Kevin Tan
Machine Learning Engineer at DoorDash
Los Angeles, California, United States
Summary
👤
Senior🎓
Top SchoolKevin Tan is a machine learning engineer with 10 years of experience applying research-grade ML to real-world systems across autonomous driving, e-commerce, logistics, and neuroscience. He blends academic depth—MS from Stanford and PhD-level neuroscience work exploring the brain's default network with intracranial EEG, scalp EEG and fMRI—with production ML at companies like DiDi, TikTok, and DoorDash, shipping models for motion planning, time-series forecasting, and large-scale recommendation/fulfillment pipelines. He has a strong foundation in generative vision and spatiotemporal modeling from Stanford and UCSD research, and a history of improving training pipeline efficiency and handling long-tail, out-of-distribution scenarios. Comfortable moving between research and engineering, Kevin has delivered novel algorithms, built scalable ML infrastructure, and public research artifacts (e.g., stacked-LSTM video prediction work) that bridge neuroscience and applied ML.
9 years of coding experience
6 years of employment as a software developer
University of California, San DiegoIB Diploma, IB Diploma at International School of BeijingMaster of Science - MS Symbolic Systems Artificial Intelligence, Master of Science - MS Symbolic Systems Artificial Intelligence at Stanford University
English, Chinese
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (1)
linux1
Programming languages (3)
Github contributions (5)
scanUCLA/spm12-dartel
Jun 2017 - Oct 2017
Contributions:25 commits, 4 PRs, 23 pushes in 3 months
kevmtan/kevmtan.github.io
Nov 2017 - Dec 2023
Contributions:152 pushes in 6 years 2 months
templategithub-pages-templatemmistakesmistakesjekyll
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