Jifan Zhang

I am a Ph.D. candidate in computer science at the University of Wisconsin. My research focuses on both applied and theoretical perspectives of Machine Learning. I am working on label and data efficient methods for training large language/vision models with Robert D. Nowak. Check out LabelTrain.ai for highlights of Label-Efficient Learning research.

I obtained my M.S. and B.S. degrees in computer science from the University of Washington. During that time, I have been fortunate to be advised by Kevin Jamieson, Lalit Jain, Tanner Schmidt, Dieter Fox and Zachary Tatlock.

[Curriculum Vitae]           [Twitter]           [Google Scholar]       [Github]


  • Check out LabelTrain.ai for our effort on Label-Efficient Learning research including LabelBench, label-efficient SFT of LLMs, TAILOR and DIRECT.
  • My internship project (among two other projects) received an internal shoutout from Mark Zuckerburg at Meta.
  • Our paper “GALAXY: Graph-based Active Learning at the Extreme” has been accepted to ICML 2022. Check out the paper on arXiv.
  • I will be joining the University of Wisconsin, Madison as a Computer Science Ph.D. student! My Google search engine is very confused about the word “UW” now.

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