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Kai Shen

Ph.D. Student
University of Toronto
kai (at) cs.toronto.edu


Short Bio

I am a second-year Ph.D. student in the Department of Electrical and Computer Engineering at University of Toronto, where I am co-supervised by Prof. Angela Demke Brown and Prof. Eyal de Lara as part of the Computer System & Networks Group. I received my B.Eng. degree with Honours, First Class from The Chinese University of Hong Kong, Shenzhen in 2022, majored in Computer Science and Engineering under the supervision of Prof. Fangxin Wang.

My research interests broadly lie at the intersection of systems and networking - with a current focus on building efficient memory management systems. From 2023 to early 2024, I developed packet-level, Transformer-based network performance estimators with scalability and generality, as well as a Rust-powered, process-based high-performance network simulator. Earlier, my work focused on server-driven adaptive realtime video streaming.

Research Interests

Publications

  1. TMC'24
    TrimStream: Adaptive Realtime Video Streaming through Intelligent Frame Retrospection in Adverse Network Conditions
    Dayou Zhang, Lai Wei, Kai Shen, Hao Zhu, Dan Wang, Fangxin Wang
    IEEE Transactions on Mobile Computing (TMC), 2024.
    PDF

  2. TMC'23
    DSJA: Distributed Server-Driven Joint Route Scheduling and Streaming Adaptation for Multi-Party Realtime Video Streaming
    Dayou Zhang, Hao Zhu, Kai Shen, Dan Wang, Fangxin Wang
    IEEE Transactions on Mobile Computing (TMC), 2023.
    PDF

  3. IEEE Network'23
    Learning-Based Network Performance Estimators: The Next Frontier for Network Simulation
    Kai Shen, Baochun Li
    IEEE Network, Special Issue on Interplay between Machine Learning and Networking Systems (IEEE Network), 2023.
    PDF

  4. INFOCOM'23
    SJA: Server-driven Joint Adaptation of Loss and Bitrate for Multi-Party Realtime Video Streaming
    Kai Shen, Dayou Zhang, Zi Zhu, Lei Zhang, Fangxin Wang, Dan Wang
    IEEE International Conference on Computer Communications (INFOCOM), 2023.
    PDF

  5. ICME'22
    Towards Joint Loss and Bitrate Adaption in Realtime Video Streaming
    Dayou Zhang*, Kai Shen*, Fangxin Wang, Dan Wang, Jiangchuan Liu (* Co-First Authors)
    IEEE International Conference on Multimedia and Expo (ICME), 2022.
    PDF

Services

Conference Reviewers

Journal Reviewers

Teaching

Teaching Assistant at The Chinese University of Hong Kong, Shenzhen

Teaching Assistant at University of Toronto

Awards

Contact

Address: 40 St George St, Toronto, ON M5S 2E4
Office Location: Bahen Centre for Information Technology 5214
Email: kai (at) cs.toronto.edu


Webpage credits