I am a Senior Researcher in the Mobility and Networking Research Group at Microsoft Research Redmond and the Office of the CTO, Azure for Operators. My research focuses on practical machine learning (ML) for networking, seeking to create ML algorithms that are deployable on real-world networked systems and build platforms for training and evaluating novel algorithms.
I completed my Ph.D. in computer science at Stanford University, advised by Keith Winstein and Philip Levis. My dissertation was on the development of platforms and algorithms to achieve practical reinforcement learning (RL) on the Internet, in the context of video streaming and congestion control. My work has received the Applied Networking Research Prize, the USENIX NSDI Community Award, and the USENIX ATC Best Paper Award.
Before that, I graduated from Tsinghua University, where I received a B.S. in computer science from Yao Class (founded by Turing Award laureate Andrew Chi-Chih Yao) and a B.A. in economics. I also studied at MIT in 2014. Here is my CV.
Prospective students: The internship positions of mine at MSR/Azure and MSRA have been filled, but please feel free to reach out if you are interested in joining a research project that applies ML/RL to systems and networking.