prof. Donglan Zhang) to examine disparities in ADRD using machine learning.
  • 05/2022, One paper on class-imbalanced domain adaptation is accepted at KDD 2022.
  • 05/2022, My PhD student Zhongliang Zhou received the Outstanding Graduate Student Award from CS department.
  • 04/2022, One paper on knowledge-infused agricultural language models is accepted at IJCAI 2022 (AI for Good Track).
  • 03/2022, I accepted the invitation to serve as Area Chair for NeurIPS 2022.
  • 03/2022, Received a Home Depot Gift Grant (PI) to support our research on deep learning and knowledge graph.
  • 03/2022, Received a DoD Grant (PI) through KRI to support our research on visual intelligence.
  • 03/2022, One paper on multi-task adversarial learning and causal inference is accepted at CHIL 2022.
  • 03/2022, Received an USGS Grant (Sole PI) to support our research on individual fish identification.
  • 02/2022, I accepted the invitation to serve as Associate Editor for IEEE Transactions on Neural Networks and Learning Systems (T-NNLS).
  • 02/2022, I received the Best Associate Editor Award from IEEE Transactions on Circuits and Systems for Video Technology.
  • 01/2022, One paper on open-set single domain generalization is accepted at ICLR 2022.
  • 12/2021, I receive the Fred C. Davidson Early Career Scholar Award.
  • 12/2021, Three papers on causal inference, unsupervised domain adaptation, and multi-modal learning are accepted at SDM 2022.
  • 10/2021, Three paper are accepted to IEEE T-NNLS, IEEE BigData 2021, and AAAI 2022 (Student Poster).
  • 08/2021, One paper is accepted by Nature Communications; Three papers are accepted at IEEE ICDM 2021 and ACM CIKM 2021.
  • 08/2021, I gave a keynote talk at the 3rd Workshop on Continual and Multimodal Learning for Internet of Things (Co-located with IJCAI 2021).
  • 05/2021, Two papers are accepted at ACM SIGKDD 2021 and IEEE T-NNLS.
  • 05/2021, My PhD students Saed Rezayi and Ronghang Zhu received the Excellent Graduate Students Research Awards from CS department.
  • 05/2021, I received the Faculty Teaching Excellence Award from the Department of Computer Science.
  • 04/2021, Two papers on self-tuning GCN and pose image generation are accepted at ACM SIGIR 2021 and ACM ICMR 2021.
  • 03/2021, I will co-organize The 10th IEEE International Workshop on Analysis and Modeling of Faces and Gestures (AMFG), at CVPR 2021.
  • 03/2021, Three papers are accepted at NAACL 2021, IEEE ICME 2021, and IEEE MIPR 2021.
  • 02/2021, Received a Cisco Gift Grant (Sole PI) to support our research on fair machine learning.
  • 02/2021, Received an ARO Grant (Sole PI) to support our research on graph reasoning and visual understanding.
  • 12/2020, Our survey paper on causal inference is accepted by ACM TKDD; One paper on multi-view learning is accepted at AAAI 2021.
  • 12/2020, I accepted the invitation to serve as Associate Editor for IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT).
  • 12/2020, Received a DoD Grant (Sole PI) to support our research on representation learning and visual understanding.

Awards and Honors

  • Fred C. Davidson Early Career Scholar Award, 2022
  • Best Associate Editor Award, IEEE TCSVT, 2022
  • CS Faculty Teaching Excellence Award, 2021
  • INNS Aharon Katzir Young Investigator Award, 2020
  • CS Faculty Research Excellence Award, 2020
  • M. G. Michael Award, 2020
  • Adobe Data Science Research Award, 2019
  • Baidu Research Fellowship, 2016-2017
  • Chinese Government Award for Outstanding Self-Financed Students Abroad, 2015-2016
  • 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


  • Panelist: NSF (III, NAIRI, CRII, GRFP), CDC
  • Associate Editor: IEEE Trans. Neural Networks and Learning Systems (2022 - ), IEEE Transactions on Circuits and Systems for Video Technology (2021 - ), IEEE Computational Intelligence Magazine (2019 - ), Neurocomputing (2017 - 2022), Journal of Electronic Imaging (2018 - 2022), IET Image Processing (2017 - 2020)
  • Editorial Board Member: Frontiers in Signal Processing (2021 - ), Neural Computing and Applications (2017 - )
  • Program Chair: CVPR-AMFG (2021), IJCAI-Tusion (2020), IJCAI-Tusion (2019), CVPR-AMFG (2019)
  • Tutorial Chair: SDM (2023)
  • Publicity Chair: ICMLA (2016), TCMFTL (2016), AMFG (2015-2017)
  • Area Chair: NeurIPS (2022), ICLR (2022-2023), ICPR (2020-2022), VCIP (2017)
  • SPC Member: IJCAI (2020-2021), AAAI (2019-2022), SDM (2023)