Baicen Xiao is a Machine Learning Engineer IV at Adobe and a final-year PhD in Electrical and Computer Engineering with eight years of experience building recommender systems, generative AI, computer vision, and reinforcement learning solutions. His work spans applied research and production: from reward shaping and human-in-the-loop RL during his PhD to deploying causal and recommendation models at scale at Adobe. He has driven measurable improvements in robust RL for autonomous driving in industry internships and published practical methods for adversarial and multi-agent settings. Based in Sunnyvale, he blends deep theoretical training in applied mathematics with hands-on engineering—often bridging research prototypes into REST APIs and time-series/recommender pipelines. Notably, he has shifted seamlessly between academic experiments on CNN semantics and production-grade generative AI features, signaling a strong track record of turning complex ML research into usable systems.
8 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD Electrical and Computer Engineering, Doctor of Philosophy - PhD Electrical and Computer Engineering at University of Washington
Bachelor’s Degree Electrical Electronics and Communications Engineering, Bachelor’s Degree Electrical Electronics and Communications Engineering at University of Electronic Science and Technology of China
Ph.D. studies Wireless Communication Coded modulation, Ph.D. studies Wireless Communication Coded modulation at Shanghai Jiao Tong University
Starter Code for the Course 2 project of the Udacity ML DevOps Nanodegree Program
Contributions:4 releases, 6 pushes, 4 tags in 1 day
pythonnanodegreeudacitydevopsmlops
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Baicen Xiao - Machine Learning Engineer 4 at Adobe