Fabio Cuzzolin

Prof Fabio Cuzzolin graduated magna cum laude in Computer Engineering from the University of Padua, one of the top 3 Italian universities and in the top spot for research quality according to the country's National Evaluation Agency. He received a Ph.D. degree there in 2001 for a thesis entitled "Visions of a generalized probability theory". He was later a Visiting Scholar with the Washington University in St. Louis (16th in US rankings), a giovane ricercatore at Politecnico di Milano (the best Italian university) and a Postdoc at the University of California at Los Angeles (the 2nd best public university in the world), before been awarded in 2006 a Marie Curie Fellowship with INRIA, Grenoble. In 2008 he joined Oxford Brookes as an Early Career Fellow and was promoted to Professor in December 2015.

Cuzzolin is the founder and Director of Brookes’ Visual AI Lab (VAIL, projected to comprise 35+ people in 2022), conducting research in artificial intelligence, machine learning, uncertainty theory, computer vision, surgical robotics and autonomous driving. He is currently the Coordinator of the H2020 FET Open project E-pi, and Scientific Officer for the H2020 project 779813-SARAS (Smart Autonomous Robot Assistant Surgeon). To date Cuzzolin has attracted funding as a PI for a total of circa £5,500,000, of which £3.5M in the past two years alone. Currently the Lab is running 9 live funded projects, supported by Horizon 2020, the Leverhulme Trust, Innovate UK, Huawei, EPSRC and the British Council. He is also Lead Advisor for Brookes’ £1,26M AI & Data Analysis Incubator.

Cuzzolin authored some 125 publications, including two monographs, three edited volumes and 32 journals or book chapters, with a total impact factor of around 172. His work won a Best Paper Award at PRICAI’08 , a Best Poster at ISIPTA’11 and the 2012 MLVR Summer School , a nomination for Best Paper and an Outstanding Reviewer Award at BMVC’12. He has served in the Board of IEEE Fuzzy Systems, IEEE SMC, Elsevier’s International Journal of Approximate Reasoning and Information Fusion, the IEEE Trans. on Neural Networks and Learning Systems and Frontiers in Artificial Intelligence. He was Chair or Steering Committee member for BELIEF 2014 and BELIEF 2018 and Area Chair for UAI, the British Machine Vision Conference, the European Conference on Computer Vision and the International Conference on Computer Vision. He served in the PC of 100+ international conferences, including IJCAI, NIPS, ICML, CVPR and was/is the lead organiser of four recent workshops and challenges co-located with MIDL 2020, ICCV, IJCAI and MICCAI 2021.

Cuzzolin is a recognised leader in uncertainty theory, thanks to his formulation of an original geometric approach in which uncertainty measures are analysed by geometric means. This work has led to two monographs, two edited volumes and various tutorials and invited talks at Harvard, Cambridge, UAI and IJCAI. His Visual AI Laboratory has a strong position in deep learning for human behaviour understanding, evidenced by the first system able to localise multiple events in real time. The team ranked 2nd at both the CVPR 2017 Charades and the CVPR 2016 ActivityNet action detection challenges, and is now pioneering the fields of future action prediction and complex activity detection for both surgical robotics (SARAS) and autonomous driving, via the new ROAD and MESAD benchmarks and the associated ICCV and MICCAI Challenges. The Lab is spinning out a company (Olympia.ai) to exploit its core detection technologies in the sports analytics sector. In artificial intelligence Cuzzolin is pioneering the concept of a machine theory of mind with Cambridge neuroscience. He has recently proposed a new continual semi supervised learning paradigm and launched the first such challenge at IJCAI 2021. He is developing with IIT Bombay the first continual zero-shot learning approach to action recognition, studying the links between neurosymbolic AI and graph networks in partnership with Samsung AI, and exploring the concept of goal-changing machines.