Luo Mai

Luo Mai

Assistant Professor

University of Edinburgh

About Me

I am an Assistant Professor (UK 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 AI Systems Group. My group aims to design and implement scalable and adaptive computer systems, with the current focus on enabling challenging machine learning and big data applications.

Before joining Edinburgh, I was a research associate (2018 - 2020) in the Large-scale Data & Systems Group at Imperial College London. I received my PhD from Imperial College London (advised by Paolo Costa) with the generous support of a Google Doctoral Fellowship in Cloud Computing. During my study, I visited Microsoft Research as a research intern (2015, 2016) and a visiting researcher (2017).

If you are interested in working with me as a Postdoc/PhD/MScR, please drop me an email with your CV.

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

Quiver is open-sourced

Quiver is a distributed graph learning library for PyTorch Geometric (PyG). Its excellent performance and scalablity 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.

Invited lecture at the Oxford ML sunmer school

I am honored to give a lecture about AI/ML systems at the prestigious Oxford Machine Learning Summer School. The school covers some of the most important topics in ML/DL that the field is showing a growing interest in (e.

Publications

(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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(2020). Spotnik: Designing Distributed Machine Learning for Transient Cloud Resources. In USENIX HotCloud.

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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

PhD 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