Rate My Professor Alessandra Russo

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).