Luo Mai

Luo Mai

Assistant Professor

University of Edinburgh

About Me

I am an Assistant Professor 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 Software Systems Group. Our research group is interested in all aspects of scaling-up and scaling-out software systems.

Before coming to Edinburgh, I was a research associate (2018 - 2020) at the Imperial College London working with Peter Pietzuch. I received 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 with Microsoft Research as a research intern (2015, 2016) and a visiting researcher (2017).

I am always looking for self-motivated PhD and MScR students. Drop me an email with your CV if you are interested. I am a member of the supervisor teams in the CDT in NLP and the CDT in Biomedical AI. Check here for how to apply.

Interests

  • Computer Systems
  • Distributed Systems
  • Machine Learning
  • Data Management
  • Stream Processing

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

Ekko to appear at 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.

Quiver is open-sourced

Quiver is a distributed graph learning library for PyTorch Geometric (PyG). Its excellent performance and scalability has made it quickly become the recommended distributed library for PyG.

HyperPose and RLzoo in open-source software competition

HyperPose and RLzoo are both accepted to the Open-source Software Competition in ACM Multimedia 2021. ACM Multimedia is the worldwide premier conference and a key world event to display scientific achievements and innovative industrial products in the multimedia field.

Publications

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

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

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

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Software

Quiver

Fast and Easy Distributed Graph Learning for PyTorch 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

CrossBow

Deep Learning on Multi-GPU Servers GitHub stars

Group

Grad Students

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Zeyuan Tan

MScR Student

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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)

Visitors

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Xiulong Yuan

Visiting Student

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Jie Ren

Visiting Student

Alumni

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Jiawei Liu

Visiting Student

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Marcel Wagenlander

Visiting Student

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Guanqi Zhan

Visiting Student

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Ioan Budea

MEng Student

Contact

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