Speakers

• Xavier Alameda-Pineda - Inria at University Grenoble Alpes, Grenoble, France
  Bio: Xavier Alameda-Pineda is a (tenured) Research Scientist at Inria and the Leader of the RobotLearn Team. He obtained the M.Sc. (equivalent) in Mathematics in 2008, in Telecommunications in 2009 from BarcelonaTech, and in Computer Science in 2010 from Univ. Grenoble-Alpes (UGA). He then worked towards his Ph.D. in Mathematics and Computer Science, and obtained it in 2013, from UGA. After a two-year post-doc period at the Multimodal Human Understanding Group, at the University of Trento, he was appointed to his current position. Xavier is an active member of SIGMM, a senior member of IEEE, and a member of ELLIS. He was the Coordinator of the H2020 Project SPRING: Socially Pertinent Robots in Gerontological Healthcare and is co-leading the “Audio-visual machine perception and interaction for companion robots” chair of the Multidisciplinary Institute of Artificial Intelligence. Xavier’s research interests are at the crossroads of machine learning, computer vision, and audio processing for scene and behavior analysis and human-robot interaction.
  

• Antoine Bosselut - EPFL
  

• Claire Boyer - LMO, Université Paris-Saclay
  

• Merouane Debbah - Khalifa University, Abu Dhabi, UAE
  Bio: Mérouane Debbah is a researcher, educator and technology entrepreneur. Over his career, he has founded several public and industrial research centers, start-ups and is now Professor at Khalifa University of Science and Technology in Abu Dhabi and founding Director of the KU 6G Research Center. He is also the Chief Scientific AI Advisor at the Technology Innovation Institute. He is a frequent keynote speaker at international events in the field of telecommunication and AI. His research has been lying at the interface of fundamental mathematics, algorithms, statistics, information and communication sciences with a special focus on random matrix theory and learning algorithms. In the Communication field, he has been at the heart of the development of small cells (4G), Massive MIMO (5G) and Large Intelligent Surfaces (6G) technologies. In the AI field, he is known for his work on Large Language Models, distributed AI systems for networks and semantic communications. He received multiple prestigious distinctions, prizes and best paper awards (more than 40 IEEE best paper awards) for his contributions to both fields and according to research.com is ranked as the best scientist in France in the field of Electronics and Electrical Engineering. He is an IEEE Fellow, a WWRF Fellow, a Eurasip Fellow, an AAIA Fellow, an Institut Louis Bachelier Fellow and a Membre émérite SEE. His recent work led to the development of NOOR (upon it release, largest language model in Arabic) released in 2022, Falcon LLM (upon its release, top ranked open source large language model) released in 2023 and the Falcon Foundation in 2024. The Falcon Model Series and The Falcon Foundation have positioned the UAE as a global leader in the generative AI field. He is a member of the Marconi Prize Selection Advisory Committee.

• Manuel Faysse - CentraleSupélec, Université Paris-Saclay/Illuin Technology
  Manuel Faysse is currently a PhD student at CentraleSupélec in the MICS laboratory, under the supervision of Pierre Colombo and Céline Hudelot.
  His research focuses on industrial applications of large language models, with interests in automatic LLM evaluation, Large Language Model pretraining (CroissantLLM), multimodal information retrieval (ColPali), as well as model memorization, or confidence estimation techniques for neural information retrieval. His work has been published in top international conferences (ICML, EMNLP, TMLR), has been featured in the press (MIT Tech Review, Nature Magazine, Usine Digitale, Usine Nouvelle, etc.) and has been shared in invited talks (Meta, IBM, Naver, LlamaIndex, etc.).
  Manuel’s PhD is funded through the CIFRE French program in collaboration with Illuin Technology, where he currently holds a Lead Research Scientist position, and spends a minor share of his time advising and accompanying various R&D efforts in the LLM and Vision LLM space.
  

• Vicky Kalogeiton - LIX, IPP
  Vicky Kalogeiton is an Assistant Professor at École Polytechnique since 2020. She received her M.Sc degree in Computer Science from the DUTh, Greece, 2013, where her master’s thesis won the best thesis award. In 2017, she obtained her PhD from the University of Edinburgh and Inria, Grenoble, advised by V.Ferrari and C.Schmid, where part of her thesis won the best poster award from the Grenoble Alpes University in 2016. From 2018 to 2021, she was a research fellow at Oxford University working with A.Zisserman. Some of the projects she supervised were a highlight (CVPR 2024), won the student honorable mention award (ACCV 2022), and the best paper award (ICCV-W 2021). She was Associate Editor for CMBBE from 2017 to 2024 and has been Associate Editor for CVIU since 2024. Since 2021, she has been serving regularly as Area Chair at major vision conferences (outstanding Area Chair in 2022) and before she used to serve as a reviewer, having been awarded six times as an outstanding reviewer. Vicky Kalogeiton is the recipient of several grants, including two MS Azure Academic gifts, and an ANR JCJC award for junior researchers in France. She has co-organized workshops at CVPR, and ICCV, has given more than 30 invited talks, has been a mentor for women, students, and underrepresented groups in vision, and high-school students. Her research interests focus on multimodal learning (visual data, text, audio) split into three axes: generative AI, video understanding, and multimodal medical applications.

• Eric Moulines - Ecole Polytechnique
  

• Claire Monteleoni - University of Colorado Boulder/INRIA
  Bio: Claire Monteleoni is a Choose France Chair in AI and a Research Director at INRIA Paris, a Professor in the Department of Computer Science at the University of Colorado Boulder, and the founding Editor in Chief of Environmental Data Science, a Cambridge University Press journal launched in December 2020. Her research on machine learning for the study of climate change helped launch the interdisciplinary field of Climate Informatics. She co-founded the International Conference on Climate Informatics, which will hold its 14th annual event in 2025. She gave an invited tutorial: Climate Change: Challenges for Machine Learning, at NeurIPS 2014. She currently serves on the U.S. National Science Foundation’s Advisory Committee for Environmental Research and Education, and as Tutorials co-Chair for the International Conference on Machine Learning (ICML) 2024 and 2025. 
  

• Alasdair Newson - Sorbonne Université
  

• Gaël Richard - IPP/Télécom Paris
  Bio: Gaël Richard received the State Engineering degree from Telecom Paris, France in 1990, the Ph.D. degree and Habilitation from University of ParisSaclay respectively in 1994 and 2001. After the Ph.D. degree, he spent two years at Rutgers University, Piscataway, NJ, in the Speech Processing Group of Prof. J. Flanagan, where he explored innovative approaches for speech production. From 1997 to 2001, he successively worked for Matra, Bois d’Arcy, France, and for Philips, Montrouge, France. He then joined Telecom Paris, where he is now a Full Professor in audio signal processing. He is also the co-scientific director of the Hi! PARIS interdisciplinary center on Artificial Intelligence and Data analytics. He is a coauthor of over 250 papers and inventor in 10 patents. His research interests are mainly in the field of speech and audio signal processing and include topics such as signal representations, source separation, machine learning methods for audio/music signals and music information retrieval. He received, in 2020, the Grand prize of IMT-National academy of science for his research contribution in sciences and technologies. He is a fellow member of the IEEE and the past Chair of the IEEE SPS Technical Committee for Audio and Acoustic Signal Processing. In 2022, he is awarded of an advanced ERC grant of the European Union for a project on machine listening and artificial intelligence for sound.
  

• Yunhao (Robin) Tang - Meta GenAI London
  

• Denis Trystam - Grenoble INP