Deep Learning Deep Feelings: Large Models, Larger Emotions
Bjoern Schuller, University of Augsburg, Germany and Imperial College London, United Kingdom
From Satellites to Social Media: What Data Tells us About Society
Ingmar Weber, Saarland University, Germany
David Camacho, Technical University of Madrid, Spain
(Cancelled)
Deep Learning Deep Feelings: Large Models, Larger Emotions
Bjoern Schuller
University of Augsburg, Germany and Imperial College London
United Kingdom
www.schuller.one
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Brief Bio
Björn W. Schuller is a distinguished academic and researcher with extensive expertise in Machine Intelligence and Signal Processing. He earned his diploma, doctoral degree, habilitation, and Adjunct Teaching Professor title in EE/IT from TUM in Munich, where he currently holds a Full Professorship as Chair of Health Informatics. Additionally, he is a Full Professor of Artificial Intelligence and Head of GLAM at Imperial College London. Schuller co-founded audEERING, an Audio Intelligence company, and has numerous affiliations, including roles at the Munich Data Science Institute and the Munich Center for Machine Learning. He has held multiple prestigious professorships globally and served as an independent research leader at the Alan Turing Institute. He is a Fellow of several prominent societies, including the ACM, IEEE, BCS, ELLIS, ISCA, and AAAC. With over 1,500 publications, more than 70,000 citations, and an h-index exceeding 110, he is highly influential in the field of Computer Science. He has held editorial positions, including Field Chief Editor of Frontiers in Digital Health, Editor in Chief of AI Open, and the IEEE Transactions on Affective Computing. Schuller has received over 50 awards, including being named one of 40 extraordinary scientists under 40 by the WEF in 2015. Currently, he is an ACM Distinguished Speaker and an IEEE Signal Processing Society Distinguished Lecturer. His work has been widely recognized in the media, with over 300 public press appearances and contributions to various international outlets including Newsweek, Scientific American, and Times.
Abstract
As AI systems permeate every corner of modern life, a crucial frontier emerges enabling machines not just to learn, but to feel—at least enough to understand our states and communicate with us in empathic manners. This keynote takes you on a journey from the current “Affective Intelligence” largely empowered by deep learning to the rising wave of large model exploitation in “Affective Intelligence 2.0”. Blending advances in affective computing and the rapid progress in multimodal foundation models, emotionally aware AI is about to reshape human-machine interaction, digital health, multimedia, and will be a corner stone of AGI to come. Beyond algorithms, this talk explores the power—and responsibility—of creating machines that respond with empathy, adapt to individual emotional states, and navigate the complexities of real-world human affective experience. It will further highlight the potential of affective computing in “Friendly AI” and discuss potential of emotion as inspiration in deep learning. With a critical eye on ethical design and societal impact, the talk invites you to imagine an AI future that goes beyond data—into emotion, connection, and care.
From Satellites to Social Media: What Data Tells us About Society
Ingmar Weber
Saarland University
Germany
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Brief Bio
Ingmar Weber is the recipient of an Alexander von Humboldt Professorship, Germany’s most valuable research award, and holds the Chair for Societal Computing at Saarland University. His interdisciplinary research comprises (i) computing of society, i.e. the measurement of different social phenomena, in particular using non-traditional data sources, and (ii) computing for society, i.e. working with partners on implementing solutions to help address societal challenges. Analyses performed by his team and collaborators have been used in displacements contexts ranging from Venezuela to Ukraine. Prior to joining Saarland University, Ingmar was the Research Director for Social Computing at the Qatar Computing Research Institute. He studied mathematics at the University of Cambridge before pursuing a Ph.D. at the Max-Planck Institute for Computer Science. He is and ACM Distinguished Member and is among the top 2% of most cited scientists worldwide.
Abstract
From estimating conflict-driven displacement by counting vehicles in satellite images to measuring digital gender gaps through advertising metrics, non-traditional data sources are transforming how we “take society’s pulse.”
In this keynote I will survey recent data-innovation projects that creatively repurpose such sources to illuminate societal phenomena. Methodologically, the central challenge is correcting for the many biases inherent in unconventional data—after all, not everyone uses social media or even has internet access. This issue becomes even more acute when collaborating with development and humanitarian stakeholders: while insights can make operations more targeted and effective, they also risk overlooking the digitally invisible. I will share lessons learned from these collaborations and discuss risks that extend beyond individual-level privacy to the broader concern of inadvertently exposing or excluding vulnerable groups.
Keynote Lecture
David Camacho
Technical University of Madrid
Spain
* CANCELLED *
Brief Bio
David Camacho is Full Professor at Computer Systems Engineering Department of Universidad Politécnica de Madrid (UPM), he is the head of the Applied Intelligence and Data Analysis research group (AIDA: https://aida.etsisi.upm.es), the Director of the PhD program in Computer Science and Technologies of Smart Cities, and the Director of the Master program in Machine Learning and Big Data at UPM. He has published more than 300 journals, books, and conference papers (https://scholar.google.es/citations?hl=en&user=fpf6EDAAAAA). His research interests include Machine Learning (Clustering/Deep Learning), Computational Intelligence (Evolutionary Computation, Swarm Intelligence), Social Network Analysis, Fake News and Disinformation Analysis. He has participated/led more than 60 AI-based R&D projects (National and International: H2020, MCSA ITN-ETN, DG Justice, ISFP, NRF Korea), applied to real-world problems in areas as aeronautics, aerospace engineering, cybercrime/cyber intelligence, social networks applications, disinformation countering, or video games among others. He serves as Editor in Chief of Expert Systems from 2023 and sits on the Editorial Board of several journals including Information Fusion, Human-centric Computing and Information Sciences (HCIS), and Cognitive Computation, IEEE Transactions on Emerging Topics in Computational Intelligence (IEEE TETCI), among others.