Luo Mai

Assistant Professor

University of Edinburgh

About Me

I am an Assistant Professor in the School of Informatics at the University of Edinburgh, where I lead the Edinburgh Large-Scale Machine Learning Systems Group. Starting in 2024, I also co-lead the UK EPSRC Centre for Doctoral Training in Machine Learning Systems and an ARIA project focused on modeling and scaling AI systems.

My research interests lie at the intersection of computer systems, machine learning, and data management. My work has resulted in award-winning computer systems, recognized at top conferences such as OSDI, SOSP, NSDI, VLDB, JMLR, ICML, NeurIPS and ECCV. I have received awards from Google, Microsoft, Alibaba, and Tencent. I am the author of the open-source textbook Machine Learning Systems: Design and Implementation and co-founder of several popular open-source projects, such as TensorLayer, TorchOpt, and ServerlessLLM.

Before joining Edinburgh, I was a research associate at Imperial College London, working with Peter Pietzuch and a visiting researcher at Microsoft Research. My PhD, supervised by Paolo Costa and Alexander L. Wolf, was supported by a Google Fellowship in Cloud Computing.

If you’re interested in pursuing a PhD or postdoctoral research with me, please email your CV along with a brief description of your proposed research.

Interests

Computer Systems
Machine Learning
Data Management

Education

PhD in Computer Science, 2018

Imperial College London, UK
MRes in Advanced Computing, 2012

Imperial College London, UK

News

[10/24, Grant] Secured a prestigious ARIA grant with Imperial College & Cambridge University.

[10/24, Paper] Tenplex, the first elastic LLM system, accepted to SOSP 2024.

[07/24, Student Achievement] Congrats to Yao Fu on Winning 2024 Rising Star in ML & Systems.

[07/24, Paper] ServerlessLLM, the first serverless LLM system, accepted to OSDI 2024.

[05/24, Award] Win a Microsoft Research Startrack Scholar Award.

[03/24, Grant] Secured funds from EPSRC and industry partners to build a CDT for ML Systems.

[12/23, Paper & Award] TorchOpt is accepted by JMLR and becomes a PyTorch Ecosystem Project.

[10/23, Award] Finalist for the Chancellor's Rising Star in Research.

[09/23, Paper] GEAR, a new training system for bridging RL and LLMs, accepted to ICML 2023.

[07/22, Paper] Ekko, the first system unifying training and inference, accepted to OSDI 2022

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Publications

Marcel Wagenländer, Guo Li, Bo Zhao, Luo Mai, Peter Pietzuch (2024). Tenplex: Dynamic Parallelism for Deep Learning using Parallelizable Tensor Collections. In SOSP.

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Yao Fu, Leyang Xue, Yeqi Huang, Andrei-Octavian Brabete, Dmitrii Ustiugov, Yuvraj Patel, Luo Mai (2024). ServerlessLLM: Locality-Enhanced Serverless Inference for Large Language Models. In OSDI.

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Jie Ren*, Xidong Feng*, Bo Liu*, Xuehai Pan*, Yao Fu, Luo Mai, Yaodong Yang (2023). TorchOpt: An Efficient Library for Differentiable Optimization. In JMLR.

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Hanjing Wang*, Man-Kit Sit*, Congjie He, Ying Wen, Weinan Zhang, Jun Wang, Yaodong Yang, Luo Mai (2023). GEAR: A GPU-Centric Experience Replay System for Large Reinforcement Learning Models. In ICML.

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Chijun Sima*, Yao Fu*, Man-Kit Sit, Liyi Guo, Xuri Gong, Feng Lin, Junyu Wu, Yongsheng Li, Haidong Rong, Pierre-Louis Aublin, Luo Mai (2022). Ekko: A Large-Scale Deep Learning Recommender System with Low-Latency Model Update. In USENIX OSDI.

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Bo Liu, Xidong Feng, Jie Ren, Luo Mai, Rui Zhu, Haifeng Zhang, Jun Wang, Yaodong Yang (2022). A Theoretical Understanding of Gradient Bias in Meta-Reinforcement Learning. In NeurIPS.

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Jie Ren*, Wenteng Liang*, Ran Yan, Luo Mai, Shiwen Liu, Xiao Liu (2022). MegBA: A GPU-Based Distributed Library for Large-Scale Bundle Adjustment. In ECCV.

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Le Xu, Shivaram Venkataraman, Indranil Gupta, Luo Mai, Rahul Potharaju (2021). Move Fast and Meet Deadlines: Fine-grained Real-time Stream Processing with Cameo. In USENIX NSDI.

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Zihan Ding, Tianyang Yu, Yanhua Huang, Hongming Zhang, Guo Li, Quancheng Guo, Luo Mai, Hao Dong (2021). Efficient Reinforcement Learning Development with RLzoo. In ACM Multimedia (Open-source Software Competition).

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Yixiao Guo, Jiawei Liu, Guo Li, Luo Mai, Hao Dong (2021). Fast and Flexible Human Pose Estimation with HyperPose. In ACM Multimedia (Open-source Software Competition).

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