Alessandra Russo is Professor in Applied Computational Logic in the Department of Computing, Imperial College London, where she leads the Structured and Probabilistic Knowledge Engineering (SPIKE) research group. She has pioneered several state-of-the-art symbolic machine learning systems and widely applied them to the areas of Intelligent Adaptive Systems, Security, Network Management, Distributed Control Systems for Sensor Networks, and System Biology. Her broad research interests include Computational Logic, Planning, Symbolic Machine Learning, Probabilistic and Distributed Inference.
The SPIKE group has developed LAS (Learning from Answer Sets) system, a state-of-the-art system for learning interpretable knowledge from labelled data, and more recently explored novel methodologies for neuro-symbolic learning that integrate machine learning and probabilistic inference with symbolic learning to support generalisation and transfer learning from multimodal unstructured data.
She has published more than 150 referred papers in top-tier AI and top-tier Software Engineering conferences and journals, has been Editor-in-Chief of the IET Software Journal and Associated Editor of the ACM Computing Survey Journal. She is Fellow BCS, and Associate Editor of the TPLP journal for the area of Logic and Machine Learning.
For more information, visit Alessandra Russo’s public profile.
