Hi, my name is Zizhao Mo (莫梓钊). I received my Ph.D. degree in Computer Science from the University of Macau, where I was fortunate to be advised by Prof. Huanle Xu at Cloud and Distributed Systems Lab.
My research interests broadly revolve around machine learning systems (MLSys), focusing on scheduling, parallelization optimization, and resource management topics. The optimization goal of my research lies in the efficiency improvement for ML workloads, in terms of latency, cost, and throughput. I also have a specific interest in designing efficient systems over heterogeneous resources, including CPU-GPU and heterogeneous GPU platforms.
My research projects:
- Resource allocation in GPU clusters. Designing fine-grained scheduling policies in the (heterogeneous) GPU cluster to optimize the performance and resource efficiency for deep learning training jobs.
- LLM inference optimization. Proposing optimization techniques for the LLM inference service, primarily focusing on the improvement of system-level metrics like throughput and latency.
I am currently on the job market and seeking opportunities from academia. Please feel free to contact me!
🔥 News
- 2025.06: 🎉🎉 I defense my Ph.D. thesis!
📝 Publications
Hetis: Serving LLMs in Heterogeneous GPU Clusters with Fine-grained and Dynamic Parallelism
- Accepted by SC’ 25 (CCF-A, CSRanking), Top conference in supercomputing.
- Authors: Zizhao Mo, Jianxiong Liao, Huanle Xu, Zhi Zhou, Cheng-Zhong Xu
Fast and Fair Training for Deep Learning in Heterogeneous GPU Clusters
- Accepted by ICS’ 25 (CCF-B, CSRanking), Top conference in supercomputing.
- Authors: Zizhao Mo, Huanle Xu, Wing Cheong Lau
Heet: Accelerating Elastic Training in Heterogeneous Deep Learning Clusters
- Accepted by ASPLOS’ 24 (CCF-A, CSRanking), Top conference in system architecture.
- Authors: Zizhao Mo, Huanle Xu, Cheng-Zhong Xu
Optimal Resource Efficiency with Fairness in Heterogeneous GPU Clusters
- Accepted by Middleware’ 24 (CCF-B).
- Authors: Zizhao Mo, Huanle Xu, Wing Cheong Lau
Derm: SLA-aware Resource Management for Highly Dynamic Microservices
- Accepted by ISCA’ 24 (CCF-A, CSRanking), Top conference in system architecture.
- Authors: Liao Chen, Shutian Luo, Chenyu Lin, Zizhao Mo, Huanle Xu, Kejiang Ye, Cheng-Zhong Xu
Interference-aware Multiplexing for Deep Learning in GPU Clusters A Middleware Approach
- Accepted by SC’ 23 (CCF-A, CSRanking), Top conference in supercomputing.
- Authors: Wenyan Chen, Zizhao Mo, Huanle Xu, Kejiang Ye, Cheng-Zhong Xu
🎖 Honors and Awards
- 2021 - 2025: Ph.D. Scholarship. University of Macau.
- 2024: Travel grant for ASPLOS’24.
- 2021: Arthur and Louis May Scholarship. Hong Kong University of Science and Technology.
🔖 Academic Activities
Reviewers:
- IEEE Transactions on Computers
- IEEE Transactions on Consumer Electronics
- Journal of Systems Architecture
📖 Educations
- 2021 - 2025: Ph.D. in Computer Science, University of Macau.
- 2020 - 2021: MSc in Information Technology, Hong Kong University of Science and Technology.
- 2014 - 2018: B.Eng. in Software Engineering, South China University of Technology.