Wei-cheng Chang is a Research Scientist with 11 years of experience bridging academic rigor and production ML systems, currently at Google DeepMind and Google after a five-year applied scientist role at Amazon Search. He holds a Ph.D. in Computer Science from Carnegie Mellon University where he worked on large-scale embedding and retrieval methods and completed influential internships at Google and A9 focused on scalable deep learning for extreme multilabel classification. Wei-cheng blends research and engineering, shipping search and retrieval innovations in production environments while publishing at top venues like ICLR. Based in Bellevue, WA, he brings deep expertise in embedding-based retrieval and practical experience moving models from research prototypes into search systems. An early background with mentors like Yiming Yang and Chih-Jen Lin underscores his foundation in both theoretical and applied ML.
11 years of coding experience
11 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at National Taiwan University
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Carnegie Mellon University
Kernel Change-point Detection with Auxiliary Deep Generative Models (ICLR 2019 paper)
Contributions:15 commits, 2 PRs, 11 pushes in 8 months
pytorchiclrchange-pointkernelauxiliary
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Wei-cheng Chang - Research Scientist at Google DeepMind