Feiyang

Wu Fei Yang, “woo-FAY-yahng” 🔊
ML PhD student at Georgia Tech

Linkedin | X | GitHub

My research interests lie in the intersection of optimization, reinforcement learning, and robotics. I develop algorithms to efficiently train robots, ideally with theoretical guarantee.

I am co-advised by Prof. Anqi Wu and Prof. Ye Zhao at Georgia Tech. Additionally, I had the privilege to collaborate with Prof. George Lan on stochastic optimization and RL.

Previously, I contributed to the development team of optimization solvers for large-scale linear programming problems at Chinese University of Hong Kong, Shenzhen (CUHKSZ), where I spent my undergrad years in computer science and engineering. I implemented and optimized the interior point method for linear programming, especially on the front of cholesky decomposition and matrix operations; for the primal/dual simplex method, I focused on the pivoting rules and the sparse linear algebra backend; additionally, I worked on several first-order methods for linear programming, such as primal-dual cutting plane methods and a C++ ported version of PDHG.

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Publication

Reinforcement Learning

Computer Vision