Assistant Professor

Computer Science and Engineering

University of California, Santa Cruz


Office: E2-341A

About Me

I’m an Assistant Professor of Computer Science and Engineering at UC Santa Cruz. My research interests are crowdsourcing and algorithmic fairness, both in the context of machine learning. The central question associated with my work is learning from dynamic and noisy data.

Previously I was holding a postdoctoral fellow position at Harvard University. I have a Ph.D. from the University of Michigan, Ann Arbor and a B.Sc. from Shanghai Jiao Tong University, China.

My research is generously supported by the National Science Foundation (by their CORE, FAI, CAREER and TRIPOS programs), Office of Naval Research (Basic AI Research), Amazon, UC Santa Cruz and CROSS. I was partially supported by the DARPA SCORE program.


  • [REAL@UCSC] Our group’s research results are disseminated at

  • [Datasets] is online! We have also concluded the 1st Learning and Mining with Noisy Labels Challenge (LMNL). Congrats to the winning teams!

  • [Join us] I am looking for highly-motivated postdocs, phd students, visitors, and interns to work with us on weakly-supervised learning and algorithmic fairness. If you are interested, please email me at .


  • [2022.05] I joined Amazon Search Science and AI as an Amazon Visiting Academic. I am helping build the next-generation high-quality and budget-efficient human label platform for AI.

  • [2022.05] Serving NeurIPS 2022 as the Area Chair.

  • [2021.12] I’m serving FAccT 2022 and UAI 2022 as the Area Chair.

Recent papers

Recent awards

Invited talk