Keynote speakers

Biography

Volkan Cevher received the B.Sc. (valedictorian) in electrical engineering from Bilkent University in Ankara, Turkey, in 1999 and the Ph.D. in electrical and computer engineering from the Georgia Institute of Technology in Atlanta, GA in 2005. He was a Research Scientist with the University of Maryland, College Park, from 2006-2007 and also with Rice University in Houston, TX, from 2008-2009. He was also a Faculty Fellow in the Electrical and Computer Engineering Department at Rice University from 2010-2020. Currently, he is an Associate Professor at the Swiss Federal Institute of Technology Lausanne and an Amazon Scholar. His research interests include machine learning, optimization theory and methods, and automated control. Dr. Cevher is an IEEE Fellow ('24), an ELLIS fellow, and was the recipient of the ICML AdvML Best Paper Award in 2023, Google Faculty Research award in 2018, the IEEE Signal Processing Society Best Paper Award in 2016, a Best Paper Award at CAMSAP in 2015, a Best Paper Award at SPARS in 2009, and an ERC CG in 2016 as well as an ERC StG in 2011.

Biography

Éric Moulines, an alumnus of École Polytechnique (1984) and PhD graduate in electrical engineering from École Nationale Supérieure des Télécommunications (1990), is a Professor of Statistics at the Centre for Applied Mathematics, École Polytechnique. Before joining École Polytechnique, he was a professor at Télécom ParisTech, where he specialized in statistics and signal processing. His research spans computational statistics, Monte Carlo methods, stochastic optimization, and probabilistic machine learning, with seminal contributions to sequential Monte Carlo methods and nonlinear filtering. Currently, Pr. Moulines focuses on generative models for inverse problems, stochastic approximation in federated and collaborative learning, and uncertainty quantification using Bayesian and conformal prediction techniques. His work bridges theoretical advancements with practical applications, particularly in telecommunications and complex system control. A prolific scholar, he has authored over 120 journal articles and 400 conference papers in signal processing, statistics, and machine learning. He has also played a key editorial role in leading academic journals, serving as Editor-in-Chief of Bernoulli (2013–2016). Pr. Moulines' contributions have earned him prestigious recognitions, including fellowships from EURASIP, IMS, and AAIA. His numerous accolades include the CNRS Silver Medal (2010), the Orange Prize from the French Academy of Sciences (2011), and the EURASIP Technical Achievement Award (2020). In 2017, he was elected to the French Academy of Sciences, underscoring his status as a leading authority in his field.

Biography

Igor Carron is the CEO and co-founder of LightOn, a publicly traded company that provides GenAI to Enterprise customers. Igor holds a PhD in Nuclear Engineering and has worked in a few nuclear and aerospace projects. In the past few years, he has also co-organized the Paris Machine Learning Applications meetup with more than 300 speakers and 100 meetups and he used to write a small blog called Nuit Blanche featuring the latest and greatest in compressive sensing.

Biography

Haitham leads the Reinforcement Learning, Embodied AI, and Bayesian Optimization teams at Huawei Technologies R&D UK and is an Honorary Lecturer at UCL. Previously, he led the Reinforcement Learning and Tuneable AI team at PROWLER.io, contributing to finance and logistics applications. Before that, he was an Assistant Professor at the American University of Beirut (AUB) and a postdoctoral researcher at Princeton University and the University of Pennsylvania, where he worked on lifelong machine learning and robotics. His research focuses on statistical machine learning, Bayesian optimisation, probabilistic modeling, and reinforcement learning, with broader interests in control theory, nonlinear systems, social networks, and distributed optimisation. Haitham published over 110 manuscripts at top-tier machine learning and AI venues including but not limited to, ICML, NeuRIPS, ICLR, JMLR. Haitham has also won numerous awards including best paper awards at CoRL, NeurIPS competition on black box optimisation, AAMAS best paper award, Epfl challenge on Logic Synthesis and IROS best paper award. 

Biography

Ludovic Denoyer is the current driving the agent research team at H Company. He is a full Professor at Sorbonne University on sabbatical, and has explored multiple directions in deep learning, large language models and deep reinforcement learning since his thesis in 2004. He has  particularly focused on agents at Meta (FAIR) but also more recently at Ubisoft where he was leading the bot research group.  He has supervised dozens of Ph.D students and contributed to more than 150 research articles in various domains. 

Biography

Giada Pistilli is a philosopher specialized in AI ethics, focusing on conversational agents and generative AI. With a PhD in philosophy from Sorbonne University, her research explores the intersections of value systems, ethical frameworks, multilingualism, and cultural biases in emerging technological landscapes. As Principal Ethicist at Hugging Face, she conducts interdisciplinary research that bridges philosophical inquiry with technological development. In this role, she also oversees the platform's content moderation policy, applying ethical principles to the challenges of large-scale AI systems.

