Keynote speakers

Biography

Zhi-Quan (Tom) Luo is the Vice President (Academic) of The Chinese University of Hong Kong, Shenzhen, where he has been a professor since 2014. He is concurrently the Director of Shenzhen Research Institute of Big Data. Professor Luo received his Ph.D. in Operations Research from MIT in 1989 and his B.S. degree in Mathematics in 1984 from Peking University, China. His research interests lie in the area of optimization, big data, signal processing and digital communication, ranging from theory, algorithms to design and implementation. Professor Luo is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) and the Society for Industrial and Applied Mathematics (SIAM). He received the 2010 Farkas Prize from the INFORMS Optimization Society, and the 2018 Paul Y. Tseng Memorial Lectureship from the Mathematical Optimization Society. He also received three Best Paper Awards in 2004, 2009 and 2011, a Best Magazine Paper Award in 2015, all from the IEEE Signal Processing Society, and a 2011 Best Paper Award from the EURASIP. In 2014, he was elected to the Royal Society of Canada. Professor Luo was elected to the Chinese Academy of Engineering in 2021, and was awarded the Wang Xuan Applied Mathematics Prize in 2022 by the China Society of Industrial and Applied Mathematics.

Biography

Laurent Lafforgue is a mathematician. He worked mainly in algebraic geometry and harmonic analysis. He was awarded the Fields Medal in 2002 for his contribution to the “Langlands program”, which relates Galois theory and automorphic representations theory through algebraic geometry. In the last years, his main interest gradually shifted to Grothendieck topos theory. He moved to the Paris Huawei Research center in 2021.

Biography

Sergio Barbarossa (Life Fellow, IEEE) is a Full Professor with Sapienza University of Rome and a Senior Research Fellow with Sapienza School for Advanced Studies (SSAS). He is a EURASIP Fellow. He received the Technical Achievements Award from the European Association for Signal Processing (EURASIP) society, in 2010, and the IEEE Best Paper Awards from the IEEE Signal Processing Society, in the years 2000, 2014, and 2020. He served as an IEEE Distinguished Lecturer from 2013 to 2014. He has been the scientific coordinator of several European projects. He is currently the Coordinator of a national project named Netwin (Network Intelligence). His main current research interests include topological signal processing and learning, generative models for semantic and goal-oriented communications, 6G networks, and distributed edge machine learning.

Biography

Tristan Cazenave is Professor of Artificial Intelligence at LAMSADE, Université Paris Dauphine - PSL. He specializes in Monte Carlo search and deep learning. He is also editor-in-chief of the ICGA Journal, head of the GT Jeux of the GDR IA of the CNRS, director of the IASD master's program at PSL and holds a chair at the PRAIRIE institute. Tristan Cazenave was the initiator of research on Monte-Carlo search algorithms in games and optimization. This has revolutionized game programming. When combined with deep learning it outperforms the best human players in difficult board games such as Go.  Tristan Cazenave extended its applications to fields other than games with the Nested Monte Carlo Search algorithm, which uses Monte Carlo search to improve Monte Carlo search.

Biography

Haitham Bou Ammar received the master's degree in mechatronics engineering from the University of Applied Science, Ravensburg Weingarten, Germany, in 2011 and the Ph.D. degree in artificial intelligence from Maastricht University, Maastricht, The Netherlands, in 2013.,He leads the reinforcement learning team at Huawei Technologies Research and Development, Cambridge, U.K. Previously, he led the Reinforcement Learning Group, Prowler. io., Cambridge, U.K. Prior to joining Prowler, he was an Assistant Professor with the Department of Computer Science, American University of Beirut (AUB), Beirut, Lebanon. Before AUB, he was a Postdoctoral Researcher with the Department of Operational Research and Financial Engineering, Princeton University, Princeton, NJ, USA. Prior to joining Princeton, he was a Postdoctoral Research Associate with the Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, USA, and a member of the General Robotics, Automation, Sensing and Perception Lab, University of Pennsylvania, Philadelphia, PA, USA. His research interests include statistical machine learning and artificial intelligence, focusing on lifelong learning, multitask learning, and knowledge transfer with applications to reinforcement learning.

