bio photo

Sharon Li

[CV]
Associate Professor
Department of Computer Sciences
University of Wisconsin-Madison
Office: Morgridge Hall 5510

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About


I am an Associate Professor in the Department of Computer Sciences at the University of Wisconsin-Madison. I am a member of machine learning@uw-madison and a faculty affiliate with the Data Science Institute. Previously, I was a postdoc researcher in the Computer Science department at Stanford University, working with Christopher Ré. I completed my PhD from Cornell University in 2017, where I was advised by John E. Hopcroft and worked closely with Kilian Q. Weinberger.


My research focuses on the foundations of reliable intelligence. We develop learning systems that can recognize the limits of their competence, reason under uncertainty, and make reliable decisions in the open world. Currently, we focus on reliable LLM and agentic systems, including diagnosing and improving long-horizon agent behavior, reasoning reliability, and hallucination detection. We also develop new post-training optimization and reinforcement learning approaches to shape model behavior toward designed outcomes. Ultimately, our goal is to develop AI systems whose behaviors can be rigorously understood and predicted, enabling principled control throughout the model lifecycle, from training to deployment.


My research has been recognized by the Alfred P. Sloan Fellowship (2025), MIT Innovators Under 35 Award (2023), NSF CAREER Award (2023), AFOSR Young Investigator (YIP) Award (2022), Forbes 30 Under 30 in Science (2020). I was named the "Innovator of the Year" by MIT Technology Review in 2023. Our research has received Outstanding Paper and Honorable Mention awards at NeurIPS and ICLR, as well as faculty research awards from Google, Meta, and Amazon. I also serve the broader machine learning community through conference leadership, most recently as Program Chair for ICML 2026.


[Openings]: My group has reached full capacity. I do not have current PhD/MS/undergrad/postdoc research openings, or for Fall 2027 cycle. You may read my [Advising Statement].



Recent/upcoming Talk

  • July 24: Cohere Lab
  • September 2: AI Agent Frontier Seminar
  • October 1-3: IFML AI Research Symposium ML towards Superintelligence
  • October 5-9: Simons Institute Workshop on Trustworthy AI: From Hallucinations to Reliable Autonomy
  • November: Language Technology Lab (LTL) Seminar at Cambridge University

    • Recent news


    7/2026: Progress Advantage won the best paper award at ICML RLxF Workshop!
    4/2026: Max received NSF Graduate Research Fellowship.
    4/2026: 8 papers accepted by ACL 2026.
    1/2026: 8 papers accepted by ICLR 2026.
    11/2025: We will organize Simons Institute Workshop on Agentic AI in the Wild: From Hallucinations to Reliable Autonomy.
    9/2025: 11 papers accepted by NeurIPS 2025. I am ranked among the top 25 researchers worldwide with the most accepted papers (and the only woman).
    7/2025: Promoted to associate professor with early tenure.
    7/1/2025: Received Google ML and Systems Faculty Award.
    6/15/2025: Shawn received the NSF Graduate Research Fellowship.
    5/16/2025: Xuefeng defended his Ph.D. thesis - congratulations Dr. Du!
    3/3/2025: Appointed as the Program Chair for ICML 2026 in Seoul, South Korea.
    2/18/2025: Honored to receive Alfred P. Sloan Fellowship.

    [Services]:

  • Program chair: ICML 2026
  • Area chair and senior program committee: NeurIPS, ICLR, ICML and AAAI.
  • Asscociate editor: ACM Transactions on Knowledge Discovery from Data (TKDD), Transactions on Machine Learning Research (TMLR)
  • Program chair and founding organizer: ICML Workshop on Uncertainty and Robustness in Deep Learning (UDL) 2019 & 2020.
  • Co-organizer: ICML Workshop on Uncertainty and Robustness in Deep Learning (UDL), 2021.
  • Co-organizer: ICML Workshop on Distribution-free Uncertainty Quantification (DFUQ), 2021.
  • Co-organizer: WiML Un-Workshop on Uncertainty Estimation, 2021.
  • Co-organizer: ICML Workshop on Distribution-free Uncertainty Quantification (DFUQ), 2022.
  • Co-organizer: NeurIPS Workshop on Robustness in Sequence Modeling, 2022.
  • Co-organizer: ICCV Tutorial on Reliability of Deep Learning for Real-World Deployment, 2023.
  • Co-organizer: CVPR Workshop on Prompting in Vision, 2024.
  • Co-organizer: DCAI: Data-centric Artificial Intelligence Workshop at WWW, 2024.
  • Co-organizer: ICLR Workshop on Quantify Uncertainty and Hallucination in Foundation Models: The Next Frontier in Reliable AI, 2025.
  • Co-organizer: ICLR Workshop on Advances in Financial AI: Opportunities, Innovations, and Responsible AI, 2025.
  • Co-organizer: ICLR Workshop on Agentic AI in the Wild: From Hallucinations to Reliable Autonomy, 2026.




    • [Teaching]:

  • Fall 2025: CS762 Advanced Deep Learning
  • Spring 2025: CS540 Introduction to Artificial Intelligence
  • Fall 2023: CS762 Advanced Deep Learning
  • Fall 2022: CS762 Advanced Deep Learning
  • Spring 2022: CS540 Introduction to Artificial Intelligence
  • Fall 2021: CS762 Advanced Deep Learning
  • Spring 2021: CS540 Introduction to Artificial Intelligence
  • Fall 2020: CS839 Advanced Topics in Deep Learning.


    • Misc
    I travel and occasionally take photos. Here is my pictorial Travel Memo. This is the treasure I shoot with.


    Sponsors We are thankful for the generous funding award and gift from the following sponsors: sponsor