We are honored and delighted to host the following IEEE ICIP 2025 Plenary Talks:

Bernhard Schölkopf
Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen.

“Causal representations, world models and digital twins”

Bio: Bernhard Schölkopf studies machine learning and causal inference, with applications to fields ranging from astronomy to biomedicine, computational photography, music and robotics. Originally trained in physics and mathematics, he earned a Ph.D. in computer science in 1997 and became a Max Planck director in 2001. His awards include the ACM AAAI Allen Newell Award, the BBVA Foundation Frontiers of Knowledge Award, the Leibniz Award, and the Royal Society Milner Award. He is a Professor at ETH Zurich, a Fellow of the ACM and of the CIFAR Program “Learning in Machines and Brains”, and a member of the German Academy of Sciences. He helped start the MLSS series of Machine Learning Summer Schools, the ELLIS society, and the Journal of Machine Learning Research, an early development in open access and today the field’s flagship journal. In 2023, he founded the ELLIS Institute Tuebingen, and acts as its scientific director.

Abstract: Research on understanding and building artificially intelligent systems has moved from symbolic approaches to statistical learning, and is now beginning to study interventional models relying on concepts of causality.

Some of the hard open problems of machine learning and AI are intrinsically related to causality, and progress may require advances in our understanding of how to model and infer causality from data, as well as conceptual progress on what constitutes a causal representation and a causal world model.

I will present basic concepts and thoughts, as well some applications to astronomy.

Photo credit: Herlinde Koelb

Antonio Torralba
Delta Electronics Professor of Electrical Engineering and Computer Science, Head of AI+D Faculty, Department of Electrical Engineering and Computer Science, MIT.

Bio: Antonio Torralba is the Delta electronics Professor and head of the AI+D faculty at the Department of Electrical Engineering and Computer Science (EECS) at the Massachusetts Institute of Technology (MIT). From 2017 to 2020, he was the MIT director of the MIT-IBM Watson AI Lab, and, from 2018 to 2020, the inaugural director of the MIT Quest for Intelligence, a MIT campus-wide initiative to discover the foundations of intelligence. He is also member of CSAIL and the Center for Brains, Minds and Machines. He received the degree in telecommunications engineering from Telecom BCN, Spain, in 1994 and the Ph.D. degree in signal, image, and speech processing from the Institut National Polytechnique de Grenoble, France, in 2000. From 2000 to 2005, he spent postdoctoral training at the Brain and Cognitive Science Department and the Computer Science and Artificial Intelligence Laboratory, MIT, where he is now a professor. Prof. Torralba has served as program chair for the Computer Vision and Pattern Recognition conference in 2015. He received the 2008 National Science Foundation (NSF) Career award, the best student paper award at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) in 2009, the 2010 J. K. Aggarwal Prize from the International Association for Pattern Recognition (IAPR), the 2017 Frank Quick Faculty Research Innovation Fellowship, the Louis D. Smullin (’39) Award for Teaching Excellence, the 2020 PAMI Mark Everingham Prize, and was named 2021 AAAI fellow. In 2021, he was awarded the Inaugural Thomas Huang Memorial Prize by the PAMITC. In 2022, he was invested Honoris Causa doctor by the Universitat Politècnica de Catalunya – BarcelonaTech (UPC). 

Maja Pantic
Imperial College London

“Conversational AI Buddies and Deep Fakes”

Bio: Maja Pantic is a Professor in AI at Imperial College London. Previously, she was a Generative AI Research Director at Meta AI (2020 – 2025) and Research Director and Co-founder of Samsung AI Centre Cambridge (2018 – 2020). Prof Pantic has co-authored more than 500 papers with more than 55k citations and an h-index of 107 to date. She received various awards for her work on automatic analysis of human behaviour, including IAPR Maria Petrou Award in 2020 and British Computer Society Roger Needham Award in 2011. She served as an Associate Editor in top AI journals, including International Journal of Computer Vision (2021- present) and IEEE Transactions on Pattern Analysis and Machine Intelligence (2011-2021). She is a Fellow of the UK’s Royal Academy of Engineering, an IEEE Fellow, and an IAPR Fellow.

Abstract: This talk is about conversational AI and how far are we from being able to talk to AI in natural languages. The talk will touch upon modelling and implementation of the AI embodiment in a photorealistic manner. It will explain machine learning, computer vision and Generative AI methods developed to this end and used for photorealistic AI Buddies generation. The talk will end in discussion of possible applications and misuses of this technology, including Deep Fakes.