Prof Blesson Varghese
Professor
Biography
Blesson Varghese is Professor in the School of Computer Science at the University of St Andrews. He directs the Edge Computing Hub funded by Rakuten, Japan, and leads research on the UKRI-funded Edge AI Hub.
He was the recipient of the 2021 IEEE Rising Star Award and a Royal Society industry fellowship to British Telecoms plc, UK. His research interests are in developing large-scale distributed systems spanning the cloud and the edge of the network and has academic, industry and consulting experience in multiple continents.
He has featured in 'Clouded', a documentary on the cloud produced by Hewlett Packard and VMWare, and has interviewed on broadcast media.
Find more information on his personal homepage or Google Scholar profile.
Teaching
I teach CS5052: Data-Intensive Systems and CS5939: Data-Driven Systems, both of which focus on the design of large-scale distributed systems spanning the cloud and the edge.
I also supervise undergraduate and postgraduate projects.
Research areas
My research focuses on addressing challenges in developing large-scale distributed systems, specifically those encompassing the cloud and the edge of the network. My current interests are in Edge AI systems. methods and architectures.
PhD supervision
- Jiawei Luo
- Dhananjay Saikumar
Selected publications
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Open access
FedFreeze: a dual-phase layer freezing framework for federated learning
Wu, D., Wong, L. & Varghese, B., Apr 2026, In: Future Generation Computer Systems. 177, p. 1-14 14 p., 108250.Research output: Contribution to journal › Article › peer-review
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Open access
FedOptima: optimizing resource utilization in federated learning
Zhang, Z., Wong, L. & Varghese, B., 1 Oct 2026, In: Future Generation Computer Systems. 183, 15 p., 108551.Research output: Contribution to journal › Article › peer-review
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Open access
Mosaic: composite projection pruning for resource-efficient LLMs
Eccles, B. J., Wong, L. & Varghese, B., Feb 2026, In: Future Generation Computer Systems. 175, p. 1-15 15 p., 108056.Research output: Contribution to journal › Article › peer-review
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EMO: Edge Model Overlays to scale model size in federated learning
Wu, D., He, W., Feng, W., Wen, Z., Qian, B. & Varghese, B., 21 Jul 2025, p. 1-6. 6 p.Research output: Contribution to conference › Poster › peer-review
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Open access
InferEdge: characterizing edge inference performance
Antar, G. O. K. & Varghese, B., 31 Dec 2025, Proceedings of the IEEE/ACM international conference on utility and cloud computing (UCC 2025). New York: ACM, 10 p. 2Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Open access
DNNShifter: an efficient DNN pruning system for edge computing
Eccles, B. J., Rodgers, P., Kilpatrick, P., Spence, I. & Varghese, B., Mar 2024, In: Future Generation Computer Systems. 152, p. 43-54Research output: Contribution to journal › Article › peer-review
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Open access
EcoFed: efficient communication for DNN partitioning-based federated learning
Wu, D., Ullah, R., Rodgers, P., Kilpatrick, P., Spence, I. & Varghese, B., 4 Jan 2024, In: IEEE Transactions on Parallel and Distributed Systems. Early Access, 13 p., 10380682.Research output: Contribution to journal › Article › peer-review
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Open access
Enabling privacy-aware interoperable and quality IoT data sharing with context
Chhetri, T. R., Dehury, C. K., Varghese, B., Fensel, A., Srirama, S. N. & DeLong, R. J., Aug 2024, In: Future Generation Computer Systems. 157, p. 164-179Research output: Contribution to journal › Article › peer-review
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Open access
NeuroFlux: memory-efficient CNN training using adaptive local learning
Saikumar, D. & Varghese, B., Apr 2024, EuroSys '24: Proceedings of the Nineteenth European Conference on Computer Systems. ACM, p. 999-1015 17 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Open access
PiPar: Pipeline parallelism for collaborative machine Learning
Zhang, Z., Rodgers, P., Kilpatrick, P., Spence, I. & Varghese, B., Nov 2024, In: Journal of Parallel and Distributed Computing. 193, 17 p., 104947.Research output: Contribution to journal › Article › peer-review