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 Chris Ré. I completed my PhD from Cornell University in 2017, where I was fortunate to be advised by John E. Hopcroft. I have received Facebook Research Award, JPMorgan early-career faculty award, and was named Forbes 30 Under 30 in Science. I am currently a faculty fellow at the Madison Teaching and Learning Excellence (MTLE) program.
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:
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.
3/4/2022: Received gift funding from Adobe Research.
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 (1.6%).
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 gift funding from Google Brain.
10/22/2021: We released a comprehensive survey on generalized OOD detection.
10/18/2021: Received gift funding from Facebook.
10/17/2021: Research is featured in Fueling Discovery by Wisconsin State Journal.
9/28/2021: Three papers on out-of-distribution detection accepted to NeurIPS 2021. Congrats to the team!
7/22/2021: Paper on frequency-domain image translation (FDIT) accepted to ICCV 2021.
7/15/2021: Received Madison Teaching and Learning Excellence Fellowship.
6/18/2021: Paper on outlier mining for out-of-distribution detection is accepted to ECML 2021.
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: Paper on KNN-based robustness accepted as an oral presentation at CVPR 2019.
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.