Tianzhe Chu is a PhD student and researcher based in Berkeley, specializing in theory and practice of deep learning with a current focus on understanding, evaluating, and improving multimodal large language models. With three years of research experience working with Prof. Yi Ma at both UC Berkeley’s BAIR lab and The University of Hong Kong, he blends rigorous theoretical grounding with hands-on experimentation in representation learning and explainable AI. He holds a BE in Computer Science from ShanghaiTech and spent time as a visiting student in UC Berkeley’s EECS program, giving him strong cross-institutional research exposure. Known for combining mathematical insight with practical model evaluation, Tianzhe is building tools and methods that make multimodal model behavior more interpretable and reliable.
3 years of coding experience
2 years of employment as a software developer
Bachelor of Engineering - BE, Computer Science, Bachelor of Engineering - BE, Computer Science at ShanghaiTech University
Visiting Student, EECS, Visiting Student, EECS at University of California, Berkeley
Contributions:13 pushes, 3 comments, 1 issue in 9 months
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