Short Biography:

Tyler Chang is a Founding Engineer at an AI Efficiency Startup in the San Francisco Bay Area, and an independent researcher in numerical optimization, scientific machine learning, and high-performance computing. Previously, he worked for two years as a research engineer in EDA, and for four years performed fundamental research at Argonne National Laboratory after earning his Ph.D. in Computer Science at Virginia Tech in 2020. He has published over 30 peer-reviewed research papers on multiobjective optimization, scientific machine learning, high-performance computing, numerical algorithms, and various applications thereof. He is also the lead developer and (co)maintainer of several open source projects.

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