Ziming Liu 🚀
Ziming Liu 子铭刘

Ph.D. Candidate

National University of Singapore
Peking University

About Me

Hi, I am a third-year CS Ph.D. candidate at NUS, supervised by Prof. Yang You and work as a member of HPC-AI lab. I received my bachelor’s degree of computer science and engineering at Peking University in 2020, supervised by Prof. Tong Yang. I had the honor to receive the 2025 ByteDance Scholarship Award (20 among all CS PhDs in China and Singapore).

My research interests are machine learning systems and high performance computing. I have been working on various parallel techniques in large model training and inference, and I am also interested in the sparsity of deep learning models. I am looking forward to collaborations and research internship opportunities, so please feel free to contact me if you are interested in my research.

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Interests
  • Machine Learning System
  • High Performance Computing
  • Distributed Training & Inference
  • Sparse Inference & Training
Education

  • PhD Computer Science

    National University of Singapore

  • Msc Artificial Intelligence

    National University of Singapore

  • BSc Computer Science

    Peking University

Recent News

2025.11.21 Awarded the ByteDance Scholarship Award (20 among all CS PhDs in China and Singapore).

2025.11.11 One paper accepted by PPoPP '26.

2025.09.22 We release Expert-as-a-Service (EaaS) for MoE serving! Find the blog here.

2025.09.18 One paper accepted by NeurIPS '25.

2024.12.09 Release RAS for efficient DiTs. Code & paper: aka.ms/ras-dit

2024.12.09 Awarded the "Stars of Tomorrow" Certificate from MSRA (top 10% intern).

2024.11.12 One paper accepted by PPoPP 2025.

2024.10.03 One paper accepted by ASPLOS '25.

2024.06.27 Awarded the SoC Teaching Fellowship (3 out of all NUS CS PhD).

2024.02.16 One paper accepted by MLSYS 2024.

2024.01.15 One paper accepted by ICLR '24.

2023.06.17 One paper accepted by SC '23.

2023.01.07 Started my PhD career.

Experience

  1. Research Intern

    Qiji Zhifeng
    Working on large scale MoE model serving system. Paper just released!

  2. Research Intern

    Microsoft Research
    Working on sparse inference and training of text-to-image and text-to-video models. Supervised by Dr. Zhenhua Han and Dr. Yuqing Yang. Awarded the “Stars of Tomorrow” Certificate from MSRA (top 10% intern).

  3. Research Intern

    HPC-AI Tech

    Responsibilities include:

    • Developing the efficient LLM inference system EnergonAI.
    • Optimizing the implementation of ColossalAI.

  4. Machine Learning Engineer

    ByteDance
    NLP algorithm engineer at Lark, ByteDance.

Education

  1. PhD Computer Science

    National University of Singapore
    Working on Machine Learning System, supervised by Presidential Young Professor Yang You.

  2. Msc Artificial Intelligence

    National University of Singapore

  3. BSc Computer Science

    Peking University
    Bacholor’s degree of computer science and engineering. Supervised by Prof. Tong Yang.
Featured Publications
Expert-as-a-Service: Towards Efficient, Scalable, and Robust Large-scale MoE Serving
Region-Adaptive Sampling for Diffusion Transformers
WeiPipe: Weight Pipeline Parallelism for Communication-Effective Long-Context Large Model Training
StarTrail: Concentric Ring Sequence Parallelism for Efficient Near-Infinite-Context Transformer Model Training
Hanayo: Harnessing Wave-like Pipeline Parallelism for Enhanced Large Model Training Efficiency
Recent Publications
Geng Zhang, Shenggan Cheng, Xuanlei Zhao, Ziming Liu, Yang You (2025). HelixPipe: Efficient Distributed Training of Long Sequence Transformers with Attention Parallel Pipeline Parallelism. PPoPP 2026..
Cite Code
Ziming Liu, Boyu Tian, Guoteng Wang, Zhen Jiang, Peng Sun, Zhenhua Han, Tian Tang, Xiaohe Hu, Yanmin Jia, Yan Zhang, He Liu, Mingjun Zhang, Yiqi Zhang, Qiaoling Chen, Shenggan Cheng, Mingyu Gao, Yang You, Siyuan Feng (2025). Expert-as-a-Service: Towards Efficient, Scalable, and Robust Large-scale MoE Serving. Arxiv Preprint.
PDF Cite Poster
Ziming Liu, Yifan Yang, Chengruidong Zhang, Yiqi Zhang, Lili Qiu, Yang You, Yuqing Yang (2025). Region-Adaptive Sampling for Diffusion Transformers. Arxiv Preprint.
PDF Cite Code Project Poster
Junfeng Lin*, Ziming Liu*, Yang You, Jun Wang, Weihao Zhang, Rong Zhao (2024). WeiPipe: Weight Pipeline Parallelism for Communication-Effective Long-Context Large Model Training. PPoPP 2025. *:Equal Contribution.
Cite
Shenggan Cheng, Shengjie Lin, Lansong Diao, Hao Wu, Siyu Wang, Chang Si, Ziming Liu, Xuanlei Zhao, Jiangsu Du, Wei Lin, Yang You (2024). Concerto: Automatic Communication Optimization and Scheduling for Large-Scale Deep Learning. To appear on ASPLOS 2025.
Cite
Ziming Liu, Shaoyu Wang, Shenggan Cheng, Zhongkai Zhao, Kai Wang, Xuanlei Zhao, James Demmel, Yang You (2024). StarTrail: Concentric Ring Sequence Parallelism for Efficient Near-Infinite-Context Transformer Model Training. NeurIPS 2025.
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Xuanlei Zhao, Bin Jia, Haotian Zhou, Ziming Liu, Shenggan Cheng, Yang You (2024). HeteGen: Efficient Heterogeneous Parallel Inference for Large Language Models on Resource-Constrained Devices. In MLSys 2024, Proceedings of Machine Learning and Systems.
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Xuanlei Zhao, Shenggan Cheng, Guangyang Lu, Jiarui Fang, Haotian Zhou, Bin Jia, Ziming Liu, Yang You (2024). AutoChunk: Automated Activation Chunk for Memory-Efficient Long Sequence Inference. In ICLR 2024, International Conference on Learning Representations.
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Xuanlei Zhao, Shenggan Cheng, Zangwei Zheng, Zheming Yang, Ziming Liu, Yang You (2024). DSP: Dynamic Sequence Parallelism for Multi-Dimensional Transformers. Arxiv Preprint.
PDF Cite Project
Ziming Liu*, Shenggan Cheng*, Haotian Zhou, Yang You (2023). Hanayo: Harnessing Wave-like Pipeline Parallelism for Enhanced Large Model Training Efficiency. In SC ‘23, Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis. *:Equal Contribution.
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Shenggan Cheng, Ziming Liu, Jiangsu Du, Yang You (2023). ATP: Adaptive Tensor Parallelism for Foundation Models. Arxiv Preprint.
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Jiangsu Du, Ziming Liu, Jiarui Fang, Shenggui Li, Yongbin Li, Yutong Lu, Yang You (2022). EnergonAI: An Inference System for 10-100 Billion Parameter Transformer Models. Arxiv Preprint.
PDF Cite Project