Summary
Andrew Lee is a graduate student researcher at UC Davis specializing in the intersection of deep learning and robotics, with a focus on domain adaptation, representation learning, and generative models. With nine years of experience and a mechanical engineering foundation from Hanyang University, he combines strong systems intuition with advanced ML techniques to build robust, adaptable robotic systems. His current work at LARA develops ADAS solutions to enhance safety for emergency tow trucks and snowplows in low-visibility conditions, translating research into real-world operational impact. Pursuing an MS and PhD in Computer Science, he blends academic rigor with hands-on experimentation, often tackling long-tail perception problems that arise when models encounter unfamiliar environments.
9 years of coding experience
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at University of California, Davis
Bachelor of Science - BS, Mechanical Engineering, Bachelor of Science - BS, Mechanical Engineering at Hanyang University
English, Korean