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Qifan (Eric) Yan
Computer Science Masters Student, University of Waterloo
qfyan[at]uwaterloo.ca

Hi there 👋

My name is Eric or Qifan Yan (闫启帆). I am a master’s student under the supervision of Dr. Raouf Boutaba at the University of Waterloo. I am broadly interested in distributed systems, networking, and machine learning (specifically federated learning). Previously, I completed my undergraduate honors thesis with Dr. Ivan Beschastnikh at the University of British Columbia (UBC)’s Systopia Lab. We explored cool ways of addressing the communication bottleneck in cross-device federated learning with techniques like update compression, client sampling, and scheduling. Furthermore, I have industry experience at Amazon, SAP, and Deloitte, where I worked on software and business development projects. Ultimately, I want to design and build novel systems to make machine learning more accessible to the public.

Outside of computer science, I graduated from UBC’s Master of Management Dual Degree Program, where I got to take some eye-opening business courses and interact with many interesting people in other fields. I also love experiencing the outdoors and trying new strategy/simulation/RPG games. A recent hike I enjoyed tremendously is Stawamus Chief in Squamish, BC, Canada. A recent game I had a lot of fun with is Unicorn Overlord.

Feel free to contact me if you are interested in chatting!

Interests

  • Distributed Systems
  • Networking
  • Systems and Machine Learning
  • Federated Learning

Education

University of Waterloo
2024 - present
Master of Mathematics Compute Science
Supervised by Dr. Raouf Boutaba
University of British Columbia
2018 - 2023
B.Sc. Honours Computer Science, Software Engineering Option
Supervised by Dr. Ivan Beschastnikh, top 5%, co-op program
University of British Columbia, Sauder School of Business
2018 - 2023
Master of Management
Dual degree program for undergraduates at UBC

News

Recent Publications

FedFetch: Faster Federated Learning with Adaptive Downstream Prefetching, 2024, INFOCOM 2025
Qifan Yan , Andrew Liu , Shiqi He , Mathias Lecuyer , Ivan Beschastnikh
GlueFL: Reconciling Client Sampling and Model Masking for Bandwidth Efficient Federated Learning, 2023, MLSys 2023
Shiqi He , Qifan Yan , Feijie Wu , Lanjun Wang , Mathias Lecuyer , Ivan Beschastnikh