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Sharon Yixuan Li

Assistant Professor
Department of Computer Sciences
University of Wisconsin-Madison
Office: CS5393

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About


I am an Assistant Professor in the Department of Computer Sciences at the University of Wisconsin Madison. Previously I was as a postdoc researcher in the Computer Science department at Stanford University, working with the Hazy Group. I completed my PhD from Cornell University in 2017, where I was fortunate to be advised by John E. Hopcroft. My work is recognized by the AFOSR Young Investigator Award (2022), Forbes 30 Under 30 in Science (2020), and faculty research awards from Google, Meta, and Amazon.


My broad research interests are in deep learning, a branch of machine learning. My time in both academia and industry has shaped my view and approach in research. My research develops algorithms and fundamental understandings to enable reliable open-world learning, which can function safely and adaptively in the presence of evolving and unpredictable data stream. Research topics that I am currently focusing on include:

  • Learning and inference under distribution shift;
  • Open-world machine learning;
  • Human-aligned machine learning.

  • News


    12/14/2022: Grateful to receive the AFOSR Young Investigator Program (YIP) Award.
    11/21/2022: Our work received NeurIPS Outstanding Paper Award.
    11/19/2022: Soumya's paper on PG-DRO accepted to AAAI 2023 as oral presentation, congrats!
    11/11/2022: Excited to receive funding from Center for Advancing Safety of Machine Intelligence (CASMI), and partner on safe AI research.
    11/2022: Received Google-Initiated Research Grant.
    9/14/2022: 4 papers accpeted to NeurIPS 2022 and 1 paper accepted to NeurIPS 2022 Datasets and Benchmarks Track. Congrats to the team and co-authors!
    8/26/2022: Received Amazon Research Award.
    8/10/2022: Will serve as an area chair for ICLR 2023.
    7/7/2022: Will be co-organizing NeurIPS'22 workshop on Robustness in Sequence Modeling.
    6/8/2022: Received American Family Funding Intiative Award.
    5/15/2022: 4 papers accepted by ICML, congratulations to the team!
    4/15/2022: Received ICLR Outstanding Paper Award Honorable Mention.
    3/30/2022: Will serve as an area chair for NeurIPS 2022.
    3/21/2022: Will be co-organizing ICML'22 workshop on Distribution-free Uncertainty Quantification.
    3/1/2022: Paper on unknown-aware object detection accepted by CVPR 2022 as an oral presentation.
    1/20/2022: Two papers accepted by ICLR 2022, including one oral presentation.
    12/3/2021: Will serve as an area chair for ICML 2022.
    12/1/2021: Two papers on OOD detection accepted by AAAI 2022 as oral presentations.
    11/1/2021: Received Facebook Research Award.
    10/25/2021: Received Google-Initiated Focused Research Award.
    10/22/2021: We released a comprehensive survey on generalized OOD detection.
    10/17/2021: Research is featured in Wisconsin State Journal.
    9/28/2021: Three papers on out-of-distribution detection accepted to NeurIPS 2021. Congrats to the team!
    7/15/2021: Received Madison Teaching and Learning Excellence Fellowship.
    6/4/2021: Received JPMorgan Chase early career outstanding faculty award.
    6/2021: Received American Family Funding Intiative Awards.
    4/4/2021: Will be co-organizing two ICML'21 workshops on uncertainty quantification.
    2/28/2021: Two papers on OOD detection accepted to CVPR 2021 (including one oral presentation).
    1/12/2021: Paper on Model Patching (for handling subgroup shift) accepted to ICLR 2021.
    10/28/2020: Will serve as a mentor at the Women in Machine Learning (WiML) workshop at NeurIPS 2020.
    9/25/2020: Paper on Energy-based Out-of-distribution Detection accepted to NeurIPS 2020.
    8/17/2020: Joined the CS Department at UW-Madison as an Assistant Professor. Here is a featured interview article.
    05/19/2020: Gave an invited talk on Out-of-distribution Uncertainty Estimation and Robustness in Open-World Machine Learning at Air Force Research Laboratory’s Workshop.
    4/23/2020: Selected Young Researcher to participate in the 8th Heidelberg Laureate Forum.
    3/14/2020: Will serve as Program Chair for ICML'20 workshop on Uncertainty and Robustness in Deep Learning.
    12/3/2019: My talk is listed as one of 30 Influential AI Presentations in 2019.
    12/3/2019: Honored and thrilled to be featured in Forbes 30 Under 30 list in Science.
    3/8/2019: Honored to be featured in 30 Under 30 Leading Women in AI.
    2/24/2019: Will serve as Program Chair for ICML'19 workshop on Uncertainty and Robustness in Deep Learning.
    1/2019: Gave a talk at Deep Learning Summit San Francisco .

