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AI Seminar Cycle

AI Seminar Cycle

About the Seminars The Hi! PARIS AI Seminar Cycle is a monthly seminar series bringing together leading voices in Artificial Intelligence and Data Science. Held on the first Wednesday of each month, these seminars showcase pioneering research from world-class scholars and offer a space for exchange across disciplines. By opening the discussions to students, faculty, and partners, the series highlights the diversity of approaches within AI and fosters dialogue on its scientific, business, and societal impact. Each seminar is anchored in Hi! PARIS’s strategic scientific themes, covering key areas such as AI theory and methods, generative and foundation models, trustworthy and sustainable AI, AI in cyberphysical systems and robotics and more. Together, these themes guide the exploration of both the foundations of AI and its transformative applications. Organization Attendance is free but requires prior registration due to access restrictions. Please use the registration link below to confirm your participation. Even if you’re not certain yet, we encourage you to register in advance to secure your spot. Upcoming sessions Xiao-Li Meng, Harvard University No Free Lunch: From a Simultaneous (Machine) Learning Impossibility to Heisenberg Uncertainty Principle Thursday, October 2 (2 PM – 3:30 PM) – Hybrid: Amphitheater Becquerel, École polytechnique (Click to register) I Online Personal Webpage Elisa Ricci, University of Trento (Hi! PARIS SAB Member) Research Session on Vision Wednesday, November 5 (11 AM – 12 PM) – Online (click to register) Personal Webpage Pavel Izmailov, New York University Exploring Bayesian Methods Wednesday, December 10 (11 AM – 12 PM) – Online (click to register) Personal Webpage Oriane Siméoni, valeo.ai Research Session on Vision Wednesday, February 4 (11 AM – 12 PM) – Online (click to register) Personal Webpage Francis Bach, Inria Research Session on Machine learning Wednesday, June 3 (11 AM – 12 PM) – Online (click to register) Personal Webpage Scientific Committee Rémi Flamary (École polytechnique) Gaël Richard (Hi! PARIS Scientific Director, Télécom Paris) Eloïse Berthier (ENSTA) Adriana Tapus (ENSTA) Radu-Alexandru Dragomir (Télécom Paris) Mathieu Fontaine (Télécom Paris) Florence d’Alché (Télécom Paris) Aymeric Dieuleveut (École polytechnique) Gianni Franchi (ENSTA)

Highlight Research Teaching

Apply Now: 2025/26 Hi! PACE Teaching Roles Available

As part of the Hi! PARIS Cluster 2030 initiative, the Hi! PACE (Programs, Academia, and Course Expansion) positions for the 2025/26 academic year are now open. These positions are the result of a coordinated effort across partner institutions to identify and prioritize teaching and program development needs in artificial intelligence and data science.  The positions are aimed at strengthening our academic offering, supporting new program launches, and responding to the growing demand for excellence in AI education. What’s next? Partner institutions can now proceed with recruitment for the listed positions. The roles cover a range of teaching and academic support needs, and are aligned with Hi! PARIS’s strategic vision for inclusive, interdisciplinary, and high-impact education in AI. Open Positions: Artificial Intelligence – ECC (4-year contract) – Université de Téchnologie de TroyesApply here Data Science – ECC (4-year contract) – Université de Téchnologie de TroyesApply here Statistical Learning – Assistant Professor (3+2 years) – ENPCApply here Trustworthy & Responsible AI / RL – Assistant Professor (permanent) – École PolytechniqueApply here Multimodal AI – Monge Assistant Professor (tenure track, 3+3 years) – École PolytechniqueApply here AI for Insurance – Assistant Professor (tenure track) – CRESTApply here Stay tuned for further updates as the Hi! PACE initiative continues to grow. For any questions, please contact: contact@hi-paris.fr

Innovation Research Teaching

The Emerging Science of Benchmarks: Moritz Hardt on AI’s Open-Ended Progress

This keynote, given by Moritz Hardt at the Hi! PARIS Summer School 2024, explores the role of benchmarks in artificial intelligence. Hardt talks about how benchmarks are key to guiding AI research and measuring progress in a field that is always changing. As AI grows, so do benchmarks, bringing up important questions about how to best measure and direct future developments.

Teaching Visibility

NEW MOOC: The AI Odyssey- History, Regulations and Impact: A European Perspective

Explore the world of AI with Hi! PARIS’s latest MOOC, offering insights into AI’s origins, regulatory landscape, industry performance, and societal impact. This 4-week course, featuring expert-led videos and quizzes, is open to everyone, with no prerequisites. Gain a solid foundation in AI’s role in shaping the future of technology and society.
Enroll today to start your journey into AI!

Innovation Research Teaching Visibility

Hi! PARIS WINS THE CALL FOR PROJECTS CLUSTER AI

Judged on its excellence regarding teaching, research, innovation and technological transfer, as well as on the variety of its training, the consortium led by HEC Paris and the Institut Polytechnique de Paris (École polytechnique, ENSTA, ENSAE, Telecom Paris, Telecom SudParis) and bringing together Inria, the CNRS, the Ecole Nationale des Ponts et Chaussées and the Université de Technologie de Troyes, wins the Project Call Cluster AI.