Connor Chen is a research scientist and MS candidate in Computer Science at UC Berkeley with nine years of hands-on experience building and researching AI systems across academia and industry. Currently splitting time between multimodal research at Mistral AI and training software-engineer agents at Berkeley RISE Lab, he specializes in bridging large-model capabilities with practical agent frameworks. His background includes internships and research stints focused on adaptive vision transformer patching, agent frameworks at Databricks, and fast-moving startup research at LMArena and Felicis. Connor combines strong theoretical foundations—teaching convex optimization—with applied engineering, shipping components of Mosaic AI Agent Framework during a Databricks internship. Based in Taipei but rooted in the Bay Area academic ecosystem, he brings a global perspective to multimodal and agent-oriented ML research. An under-the-radar strength is his knack for translating cutting-edge research into production-adjacent tooling that accelerates team experimentation.
9 years of coding experience
1 year of employment as a software developer
Master of Science - MS Computer Science, Master of Science - MS Computer Science at University of California, Berkeley
High School Diploma, High School Diploma at Irvington High School
Contributions:55 pushes, 2 branches, 1 tag in 2 years 7 months
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Connor Chen - Research Scientist at Berkeley RISE Lab