Published multiple papers in top conferences and journals such as NeurIPS, IJCAI, ICML, IJCV, ICLR, IEEE TVCG, IEEE T-PAMI, IEEE TMC, SenSys, CIKM, CVPR, IEEE T-ITS, AAAI, AutoML Conf, ACM TOSN, and IEEE TPAMI. Topics include efficient distillation, sign language translation, brain parcellations, road network generation, dynamic graph modeling, controlled text-to-image generation, attention reuse, differentiable pruning, eye tracking, on-face gesture recognition, opportunistic inference, trajectory recovery, hierarchical generative NAS, graph-based sign language processing, rotational speed estimation, fleet management, efficient NAS, macro NAS benchmarks (BLOX), zero-cost NAS, spatial data synthesis, deployment optimization for EV charging infrastructure, blind video super-resolution, zero-cost differentiable NAS, vibration-based communication between IoT devices, representation learning for event streams, NAS for tiny perceptual super-resolution, and semantic-instance segmentation for point clouds. Notable achievements include Best Paper Runner-up Award for AdaFlow at SenSys 2024 and Best Paper Award for T-CET at AutoML Conf 2023.
Research Experience
Previously a Senior Research Scientist at Samsung AI Centre Cambridge, where his team worked on Automated Machine Learning (AutoML) for On-device Intelligence.
Education
Postdoctoral research with the Cyber-Physical Systems Group in the Department of Computer Science (formerly known as the Computing Laboratory, or Comlab), University of Oxford. Studied Computer Science at Keble College, Oxford.
Background
Full Professor at the Department of Computer Science, University of Warwick, and Head of the AI/ML Systems (AMS) Division. Fellow of the Alan Turing Institute, serving as an Independent Scientific Advisor for the BridgeAI programme and a member of the Turing Research Ethics (TREx) team.
Miscellany
Multiple openings for PhD/internship positions for 2026 entry, with scholarships available from various sources at Warwick.