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. My research interests also span video streaming/conferencing/analytics, transport and congestion-control protocols, and other network systems and applications.

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. I am the creator of Puffer, a live-streaming site that has reached 150,000 real users (as of June 2021).

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 Yao) and a B.A. in economics. I also studied at MIT in 2014. Here is my CV.

I tweet research internship opportunities and bad jokes on Twitter.

Oct 2021
I am thrilled to serve on the award committee of the IRTF Applied Networking Research Prize 2022. Nominations are being accepted now until Nov 19, 2021. How to nominate?
Sept 2021
We have a research internship opening for an RL-in-videoconferencing project I have been leading. Due to some special arrangement of this collaborative project between MSR Redmond & Asia, applicants must physically be present in China and will work from MSR Asia. Update: The position has been filled.
May 2021
My colleague Mike Liang at MSR Asia and I are seeking a research intern to work with us on microservices. The internship is affiliated with MSR Asia and requires the intern to be physically located in Beijing. Female candidates are encouraged to apply! Update: We recruited a female intern!
Apr 2021
Glad to serve on the editorial board of the Journal of Systems Research (JSys). Looking forward to reading high-quality submissions to the networking area!
Apr 2021
You are invited to take on the Grand Challenge on Bandwidth Estimation for Real-Time Communications I am organizing. The prize pool is 7,500 USD! Submission deadline: June 25th July 19th, 2021.
Zhengxu Xia*, Yajie Zhou*, Francis Y. Yan, Junchen Jiang (*equal contribution)
In submission; draft available upon request.
arrow_right We proposed Genet, a novel training framework that enhances the generalization of reinforcement learning (RL) policies in systems and networking. In combining the latest RL generalization technique with judicious use of rule-based heuristics, Genet substantially improves the performance of simulation-trained RL policies under unseen workloads and in real environments.
Michael Rudow, Francis Y. Yan, Ganesh Ananthanarayanan, Martin Ellis, K.V. Rashmi
In submission; draft available upon request.
arrow_right We designed Tambur, a new approach to forward error correction (FEC) for videoconferencing built upon streaming codes and machine learning. Compared with the FEC scheme deployed in production by a commercial videoconferencing application, Tambur reduced decoding failures of video frames by 26% while employing 35% less bandwidth for redundancy.
Francis Y. Yan, Hudson Ayers, Chenzhi Zhu, Sadjad Fouladi, James Hong, Keyi Zhang, Philip Levis, Keith Winstein
USENIX Symposium on Networked Systems Design and Implementation (NSDI), February 2020
arrow_right We built Puffer, a free, publicly accessible website that live-streams television channels and operates as a randomized experiment of adaptive bitrate (ABR) algorithms. As of June 2020, Puffer has attracted 120,000 real users and streamed 60 years of video across the Internet. Using Puffer, we developed an ML-based ABR algorithm, Fugu, that robustly outperformed existing schemes by learning in situ, on real data from its actual deployment environment.
Francis Y. Yan, Jestin Ma, Greg D. Hill, Deepti Raghavan, Riad S. Wahby, Philip Levis, Keith Winstein
USENIX Annual Technical Conference (ATC), July 2018
arrow_right Pantheon is a “training ground” for congestion-control research and has assisted four schemes from other research groups in publishing at NSDI 2018 (Copa and Vivace), ICML 2019 (Aurora), and SIGCOMM 2020 (TCP-TACK). It also enabled our own ML-based congestion-control algorithm, Indigo, which was trained to imitate expert congestion-control algorithms we created in emulation and achieved good performance over the real Internet.
  • Applied Networking Research Prize (for Puffer), Internet Research Task Force (IRTF), 2021
  • USENIX NSDI Community Award (for Puffer), 2020
  • USENIX ATC Best Paper Award (for Pantheon), 2018
  • Award of Excellence, Stars of Tomorrow Internship Program, Microsoft Research, 2015
  • Outstanding Graduate of Tsinghua University, 2015
  • Outstanding Graduate of Beijing, China, 2015
  • National Scholarship, China, 2014
  • Silver Prize, Yao Award, Tsinghua University, 2014
  • Tsinghua University Comprehensive Scholarship, 2013
  • National Endeavor Fellowship, China, 2012
  • Tsinghua-Baidu Scholarship, 2012
  • Scholarship for Tsinghua Xuetang Talents Program, 2011–2014
  • First Prize, National Senior High School Mathematical Olympiad, China, 2010
  • First Prize, National Olympiad in Informatics in Provinces, China, 2008
  • Award Committee Member, IRTF Applied Networking Research Prize 2022
  • External Reviewer, NSDI 2022
  • Editorial Board Member, Journal of Systems Research (2021-2022)
  • Session Chair and Challenge Chair, ACM MMSys 2021
  • Organizer, Grand Challenge on Banwidth Estimation for Real-Time Communications, ACM MMSys 2021
  • Reviewer, IEEE/ACM Transactions on Networking (2019)
  • Reviewer, ACM SIGCOMM Computer Communication Review (2019)
  • Reviewer, Computer Communications (2019)