Yuqi Fu

I am a Ph.D. Candidate in the Computer Science Department at University of Virginia where I work with Dr. Yue Cheng and Dr. Songqing Chen

My research interests include the operating system and cloud computing. Specifically, Serverless computing enables a new way of building and scaling cloud applications by allowing developers to write fine-grained cloud functions. My current research focuses on designing effective scheduling algorithms on both per server’s operating system and distributed serverless cluster levels. The goal is to accelerate the overall performance of serverless clusters and minimize contention costs among users’ tasks.

Publications

  • The Decentralization Dilemma: Performance Trade-Offs in IPFS and Breakpoints (IMC’25)
    Ruizhe Shi,Yuqi Fu, Ruizhi Cheng, Bo Han, Yue Cheng, Songqing Chen

  • Centralization in the Decentralized Web: Challenges and Opportunities in IPFS Data Management (WWW’25)
    Ruizhe Shi, Ruizhi Cheng, Yuqi Fu, Bo Han, Yue Cheng, Songqing Chen

  • ALPS: An Adaptive Learning, Priority OS Scheduler for Serverless Functions (ATC’24)
    Yuqi Fu, Ruizhe Shi, Haoliang Wang, Songqing Chen, Yue Cheng
    paper | slide

  • SHADE: Enable Fundamental Cacheability for Distributed Deep Learning Training, 21th USENIX Conference on File and Storage Technologies (FAST’23)
    Redwan Ibne Seraj Khan, Ahmad Hossein Yazdani, Yuqi Fu, Arnab K. Paul, Bo Ji, Xun Jian, Yue Cheng, Ali R. Butt

  • SFS: Smart OS Scheduling for Serverless Functions, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC’22)
    🏆Best Student Paper Finalist
    Yuqi Fu, Li Liu, Haoliang Wang, Yue Cheng, Songqing Chen
    paper | slide

  • Speculative Container Scheduling for Deep Learning Applications in a Kubernetes Cluster, IEEE Systems Journal (ISJ’21)
    Ying Mao, Yuqi Fu, Wenjia Zheng, Long Cheng, Qingzhi Liu, Dingwen Tao

  • Progress Based Load Balancing for Containerized Deep Learning Applications, 2019 IEEE International Conference on Big Data (BigData’19)
    Yuqi Fu, Shaolun Zhang, Jose Terrero, Ying Mao, and Guangya Liu

Working Experience

  • 05/2023 - 08/2023, Research Intern, Adobe
  • 05/2022 - 08/2022, Research Intern, ByteDance
  • 04/2024 – 09/2024, Student Researcher, Google

Professional Services

External Review

  • FAST, 24th USENIX Conference on File and Storage Technologies, 2025
  • ATC, 2025 USENIX Annual Technical Conference, 2025
  • SoCC, ACM Symposium on Cloud Computing, 2024
  • HPDC, ACM International Symposium on High-Performance Parallel and Distributed Computing, 2024
  • HPDC, ACM International Symposium on High-Performance Parallel and Distributed Computing, 2023
  • NAS (storage track), IEEE International Conference on Networking, Architecture, and Storage, 2022
  • HPDC, ACM International Symposium on High-Performance Parallel and Distributed Computing, 2022
  • SEC, ACM/IEEE Symposium on Edge Computingm, 2022
  • ICDCS, 41st IEEE International Conference on Distributed Computing Systems, 2021
  • HPDC, ACM International Symposium on High-Performance Parallel and Distributed Computing, 2021

Student Volunteer

  • ICDCS, 41st IEEE International Conference on Distributed Computing Systems, 2021

Awards

  • Student Travel Grant, USENIX ATC 2024.
  • Student Travel Grant, USENIX FAST 2023

Contact