Professor Peter Garraghan
Professor in Distributed SystemsResearch Overview
Machine Learning systems, AI Security, Sustainable computing, Distributed Systems
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Profile
Peter Garraghan is a Professor in Distributed Systems, EPSRC Fellow, and CEO of Mindgard.
His research expertise is empirically studying and designing secure and sustainable systems at scale (AI/ML systems, Cloud datacentres, core network infrastructure). His research places strong emphasis on system experimentation within both laboratory and production environments.
Peter has published over 60 research articles, led software teams to create bleeding-edge technology, has industrial experience building large-scale production distributed systems, and has worked and collaborated internationally with the likes of Microsoft, Nvidia, BT, BBC, Alibaba Group, STFC, CONACYT, UK government, as well as the UK datacenter and defence industry.
He is the recipitent of the prestigious EPSRC Fellowship (2021 - 2026), and his research on AI/ML security and sustainable computing has featured in the media including the BBC and the Daily Mail.
Research Interests
- Distributed Systems, Deep Learning systems, Cloud datacenters
- AI/ML Security, Adversarial Machine Learning
- Sustainable & energy-efficient computing at scale
Qualifications
Ph.D. in Computer Science (University of Leeds, UK)
PhD Supervision Interests
I am happy to explore and supervise topics within distributed systems, AI/ML systems, AI security, and energy-aware computing. 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.
HTTP version 3 for unicast delivery of video services over the Internet
01/01/2023 → 31/03/2027
Research
DSI: Reducing the Global ICT Footprint via Self-adaptive Large-scale (DCMS Supplement)
01/12/2022 → 31/05/2023
Research
DSI:SL: The Security Gene: Discovering Embedded Commonalities within Adversarial Machine Learning
16/11/2022 → 31/03/2023
Research
PINCH: Cyber Security Threat Assessment for AI: phase 2
26/09/2022 → 28/02/2023
Research
MSI: Ultralow-power, Non-volatile, Random Access Memory Arrays for Data centers and Space Applications (ULTRARAM)
01/06/2022 → 31/12/2024
Research
SL: PINCH: An End-to-end Cyber Security Technology to Better Understand the Risks of Deep Learning Model Stealing
01/04/2022 → 31/07/2022
Research
ICASE: Sustainable Workload Scaling in Distributed Network Infrastructure (Matthew Hodkin)
01/10/2021 → 30/09/2025
Research
Reducing the Global ICT Footprint via Self-adaptive Large-scale ICT Systems
01/06/2021 → 31/05/2025
Research
Future Places: A Digital Economy Centre on Understanding Place Through Pervasive Computing
01/10/2020 → 30/09/2025
Research
Investigation of intelligent Controller for indirect Heaters on Gas Networks
01/06/2018 → 15/07/2018
Research
Pin the Tail: Understanding Straggler Manifestation in Internet-based Distributed Systems
01/09/2017 → 30/11/2019
Research
Security Lancaster (Secure Machine Learning and Intelligence), Security Lancaster (Systems Security)
Security Lancaster (Secure Machine Learning and Intelligence)
Security Lancaster (Distributed Systems), Security Lancaster (Systems Security)
Materials Science Institute PhD Student, MSF PhDs Cohort 2 (2019/20)
Security Lancaster (Secure Machine Learning and Intelligence)
- DSI - Foundations
- MSF Supervisors 2019/20
- SCC (Distributed Systems)
- Security Lancaster (Distributed Systems)
- Security Lancaster (Secure Machine Learning and Intelligence)
- Security Lancaster (Software Security)