Hi, there! I’m Jack. I’m an M.S. student in Computer Science at UIUC, where I’m fully devoted to autonomous intelligence. I work on this problem upon two levels:
- I study representation learning for foundation models in order to interpret their behaviors.
- I study reinforcement learning algorithms for foudation models based on the so-derived understandings.
I’m also slightly involved in data augmentation to enhance intelligence.
Bio: Jack Bai is an M.S. student in Computer Science at UIUC, advised by Prof. Nan Jiang and Heng Ji, and a visiting scholar at BAIR, advised by Prof. Sergey Levine and Yi Ma. Before master’s, he obtained a dual degree from Zhejiang University and UIUC in Computer Engineering. During those wonderful years, he interned at Microsoft Research advised by Dr. Shilin He, and participated in the Amazon SocialBot Challenge advised by Prof. Chengxiang Zhai.
- Representation Learning
- Reinforcement Learning
MS in Computer Science, 2025
University of Illinois, Urbana Champaign
BS in Computer Engineering, 2023
University of Illinois, Urbana-Champaign
Quotes
We have to learn the bitter lesson that building in how we think we think does not work in the long run. The two methods that seem to scale arbitrarily … are learning and search. Learning is to use data to extract patterns, and search is the optimization procedure that uses computation to make rational decisions.
– Richard Sutton, The Bitter Lesson, 2019
Data without optimization doesn’t allow to solve new problems in new ways; optimization without data is hard to apply to the real world outside of simulators.
– Sergey Levine, RL with Large Datasets, 2023
Collaboration
- Only referred collaboration from UC Berkeley will be considered (updated SP24)
Core Publications
The publications are not complete. Some work are protected and some work are still in the publication process.
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