Visual artificial intelligence automatically interprets what happens in visual data like videos. Today’s research strives with queries like: “Is this person playing basketball?”; “Find the location of the brain stroke”; or “Track the glacier fractures in satellite footage”. All these queries are about visual observations already taken place. Today’s algorithms focus on explaining past visual observations. Naturally, not all queries are about the past: “Will this person draw something in or out of their pocket?”; “Where will the tumour be in 5 seconds given breathing patterns and moving organs?”; or, “How will the glacier fracture given the current motion and melting patterns?”. For these queries and all others, the next generation of visual algorithms must expect what happens next given past visual observations. Visual artificial intelligence must also be able to prevent before the fact, rather than explain only after it. In this talk, I will present my vision on what these algorithms should look like, and investigate possible synergies with other fields of science, like biomedical research, astronomy and others. Furthermore, I will present some recent works and applications in this direction within my lab and spinoff
Dr. Efstratios Gavves is an Associate Professor with the University of Amsterdam in the Netherlands and Scientific Director of the QUVA Deep Vision Lab. He is a recipient of the ERC Career Starting Grant 2020 and NWO VIDI grant 2020 to research on the Computational Learning of Temporality for spatiotemporal sequences. Also, he is a co-founder of Ellogon.AI, a University spinoff and in collaboration with the Dutch Cancer Institute (NKI), with the mission of using AI for pathology and genomics. He is currently supervising more than 12 Ph.D. and postdoctoral students in projects with the University of Amsterdam, the Dutch Cancer Institute, Ellogon.AI, and BMW. Efstratios has authored several papers in the top Computer Vision and Machine Learning conferences and journals and he is also the author of several patents. Further, Efstratios teaches Deep Learning in the MSc in Artificial Intelligence at the University of Amsterdam. All material is available on the project website, uvadlc.github.io. His research focus is on Temporal Machine Learning and Dynamics, Efficient Computer Vision, and Machine Learning for Oncology.