Vaishak Belle

Vaishak Belle is Reader in AI at the School of Informatics, University of Edinburgh, and Director of Research and Innovation at the Bayes Centre. He is also a Royal Society University Research Fellow and an Alan Turing Institute Faculty Fellow. He leads a research group that unifies logic and machine learning, with an emphasis on neuro-symbolic AI, probabilistic and causal reasoning, explainability, and AI ethics. His work develops computational frameworks that learn from data while remaining modular, explainable, and robust to changes in problem description. He has co-authored close to 150 peer-reviewed articles at venues including IJCAI, UAI, AAAI, Artificial Intelligence, JAIR, Machine Learning, and TMLR, and his work has received best paper awards at NeSy 2026, IJCLR 2024, and UAI 2015 (Microsoft best paper award). He is the author of the book Toward Robots That Reason: Logic, Probability and Causal Laws (Springer, 2023). Within the QSL, he is a co-investigator on the UKRI-funded Quantum Advantage TurboCHarger (QATCH) project, working on trust and verification with hybrid quantum-classical models. He has consulted with industry partners, including NatWest Group, on explainable AI, and previously held positions at KU Leuven, the University of Toronto, RWTH Aachen, and the University of Trento.