Xinchen Yan is a Senior Research Scientist in San Francisco with 11 years of experience at the intersection of deep representation learning and generative modeling, currently leading data-driven sensor and perception simulation efforts at Waymo. He has a strong track record across industry research labs—Waymo, Uber ATG, Google Brain/X, and Adobe Research—and a Ph.D. in Machine Learning from the University of Michigan. His work spans controllable visual and 3D content generation, weakly-supervised shape and motion learning, and scalable perception simulation for robotics, with papers in CVPR, ECCV, CoRL and IROS. Xinchen has driven practical ML-based simulation systems (e.g., GeoSim) and neural-field approaches that bridge photorealistic rendering and robust multi-sensor perception. He combines deep theoretical expertise with production-focused research, often translating ideas into public papers and internal systems used for autonomous driving research.
11 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Machine Learning, Doctor of Philosophy (Ph.D.), Machine Learning at University of Michigan - Rackham Graduate School
Torch Implementation of NIPS'16 paper: Perspective Transformer Nets
Contributions:61 commits, 35 pushes, 18 comments in 4 years
deep-learningnips-20163d-graphicstorch7shapenet
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