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Peter Garraghan supervises 7 postgraduate research students. If these students have produced research profiles, these are listed below:

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Dr Peter Garraghan

Lecturer in Distributed Systems

Peter Garraghan

InfoLab21

LA1 4WA

Lancaster

Tel: +44 1524 510306

Research overview

Distributed systems, green computing, Machine Learning systems, systems security, resource schedulers.

(Jan 2021): I am hiring! I have multiple funded positions commencing this year:

  • PhD students: Sustainable ML systems, energy-adaptive network infrastructure (All include fully covered UK-level home tuition fees + stipend.)
  • Postdocs: Sustainable computing at scale, energy-aware ML training & compilation, secure ML systems.

if you have experience/have strong interest in experimental systems research, kindly contact me via email to discuss further.

PhD supervision

I am happy to explore and supervise topics within distributed systems, machine learning systems, cloud computing, energy, resource scheduling, security, and dependability research. If you have your own ideas for a research project you would like to pursue, feel free to contact me to discuss further. I currently have multiple fully funded positions open.

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Profile

Peter Garraghan is a Lecturer (Assistant Professor) and EPSRC Fellow in Distributed Systems. His research expertise is empirically studying and and designing high performance, resilient, and sustainable distributed systems at scale (Cloud computing, Machine Learning systems, Datacentres, core network infrastructure) in the face of societal and environmental change. His research places strong emphasis on conducting analysis, design, and evaluation via experimentation on systems both in laboratory and production.

Peter has published over 50 articles, has industrial experience building large-scale production distributed systems, and has worked and collaborated internationally with the likes of Alibaba Group, Microsoft, BT, STFC, CONACYT, and the UK datacenter and IoT industry.

He is the recipitent of the prestigious EPSRC Early-career Fellowship (2021 - 2025), and his research on sustainable computing and future AI systems has featured in the media including the BBC and the Daily Mail.

Research Interests

  • Distributed Systems, Machine Learning systems, Cloud datacenters
  • Energy-efficient & sustainable computing at scale
  • CPU & GPU cluster resource management
  • Systems security & resiliency

Qualifications

Ph.D. in Computer Science (University of Leeds, UK)

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