Guoliang He

Guoliang He

PhD Student @ Department of Computer Science, University of Cambridge

About me

I am a final year PhD Student in the system research group at the Department of Computer Science and Technology, University of Cambridge. My research focuses on RL-driven performance optimization, and recently works on LLM systems for efficient training and inference.

I have worked at Cohere, Bytedance Seed and Shanghai AI Lab for efficient LLM training and serving systems.

I have also contributed to open-source projects such as Pytorch and Triton. For more information, see my Project page.


Latest publications

(* denotes equal contributions)

LLM Systems, Training and Serving

  • Efficient Pre-Training of LLMs via Topology-Aware Communication Alignment on More Than 9600 GPUs
    ICML 2025, Efficient Systems for Foundation Models workshop
    G. He*, Y. Jiang*, W. Xiao, K. Jiang, S. Wang, J. Wang, Z. Du, Z. Jiang, X. Zhang, B. Yuan, E. Yoneki

  • Demystifying Cost-Efficiency in LLM Serving over Heterogeneous GPUs
    ICML 2025
    Y. Jiang*, F. Fu*, X. Yao*, G. He*, X. Miao, A. Klimovic, B. Cui, B. Yuan, E. Yoneki

  • vPALs: Towards Verified Performance-aware Learning System For Resource Management
    AAAI 2024, deployable AI workshop
    G. He, G. Yeung, S. Ceesay, and A. Barker


RL-Driven Performance Optimization

  • CuAsmRL: Optimizing GPU SASS Schedules via Deep Reinforcement Learning
    CGO 2025
    G. He, E. Yoneki

  • SIP: Autotuning GPU Native Schedules via Stochastic Instruction Perturbation
    EuroSys 2024, EuroMLSys workshop
    G. He, E. Yoneki

  • Optimizing Tensor Computation Graphs with Equality Saturation and Monte Carlo Tree Search
    PACT 2024
    J. Hartmann, G. He and E. Yoneki

  • X-RLflow: Graph Reinforcement Learning for Neural Network Subgraph Transformation
    MLSys 2023
    G. He, S. Parker, and E. Yoneki

  • MCTS-GEB: Monte Carlo Tree Search is a Good E-graph Builder
    EuroSys 2023, EuroMLSys workshop
    G. He, Z. Singh, and E. Yoneki


Biography

  • 2021 - 2025 : Studied PhD degree at the University of Cambridge.

  • 2020 - 2021 : Worked as a software engineer in cloud infrastructure.

  • 2019 - 2020 : Receive my M.Sc. degree in Machine Learning from University College London.

  • 2015 - 2019 : Receive my B.Eng. degree from University of Edinburgh and South China University of Technology.