Kai-wei Chang
Associate Professor
Los Angeles, California, United States
Summary
🤩
Rockstar🎓
Top SchoolKai-wei Chang is an associate professor of computer science at UCLA and a Sloan Fellow whose 12-year career bridges foundational research and practical systems in machine learning, NLP, and multimodal AI. He led pioneering work on Trustworthy NLP—advancing fairness, value alignment, and robustness in language models—and helped create early vision-language foundation models such as VisualBERT as well as state-of-the-art novel object recognition models like GLIP and DesCo. A prolific conference leader and editor, he has won multiple best paper awards (EMNLP, KDD, ACL) and serves in senior roles across NeurIPS, ICML, AAAI, ACL and more, while his research is funded by NSF, DARPA, NIH, IARPA, ONR and industry partners. In addition to academic leadership, he contributes to impactful open-source ML tooling—having worked on core extensions to Vowpal Wabbit—bringing a practical systems perspective to high-impact research. Based in Los Angeles, he combines deep theory with hands-on engineering and cross-sector collaboration, including ongoing ties with Amazon Alexa as an Amazon Scholar.
11 years of coding experience
7 years of employment as a software developer
M.S Computer Science and Information Engineering, M.S Computer Science and Information Engineering at National Taiwan UniversityDoctor of Philosophy (Ph.D.) Computer Science, Doctor of Philosophy (Ph.D.) Computer Science at University of Illinois Urbana-Champaign
Github Skills (7)
machine-learning10
c-language10
cprogramming-language10
elearning10
searching9
bandit8
active-learning7
Programming languages (6)
Github contributions (5)
VowpalWabbit/vowpal_wabbit
Jun 2014 - May 2016
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:106 commits, 8 PRs, 1 push in 1 year 11 months
Contributions summary:Kai-wei primarily contributed to implementing and enhancing the Vowpal Wabbit machine learning system, evidenced by modifications to its core codebase. Their work included adding support for multi-class tasks and integrating features like cost-to-go. These changes suggest involvement in both the back-end development of the system and the application of machine learning algorithms within the project.
hashingtechniquescpppythonactive-learning
KaiWeiChang/vowpal_wabbit
Jun 2014 - Oct 2015
Contributions:16 commits, 52 pushes, 11 branches in 1 year 4 months
wabbitmachine-learningonline-learningvowpal-wabbitlearning-algorithm
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