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 founded in 2010. She is currently Head of the Department of Computing, Convening Co-Director of the School of Convergence Science in Human and Artificial Intelligence, Co-Director of the UKRI CDT on Safe and Trusted AI, and promoter of the Imperial-X multi-disciplinary research initiative “Intelligible AI”.

Her work concerns the development of general-purpose symbolic machine learning systems and neuro-symbolic AI methods and tools that are robust, interpretable and explainable to humans. 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 and more recently Healthcare. Her broad research interests include Artificial Intelligence, Symbolic Machine Learning, Neurosymbolic AI, Computational Logic, Planning, Probabilistic and Distributed Inference.

With her collaborators, she has pioneered several state-of-the-art symbolic machine learning systems. The most recent of these, ILASP, is currently the most expressive, powerful, and robust state-of-the-art system for learning interpretable models from labelled data. This work has led to the creation of a R&D company (ILASP Limited), which focuses on the development of AI-driven systems for safety and critical decision making. ILASP is led by Prof Russo ex PhD student Dr Mark Law, and Professor Russo is senior research advisor of ILAPS Limited.

From 2018, Prof Russo’s work has focused on neuro-symbolic AI, proposing novel architectures and systems that integrate Machine Learning and Frontier AI with probabilistic inference and symbolic learning, to support the learning and generalisation of interpretable and explainable models from multimodal unstructured data, and the development of provable guarantees over the performance of frontier AI. She has applied these solutions to real-world problems in Healthcare, Security and Network Management.

She has published over 200 articles in flagship conferences and high impact journals in the areas of Artificial Intelligence and Software Engineering. She has served over 25 research projects as PI/CoI funded by the EPSRC, the EU and Industry, securing in total over £15M.