Michael Wan
Engineering at Applied Intuition
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolMichael Wan is an engineering professional and UC Berkeley EECS student focused on computer vision, optimization, robotics, and reinforcement learning, with a strong interest in autonomous vehicles. He currently develops autonomous systems software at Applied Intuition and has applied ML and control methods to real-world problems—from multi-agent RL for Google’s Core Crawl Scheduler to optimal UAV flight planning and radiation-detection payload integration in Berkeley’s Hybrid Systems Lab. His internships span production-focused tooling and research: anomaly detection on graph embeddings at Capital One, cloud automation and Kubernetes tooling at Keysight, and ML-driven malware detection at Zingbox. Early leadership founding a nonprofit tutoring organization and leading FIRST robotics vision and electrical teams shows he pairs technical depth with people-first project leadership. Notably, he has hands-on experience taking algorithms from research to autonomous hardware in complex environments like the Port of Oakland.
25 years of coding experience
5 years of employment as a software developer
Bachelor's degree, Electrical Engineering and Computer Science, Bachelor's degree, Electrical Engineering and Computer Science at UC Berkeley College of EngineeringMonta Vista High School
English, Chinese
Github Skills (7)
robotics8
computer-vision6
abstract-syntax-tree5
mercurial5
version-control4
git2
machine-learning1
Programming languages (4)
Github contributions (5)
FindMyClassmates/webapp
Jun 2017 - Jul 2018
Contributions:37 commits, 93 pushes in 1 year 1 month
valkyrierobotics/vision2017
Dec 2000 - Feb 2016
Valkyrie Robotics' computer vision code for the preseason, build season and offseason
Contributions:12 commits, 3 branches in 15 years 3 months
computer-visionrobotics
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