Rate My Professor Alessandra Russo

Alessandra Russo is Professor in Applied Computational Logic in the Department of Computing, Faculty of Engineering at Imperial College London. She serves as Head of the Department of Computing and Convening Co-Director of the School of Human and Artificial Intelligence in the School of Convergence Science. An academic member of the Distributed Software Engineering section, she leads the Structured and Probabilistic Knowledge Engineering (SPIKE) research group and directs the Machine Learning Lab. Russo earned her PhD in Computing from Imperial College London in 1996, following a First Class Honours degree with Distinction in Computer Science from Università degli Studi di Bari, Italy. She joined Imperial as a Research Associate from 1997 to 2001, became a Lecturer in 2001, and has been a faculty member for over 25 years.

Her research specializes in computational logic, planning, symbolic machine learning, probabilistic and distributed inference, neuro-symbolic AI, and robustness of generative models. Russo has pioneered state-of-the-art symbolic machine learning systems applied to intelligent adaptive systems, security, network management, distributed control systems for sensor networks, and healthcare. She has authored over 150 refereed papers in top-tier AI and software engineering venues, with her work cited more than 6,500 times on Google Scholar. Notable publications include 'Inductive Learning of Answer Set Programs' (Law, Russo, Broda, 2014) and 'Learning Weak Constraints in Answer Set Programming' (Law, Russo, Broda, 2015). Her contributions extend to leadership in the Thomson Reuters-Imperial Frontier AI Lab. Awards include the Imperial College Rector's Award for Excellence in Teaching (2011) and the President's Award for Research Supervision (2020).