Biography

Rolf Pfister is Director of Research at Lab42, a Swiss non-profit AI institute dedicated to the development of human-level AI. His research includes the development of fundamentally new approaches to AGI as well as measuring the progress of current approaches. This includes theoretical considerations on the nature of intelligence as well as the development and application of benchmarks such as ARC-AGI. With a background in philosophy of science, Rolf's focus is on how scientific theories are developed and new theoretical concepts, such as gravity, are introduced. In addition to his academic experience, Rolf has extensive entrepreneurial experience in the field of AI, in which he is active as a consultant, speaker, and founder of several companies.

Biography

Yinyu Ye is currently the K.T. Li Professor of Stanford University and Visiting Chair Professor Shanghai Jiao Tong University. His current research topics include Continuous and Discrete Optimization, Data Science and Applications, Numerical Algorithm Design and Analyses, Algorithmic Game/Market Equilibrium, Operations Research and Management Science etc.; and he was one of the pioneers on InteriorPoint Methods, Conic Linear Programming, Distributionally Robust Optimization, Online Linear Programming and Learning, Algorithm Analyses for Reinforcement Learning&Markov Decision Process and nonconvex optimization, and etc. He and his students have received numerous scientific awards, himself including the 2006 INFORMS Farkas Prize (Inaugural Recipient) for fundamental contributions to optimization, the 2009 John von Neumann Theory Prize for fundamental sustained contributions to theory in Operations Research and the Management Sciences, the inaugural 2012 ISMP Tseng Lectureship Prize for outstanding contribution to continuous optimization (every three years), the 2014 SIAM Optimization Prize awarded (every three years), etc. According to Google Scholar, his publications have been cited over 60,000 times.

Biography

Prof. Simone Rossi received his MSc in Electronic Engineering from Politecnico di Torino and his MSc in Computer Engineering from Telecom ParisTech, and he received his PhD in Computer Science from Sorbonne University, Paris. Simone is currently an Assistant Professor at EURECOM and in his works he focuses on scalable uncertainty quantification methods applied to large neural networks models. Before joining EURECOM, Simone was a Research Scientist at Stellantis, France, where he supervised several research projects, including on large language models, co-authoring 10+ patents 

Biography

Simon Lucas is a full professor of AI in the School of Electronic Engineering and Computer Science at Queen Mary University of London where he leads the Game AI Research Group.  He was previously Head of School of EECS at QMUL.  He recently spent two years as a research scientist / software engineer in the Simulation-Based Testing team at Meta, applying simulation-based AI to automated testing. Simon was the founding Editor-in-Chief of the IEEE Transactions on Games and co-founded the IEEE Conference on Games, was VP-Education for the IEEE Computational Intelligence Society and has served in many conference chair roles.  His research is focused on simulation-based AI (e.g. Monte Carlo Tree Search, Rolling Horizon Evolution), bandit-based optimisation, and LLMs.

Biography

Jia Li is the co-founder of Project Numina, a non-profit open scientific collaboration working on fostering the development of human and artificial intelligence in the field of mathematics. In July 2024, Numina’s math LLM won the AI MO progress prize and released publicly the largest dataset of mathematical problems and proofs. Before Numina, Jia co-founded Cardiologs Technologies, a French Medtech company that pioneered the application of machine learning, deep learning and signal processing in ECG analysis and that was acquired by Philips in 2021. Jia holds a degree in Applied Mathematics from Telecom ParisTech and Ecole Polytechnique Paris (X), specializing in Computer Vision and Machine Learning. 

Biography

Bertrand Charpentier is the co-founder, President and Chief Scientist Officer at Pruna AI, a company focused on making AI models more efficient, sustainable, and accessible. They already compressed thousands of models to make them faster, smaller, cheaper, greener by combining compression methods, making them the #1 contributor on Hugging Face. Bertrand did his Ph.D. in Machine Learning at the Technical University of Munich (TUM) and research at Twitter, Stanford, or Télécom Paris where he created the scikit-network package and published influential papers at NeurIPS, ICML, and ICLR on the topic of efficient and reliable AI. His work in cover machine learning models across various domains, including computer vision, natural language processing, graphs, and molecular prediction.

Biography

Lina Bariah received the  Ph.D. degree in communications engineering from Khalifa University, Abu Dhabi, UAE, in 2018. She was a Visiting Researcher with the Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada, in 2019, and an aOiliate research fellow, James Watt School of Engineering, University of Glasgow, UK. She was a Senior Researcher at the technology Innovation institute, and a Lead AI Scientist at Open Innovation AI. She is currently an Adjunct Professor at Khalifa University, and an Adjunct Research Professor, Western University, Canada. Dr. Bariah serves as the Industry Chair for GenAINet ETI. Dr. Bariah is a senior member of the IEEE, IEEE Communications Society, IEEE Vehicular Technology Society, and IEEE Women in Engineering. She is the founder and lead of Women in Machine Learning and Data Science (WiMLDS)-Abu Dhabi Chapter. She was recently listed among the 100 Brilliant and Inspiring Women in 6G", by Women in 6G organization. She has authored/co-authored 80+ research papers/book chapters in highly ranked journals and flagship conferences. She is currently an Editor at IEEE Transactions on Wireless Communications. Her research area includes Generative AI for Telecom, Large Language Models, and AI for communications.