I am a tenure-track Assistant Professor in the Department of Computer Science at University of Illinois Chicago (UIC). I lead the Responsible and Reliable AI Lab (R2 Lab). I received my PhD degree in Computer Science at Arizona State University (ASU) in 2022 advised by Dr. Huan Liu, M.Eng. degree in Industrial Engineering at Rensselaer Polytechnique Institute (RPI), and B.Eng. degree in Industrial Engineering at Huazhong University of Science & Technology (HUST). My research interests are broadly in AI, with a particular focus on socially responsible AI, causal machine learning, and AI for social good. More details can be found in my CV.

Prospective students: I am always actively looking for self-motivated PhD students to conduct research in responsible AI (e.g., fairness, interpretability/explainability, and privacy) and reliable AI (e.g., robustness and uncertainty quantification), causal machine learning, and data mining in general. I’m also happy to work with self-funded masters and undergraduate students. Interested students, please email me with your CV and transcript(s).

News

  • [06/2024] Invited to serve as the EMNLP’24 Area Chair.
  • [06/2024] Our JORA paper is accepted to the ACL’24 System Demo Track.
  • [05/2024] Invited talk “Conformal Methods for Reliable and Fair Machine Learning” at the IDEAL Graph Representation Learning Workshop.
  • [05/2024] Our tutorial and survey paper “Safe Multi-Modal Machine Learning” are accepted to KDD’24.
  • [05/2024] Our NAIRR Pilot project on uncertainty quantification for LLMs has been selected!
  • [05/2024] Our paper “Conformalized Link Prediction” is accepted to KDD’24.
  • [05/2024] Our PAKDD’24 paper “Interpreting Pretrained Language Models via Concept Bottlenecks” received the Best Paper Award.
  • [04/2024] Invited to serve as an Area Chair at ICDM’24.
  • [02/2024] Co-organizing the 2024 Web Conference workshop AI-Driven Online Advertising.
  • [02/2024] Our US patent “Systems and Methods for Unsupervised Cyberbullying Detection via Time-Informed Gaussian Mixture Model” is granted.
  • [01/2024] One paper accepted to PAKDD’24.
  • [01/2024] Invited to serve as a tutorial co-chair at IEEE Big Data’24.
  • [01/2024] Invited to serve on an NSF panel.
  • [12/2023] Selected as one of the AAAI’24 New Faculty Highlight Speakers.
  • [10/2023] Invited talk at Case Western Reserve University.
  • [10/2023] One paper accepted to UbiComp’23.
  • [09/2023] One paper accepted to NeurIPS’23.
  • [09/2023] Our workshop on Responsible Language Models is accepted to AAAI’24. Co-organizing with Vector Institute for AI.
  • [09/2023] Invited talk at Pacific Causal Inference Conference 2023, Sept 16-17. Beijing, China
  • [08/2023] Invited talk at NSF Tripods Workshop on Privacy, Fairness and Causality in Graphs. UCSC. Oct 19-20.
  • [08/2023] Received an NSF III Medium grant as a Co-PI. Thanks, NSF!
  • [08/2023] Two papers accepted to CIKM’23.
  • [07/2023] Invited to give a talk at LMU Munich.
  • [07/2023] One paper accepted to ECAI’23.
  • [06/2023] Invited to serve as a Senior PC member for AAAI’24.
  • [06/2023] Thrilled to win the runner-up of the 2022-23 INNS Doctoral Dissertation Award!
  • [06/2023] One paper accepted to ACL’23 Clinical NLP workshop.
  • [04/2023] Our work on intersectional fairness is accepted to IJCAI’23 Survey Track.
  • [01/2023] Receiving a gift grant from Cisco Research for the project on Privacy-Preserving GNNs. Thanks, Cisco!