    [Openings]: I am looking for highly motivated Ph.D. and M.S. students to join my lab. The admission decision at UW-Madison is committee-based. For questions regarding the application process, please read the FAQ.



    [Services]:

  • Program chair: ICML Workshop on Uncertainty and Robustness in Deep Learning (UDL) 2019 & 2020.
  • Area chair and senior program committee: NeurIPS, ICLR, ICML and AAAI.
  • 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: ICML Workshop on Distribution-free Uncertainty Quantification (DFUQ), 2022.
  • Co-organizer: NeurIPS Workshop on Robustness in Sequence Modeling, 2022.

  • [Recent/upcoming talks]:

  • 6/18/2023: Invited talk at CVPR'23 Workshop on Anomaly Detection.
  • 4/20/2023: Invited talk at Rivian Data Science Seminar.
  • 4/14/2023: Invited talk at Computer Vision Round Table (CVRT) at UW-Madison.
  • 2/10/2023: Invited talk at Cornell AI Seminar.
  • 2/7/2023: Talk at Machine Learning Lunch Meeting (MLLM) at UW-Madison.
  • 2/2/2023: Invited talk at American Family Insurance.
  • 1/27/2023: Invited talk at Wisconsin Science and Computing Emerging Research Stars (WISCERS) Workshop.
  • 12/14/2022: Invited guest lecture at NYU.
  • 12/8/2022: Invited talk at National Institute of Standards and Technology (NIST).
  • 12/2022: Invited talk at NeurIPS'22 Workshop on ML Safety.
  • 10/2022: Invited talk at ECCV workshop on uncertainty quantification for computer vision (UNCV)
  • 10/2022: Invited talk at ECCV workshop on Learning from Limited and Imperfect Data (L2ID)
  • 10/5/2022: Invited talk at TrustML Young Scientist Seminar
  • 10/3/2022: Invited talk at OSU CSE AI Seminar.
  • 9/2022: Invited talk at SIAM Conference on Mathematics of Data Science
  • 8/2022: Invited talk at Future of Data-Centric AI Event
  • 7/2022: Invited talk at ICML'22 DataPerf Workshop
  • 3/2022: Invited talk at UT-Austin
  • 3/9/2022: AI Seminar at Oregon State University
  • 2/10/2022: Anomaly Detection for Scientific Discovery (AD4SD) Seminar [Recording]
  • 12/2021: NeurIPS'21 workshop on ImageNet: past, present, and future
  • 12/1/2021: PhysicsMeetsML seminar
  • 9/28/2021: Future of Data-Centric AI virtual event
  • 8/27/2021: Talk at Facebook
  • 8/21/2021: Keynote @ Artificial Intelligence for Anomalies and Novelties (AI4AN 2021)
  • 8/22/2021: Keynote @ Weakly-supervised Representation Learning (WSRL 2021 workshop)
  • 8/2/2021: IFDS workshop on Statistical Approaches to Understanding Modern ML Methods
  • 4/27/2021: MINDS & CIS Seminar at John Hopkins University
  • 4/17/2021: Women in Scientific Education and Research (WISER) at UW-Madison
  • 4/1/2021: Open Data Science Conference (ODSC) East 2021
  • 11/4/2020: Women in Computer Science (WiCS) Seminar at Stanford
  • 10/30/2020: Information Systems Seminar at UC Berkeley
  • 10/28/2020: SILO Seminar at UW-Madison.
  • 9/21/2020: MLOS Seminar at UW-Madison+Microsoft.


  • [Teaching]:

  • 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.