Nicola Conci
Associate Professor, University of Trento
Nicola Conci is Associate Professor at the Dept. of Information Engineering and Computer Science, University of Trento (Italy), where he teaches computer vision and signal processing. He received his PhD degree from the international ICT Doctoral School of Trento, Italy, in 2007. In 2008 he was post Doctoral Researcher at Create-NET, leading the video coding research activities for the EU-Project MING-T (VI Framework Programme RTD – IST). In 2008 and 2009, he was research assistant in the Multimedia and Vision Group at the Queen Mary, University of London (UK). His research interests are in the field of image and video analysis for human behavior understanding in monitoring and surveillance applications, focusing on the classification of human interactions and behavioral patterns from crowded scenes, with application to motion segmentation, anomaly detection and path prediction.
Lecture
Leveraging Simulation to Better Understand the Real World
Artificial Intelligence increasingly relies on processing vast amounts of data. Simulation tools have proven invaluable in both enriching existing datasets and generating new ones from scratch, especially given the availability of advanced modeling software. While simulations are well-established for object modeling and producing limitless visual samples under varying perspectives and lighting conditions, their potential goes far beyond.
Modern simulation frameworks now enable the modeling of human-related activities, capturing actions at multiple scales and complex behavioral patterns. Accurately simulating human behavior provides insight into the subtle features that characterize individual traits. This capability opens up transformative applications across diverse domains: from video surveillance and health monitoring to rehabilitation, athletic performance analysis, and tactics in sports.
By bridging synthetic environments and real-world complexity, simulation is poised to play a central role in advancing AI’s understanding of human and environmental dynamics.