Biography

Mérouane Debbah is 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 and Falcon LLM (upon its release, top ranked open source large language model) released in 2023. These two models have positioned the UAE as a global leader in the generative AI field. model) released in 2023. He is a member of the Marconi Prize Selection Advisory Committee.

Biography

Julien Launay, currently leading the Extreme-Scale Team at Hugging Face, focuses on open models and tools. He previously led research at LightOn, developing large language models and projects like Falcon-40B and RefinedWeb. Holding an Industrial Ph.D. in Applied Mathematics from École Normale Supérieure and a Master's in Climate Science from École Polytechnique, he's contributed to beyond backpropagation methods and optical computing. His research relates to challenges in scaling LLMs, with a focus on data scalability and solving problems at the crossroads of large-scale engineering and pure research. Julien is now focusing his work on democratising reinforcement learning for more singular AI experiences. 

Biography

Johannes Schneider is an Associate Professor of Data Science and Artificial Intelligence (AI) at the University of Liechtenstein. He has worked in industrial research labs at IBM and ABB. His international experience covers working in Switzerland, Japan, India, Sweden, etc. He obtained his Master's degree and Ph.D. in Computer Science and a Master of Advanced Studies in Management, Technology, and Economics from ETH Zurich. His research, honored with multiple best paper awards, encompasses theoretical studies and practical applications of data science and AI. It has been published both within and outside the computer science community.

Biography

Andreas Geiger is a professor at the University of Tübingen and the Tübingen AI Center. Prior to this, he was a visiting professor at ETH Zürich and a group leader at the Max Planck Institute for Intelligent Systems. He studied at KIT, EPFL and MIT, and received his PhD degree in 2013 from KIT. His research interests are at the intersection of computer vision, machine learning and robotics. His work has been recognized with several prizes, including the Longuet-Higgins Prize, the Mark Everingham Prize, the IEEE PAMI Young Investigator Award, the Heinz Maier Leibnitz Prize and the German Pattern Recognition Award. In 2013 and 2021 he received the CVPR best paper and best paper runner-up awards. He also received the best paper award at GCPR 2015 and 3DV 2015 as well as the best student paper award at 3DV 2017. In 2019, he was awarded an ERC starting grant. He is an ELLIS fellow and coordinates the ELLIS PhD and PostDoc program. He regularly serves as area chair and associate editor for several computer vision conferences and journals including CVPR, ICCV, ECCV, PAMI and IJCV. He maintains the KITTI and KITTI-360 benchmarks.

Biography

Christina-Ourania Tze is a PhD student at the University of Tübingen working with Prof. Andreas Geiger at the Autonomous Vision Group. As part of the ELLIS PhD program, she is co-supervised by Dzmitry Tsishkou from Huawei Technologies. Prior to this, she was an undergraduate in the School of Electrical and Computer Engineering in Athens, Greece, where she worked with Prof. Petros Maragos on sign language processing, video anonymization, and human motion retargeting. Her research interests lie at the intersection of Computer Vision and Computer Graphics, particularly in the areas of 3D vision and controllable generative models for objects and scenes.

Biography

Martin Jaggi is an Associate Professor at EPFL, heading the Machine Learning and Optimization Laboratory. Before joining EPFL, he was a post-doctoral researcher at ETH Zurich, at the Simons Institute in Berkeley, and at École Polytechnique in Paris. He has earned his PhD in Machine Learning and Optimization from ETH Zurich in 2011, and a MSc in Mathematics also from ETH Zurich. He is a co-founder of EPFL's Applied Machine Learning Days, and a Fellow of the European ELLIS network.

Biography

Paolo Papotti is an Associate Professor at EURECOM, France since 2017. He got his PhD from Roma Tre University (Italy) in 2007 and had research positions at the Qatar Computing Research Institute (Qatar) and Arizona State University (USA). His research is focused on data management and, more recently, on NLP. He has authored more than 140 publications, and his work has been recognized with two “Best of the Conference” citations (SIGMOD 2009, VLDB 2016), three best demo award (SIGMOD 2015, DBA 2020, SIGMOD 2022), and two Google Faculty Research Award (2016, 2020).