About me

I am currently a full-time researcher at NEC Laboratories America Inc., working with Dr. Haifeng Chen. Before that, I received my Ph.D. in Computer Sciences from the University of Wisconsin-Madison, advised by Prof. Sharon (Yixuan) Li. My research aims to pave the way to a reliable Open-world Machine Learning system, which revolves around three aspects:

  • Out-of-distribution (OOD) Detection: In the open world, the AI system will encounter new contexts and data that were not taught to the algorithms during training. A reliable machine learning model should not only accurately classify in-distribution (ID) samples but also possess the capability to identify samples that lie outside the known distribution.
  • Open-world Representation Learning (ORL): Moving beyond OOD detection, the ORL problem further requires models to learn the hidden classes within OOD samples, in addition to the known classes.
  • Interpretability: We aim to build an interpretable machine learning system, particularly in visualizing and quantitating the model’s inference mechanism or even constructing one inherently sparse, simulatable, modular, and thus, interpretable.

My current research revolves around the trustworthy Large Language Models (LLMs) on the following topics:

  • Retrieval-Augmented Generation (RAG), Multi-modality, Privacy, Uncertainty Estimation

See more in my CV and publications here!

(Latest update: 5/2/2024)


  • [5/1/2024] Two papers are acccepted to ICML 2024.
  • [3/13/2024] One paper is accepted to NAACL 2024.
  • [12/8/2023] One (co)first-authored paper is accepted to AAAI 2024.
  • [9/21/2023] Two papers are accepted to NeurIPS 2023. One is spotlighted.
  • [8/14/2023] Joined NEC Laboratories America Inc. as a full-time researcher.
  • [7/19/2023] Defended my thesis “Detecting and Learning Out-of-Distribution Data in the Open world: Algorithm and Theory”. Finally Dr. Sun!
  • [4/24/2023] One first-authored conference paper is accepted to ICML 2023.
  • [2/27/2023] One first-authored conference paper is accepted to CVPR 2023.
  • [1/4/2023] One first-authored journal paper is accepted to TMLR.