Francis Y. Yan
- Gates 286, 353 Serra Mall, Stanford, CA 94305
- fyy [at] cs.stanford.edu
- github.com/francisyyan
- Curriculum Vitae
ABOUT ME
I am a fifth-year computer science Ph.D. at Stanford University advised by Prof. Keith Winstein and Prof. Philip Levis, with a research focus on applying machine learning to improve networked systems.
My most recent research proposed a machine-learned video streaming algorithm that robustly outperforms existing schemes. For the purposes of training and evaluation, I built a live TV streaming website, Puffer (Community Award at NSDI '20), which currently has more than 100,000 users, and is covered by Wikipedia and many press articles. Previously, I received a USENIX ATC Best Paper Award for Pantheon.
In my spare time, I play table tennis at the Stanford Table Tennis Club.
EDUCATION
Stanford UniversityStanford, CA
Ph.D. in Computer Science
September 2015 - June 2020 (expected)
- Advised by Prof. Keith Winstein and Prof. Philip Levis
- Research interests: intersection of computer networks and machine learning
- Thesis: Machine learning improves stochastic control in video streaming and congestion control
- Dissertation committee: Keith Winstein, Philip Levis, Emma Brunskill, Percy Liang
Tsinghua UniversityBeijing, China
B.S. in Computer Science with Highest Distinction
August 2011 - July 2015
- Valedictorian of Yao Class (founded by Turing Award laureate Prof. Andrew Yao)
- Rank: 1st/39; GPA: 3.93/4.00
B.A. in Economics
August 2012 - July 2015
Massachusetts Institute of TechnologyCambridge, MA
Exchange Student in EECS Department
January - May 2014
- GPA: 5.0/5.0
PUBLICATIONS
- Francis Y. Yan, H. Ayers, C. Zhu, S. Fouladi, J. Hong, K. Zhang, P. Levis, K. Winstein, Learning in situ: a randomized experiment in video streaming, 17th USENIX Symposium on Networked Systems Design and Implementation (NSDI '20). Community Award (for the best paper whose code and/or data set is made publicly available). (website) (Wikipedia) (media coverage) (code)
- Francis Y. Yan, J. Ma, G. Hill, D. Raghavan, R. Wahby, P. Levis, K. Winstein, Pantheon: the training ground for Internet congestion control research, 2018 USENIX Annual Technical Conference (ATC '18). Best Paper Award. (website) (code)
- R. Jung, Francis Y. Yan, P. Levis, K. Jamieson, K. Balachandran, D. Hui, I. Maric, Desynchronized Timers as a Service, submitted to the 19th ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN '20).
- D. Yu, Y. Wang, Francis Y. Yan, J. Yu, F. Lau, Speedup of Information Exchange using Multiple Channels in Wireless Ad Hoc Networks, 34th Annual IEEE International Conference on Computer Communications (INFOCOM '15).
- Francis Y. Yan, S. He, Y. Liu, L. Huang, Optimizing Power Consumption of Mobile Games, 7th USENIX Conference on Power-Aware Computing and Systems (HotPower '15).
- Francis Y. Yan, D. Yu, Y. Wang, J. Yu, F. Lau, Bounded information dissemination in multi-channel wireless networks, Journal of Combinatorial Optimization, 2014.
WORK EXPERIENCE
Microsoft Research, Mobility and Networking Research GroupRedmond, WA
Research Intern mentored by Dr. Ganesh Ananthanarayanan and Dr. Yuanchao Shu
June - September 2019
- Ongoing research on video compression and streaming for computer vision tasks
Google, Congestion Control GroupMountain View, CA
Research Intern mentored by Dr. Yuchung Cheng
June - September 2016
- Added instrumentation to Linux kernel for TCP sender limits, measuring how long TCP is limited by the receive window or by an insufficient send buffer
- Commits accepted into Linux kernel since 4.10 (i.e., into Ubuntu since 17.04)
Microsoft Research, Wireless and Networking GroupBeijing, China
Research Intern mentored by Dr. Yunxin Liu
March - June 2015
- Implemented a dynamic frame rate scaling system for optimizing mobile power consumption
- Published a research paper and gave an oral presentation at HotPower '15
Baidu, Big Data LabBeijing, China
Research Intern on the team led by Prof. Tong Zhang
June - August 2015
- Implemented a high-performance multithreaded hash table
- Worked on optimization of a distributed deep learning framework
The University of Hong Kong, Computer Science DepartmentHong Kong
Research Assistant advised by Prof. Francis Lau
July - August 2014
- Designed randomized distributed algorithms for information dissemination in wireless ad hoc networks
- Published research papers at INFOCOM '15 and Journal of Combinatorial Optimization
TEACHING EXPERIENCE
Stanford University, Computer Science DepartmentStanford, CA
Course Assistant for CS140: Operating Systems
Winter & Spring 2019
Massachusetts Institute of Technology, EECS DepartmentCambridge, MA
Grader for 6.207/14.15: Networks
Spring 2014
ACTIVITIES
Professional Services
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Reviewer, IEEE/ACM Transactions on Networking2019 - Present
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Reviewer, ACM SIGCOMM Computer Communication Review2019 - Present
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Reviewer, Computer Communications2019 - Present
Chuang Plus (startup incubator of Tsinghua University)
2015
- Co-developed the homepage
Director, Tsinghua Student Associations Department
2015
Member, Tsinghua-Berkeley Global Technology Entrepreneurship Program
2014 - 2015
Social Practice
2013
- Investigated the community reconstruction of Taomi ecological village in Taiwan
- Won the Silver Prize of Tsinghua Student Social Practice 2013
HONORS AND AWARDS
- Community Award (out of 354 submissions), USENIX NSDI2020Best Paper Award (out of 378 submissions), USENIX ATC2018Award of Excellence, Stars of Tomorrow Internship Program, Microsoft Research2015Outstanding Graduate of Tsinghua University (lone recipient at my institution)2015Outstanding Graduate of Beijing, China2014National Scholarship, China2014Silver Prize, Yao Award, Tsinghua University2014Tsinghua University Comprehensive Scholarship2013National Endeavor Fellowship, China2012Tsinghua-Baidu Scholarship2012Scholarship for Tsinghua Xuetang Talents Program2011 - 2014First Prize, National Senior High School Mathematical Olympiad, China2010First Prize, National Olympiad in Informatics in Provinces, China2008
SKILLS
C, C++, Python, TensorFlow, PyTorch, Linux kernel (contributor), SQL, HTML, CSS, JavaScript, LaTeX