In the fall of 2020, I will join Microsoft Research Redmond as a Senior Researcher in the Mobility and Networking Research Group. 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 large-scale platforms opened to the research community for training and validating new algorithms. If you are excited about applying ML to systems and networking research, I will be happy to talk to you.
I completed my Ph.D. in computer science at Stanford University in 2020, advised by Keith Winstein and Philip Levis. My dissertation was on the development of platforms and algorithms to achieve practical machine learning for sequential decision problems on the Internet, with a focus on video streaming and congestion control. The two papers composing my dissertation received the Community Award at USENIX NSDI 2020 and the Best Paper Award at USENIX ATC 2018 respectively.
Before that, I graduated from Tsinghua University in 2015, 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 from the School of Economics and Management. In 2014, I spent a semester studying at MIT as an exchange student and took my first machine learning class there.
My current favorite sport is table tennis (skilled), but I also enjoy skiing (blue trail), ice/roller skating (intermediate), playing badminton (average) and tennis (beginner), swimming (novice), kayaking (amateur), etc. When I have no other choice, I'm fine with hiking too, preferably in scenic national parks though.