Luo Mai

Luo Mai

Assistant Professor

University of Edinburgh

About Me

I am an Assistant Professor (Lecturer) in the School of Informatics at the University of Edinburgh. I am a member of the Institute of Computing Systems Architecture where I am leading the Large-Scale System Software Group.

In addition to my academic role, I co-found the Open Machine Learning System Community, serving as an educational platform that fosters the development of system software for machine learning. I have also contributed to the education of machine learning systems through my open-source textbook, Machine Learning Systems: Design and Implementation.

Before coming to Edinburgh, I was a research associate (2018 - 2020) at the Imperial College London working with Peter Pietzuch. I obtained my PhD from Imperial College London under the supervision of Paolo Costa and Alexander L. Wolf. My PhD was supported by a Google Fellowship in Cloud Computing. During my PhD study, I was a research intern (2015, 2016) and a visiting researcher (2017) at Microsoft Research.

05/2023: Fully-funded Ph.D. and Postdoc positions available. Contact me if interested.

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

  • BSc in Software Engineering, 2011

    Xidian University, China

News

TorchOpt and Gear to appear in NeurIPS and ICML

We have three papers to appear in leading machine learning conferences: “GEAR: A GPU-Centric Experience Replay System for Large Reinforcement Learning Models” to appear in ICML 2023. “A Theoretical Understanding of Gradient Bias in Meta-Reinforcement Learning” appeared in NeurIPS 2022.

MegBA in ECCV 2022

Our Paper “MegBA: A GPU-Based Distributed Library for Large-Scale Bundle Adjustment” is accepted by ECCV 2022.

Ekko in OSDI 2022

Our Paper “Ekko: A Large-Scale Deep Learning Recommender System with Low-Latency Model Update” is accepted by USENIX Symposium on Operating Systems Design and Implementation (OSDI) 2022. OSDI brings together professionals from academic and industrial backgrounds in what has become a premier forum for discussing the design, implementation, and implications of systems software.

Publications

(2023). GEAR: A GPU-Centric Experience Replay System for Large Reinforcement Learning Models. In ICML.

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(2023). Quiver: Supporting GPUs for Low-Latency, High-Throughput GNN Serving with Workload Awareness. In Arxiv.

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(2022). Ekko: A Large-Scale Deep Learning Recommender System with Low-Latency Model Update. In USENIX OSDI.

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(2022). A Theoretical Understanding of Gradient Bias in Meta-Reinforcement Learning. In NeurIPS.

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(2022). TorchOpt: An Efficient Library for Differentiable Optimization. In NeurIPS OPT Workshop.

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(2022). MegBA: A GPU-Based Distributed Library for Large-Scale Bundle Adjustment. In ECCV.

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(2021). Move Fast and Meet Deadlines: Fine-grained Real-time Stream Processing with Cameo. In USENIX NSDI.

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(2021). Efficient Reinforcement Learning Development with RLzoo. In ACM Multimedia (Open-source Software Competition).

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(2021). Fast and Flexible Human Pose Estimation with HyperPose. In ACM Multimedia (Open-source Software Competition).

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(2020). KungFu: Making Training in Distributed Machine Learning Adaptive. In USENIX OSDI.

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Software

MegBA

A GPU-Based Distributed Library for Large-Scale Bundle Adjustment. GitHub stars

TorchOpt

An efficient library for differentiable optimization built upon PyTorch. GitHub stars

Quiver

PyTorch Library for Low-Latency, High-Throughput Graph Learning on GPUs. GitHub stars

KungFu

Adaptive Large-scale Deep Learning GitHub stars

TensorLayer

Easy-to-use Deep Learning Library GitHub stars

HyperPose

Real-time Visual Computing Library GitHub stars

RLzoo

Reinforcement Learning Model Zoo GitHub stars

Group

Grad Students

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Yao Fu

PhD Student

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Man-Kit Sit

PhD Student

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Leyang Xue

PhD Student (Co-supervised with Mahesh)

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Congjie He

PhD Student

Teaching

Service and Awards

Research Awards

  • Chancellor Rising Star in Research (Nominated), 2023
  • Tencent Research Award, 2022
  • Alibaba Innovative Research Award, 2020
  • Microsoft Azure Research Award, 2018
  • ACM Multimedia Best Open-Source Software Award, 2017
  • Google PhD Fellowship in Cloud Computing, 2012 - 2016
  • ACM CoNEXT Conference Best Paper Finalist, 2014
  • IEEE MASS Conference Best Paper Finalist, 2012

Conference Committee Member

  • 2023: SoCC, APSys, Middleware, ICDE
  • 2022: ICDE, ANCS, MICRO (ERC)
  • 2021: ICDE

Journal Reviewer

  • ACM Transaction in Computer Systems
  • Nature Engineering Communication

Contact

  • luo.mai@ed.ac.uk
  • IF-2.03, Informatics Forum, University of Edinburgh, Edinburgh, EH8 9AB