Télécom Paris PhD researcher Ali Keshavarzi reveals how AI can model the lungs more accurately, using fewer annotated scans, by combining deep learning with frugal, topology-aware techniques.
Hi! PARIS launched the International Visiting Chairs program in December 2024 to support international scientific collaboration. The program invites researchers from institutions abroad to spend time working with research teams affiliated with Hi! PARIS member schools in France. For 2025, we are welcoming seven international visiting professors. Each will collaborate on a specific project in artificial intelligence or data science, hosted by a Hi! PARIS researcher. Meet the 2025 Visiting Chairs: Alessandro VinciarelliProject: Socially Intelligent Multimodal Conversation AnalysisHost: Mounim El Yacoubi, Télécom SudParis Alexei EfrosProject: Discovering Typical Visual Structures in Large Image Collections with Diffusion ModelsHost: Mathieu Aubry, ENPC Andréas NüchterProject: Universal Semantic Mapping for Outdoor and Underwater EnvironmentsHost: François Goulette, ENSTA Dimitris SamarasProject: Human Attention-Guided Video RepresentationsHost: Vicky Kalogeiton, École polytechnique Eric XingProject: Multiscale Foundation Models for Predicting, Simulating, and Programming Biology at All LevelsHosts: Eric Moulines & Alain Durmus, École polytechnique Milan MiricProject: Identifying US, Chinese, and European AI Technologies: Extending Patent Databases Using Novel Data and ApproachesHost: Mickael Impink, HEC Paris Thibaut VidalProject: Trustworthy and Decision-Focused LearningHost: Axel Parmentier, ENPC This initiative reflects our core values of openness, excellence, and cross-border collaboration. By welcoming top researchers into our ecosystem, we aim to accelerate innovation and contribute to advance the global conversation around responsible and impactful AI.
In April 2025, Hi! PARIS researchers were recognized at two major international conferences in Artificial Intelligence. From April 6 to 11, the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) highlighted breakthroughs in signal processing, audio, and speech technologies. Later, from April 24 to 28, the International Conference on Learning Representations (ICLR), the premier gathering for experts advancing the field of representation learning brought together leading minds in machine learning and deep learning. Across both events, 41 research papers by Hi! PARIS-affiliated teams were accepted, underscoring the center’s commitment to cutting-edge, interdisciplinary research in AI and data science. Congratulations to our researchers! List of papers accepted at ICASSP and ICLR 2025 Conference Title Hi! PARIS Authors All Authors ICLR 2025 Probabilistic Conformal Prediction with Approximate Conditional Validity Eric Moulines Vincent Plassier, Alexander Fishkov, Mohsen Guizani, Maxim Panov, Eric Moulines ICLR 2025 From Risk to Uncertainty: Generating Predictive Uncertainty Measures via Bayesian Estimation Eric Moulines Nikita Kotelevskii, Vladimir Kondratyev, Martin Takáč, Eric Moulines, Maxim Panov ICLR 2025 Variational Diffusion Posterior Sampling with Midpoint Guidance Yazid Janati el idrissi, Lisa Bedin, Alain Oliviero Durmus, randal douc, Eric Moulines Badr MOUFAD, Yazid Janati el idrissi, Lisa Bedin, Alain Oliviero Durmus, randal douc, Eric Moulines, Jimmy Olsson ICLR 2025 Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson–Romberg Extrapolation Alain Oliviero Durmus, Eric Moulines Marina Sheshukova, Denis Belomestny, Alain Oliviero Durmus, Eric Moulines, Aleksei Naumov, Sergey Samsonov ICLR 2025 Imputation for prediction: beware of diminishing returns Gael Varoquaux Marine Le Morvan, Gael Varoquaux ICLR 2025 Learned Reference-based Diffusion Sampler for Multi-Modal Distributions Alain Oliviero Durmus Maxence Noble, Louis Grenioux, Marylou Gabrié, Alain Oliviero Durmus ICLR 2025 Denoising Levy Probabilistic Models Alain Oliviero Durmus Dario Shariatian, Umut Simsekli, Alain Oliviero Durmus ICLR 2025 Watermark Anything With Localized Messages Alain Oliviero Durmus Tom Sander, Pierre Fernandez, Alain Oliviero Durmus, Teddy Furon, Matthijs Douze ICLR 2025 Building Blocks of Differentially Private Training Aymeric Dieuleveut Mahmoud Hegazy, Aymeric Dieuleveut ICLR 2025 Tailoring Mixup to Data for Calibration Florence d’Alché-Buc Quentin Bouniot, Pavlo Mozharovskyi, Florence d’Alché-Buc ICLR 2025 Restyling Unsupervised Concept Based Interpretable Networks with Generative Models Florence d’Alché-Buc Jayneel Parekh, Quentin Bouniot, Pavlo Mozharovskyi, Alasdair Newson, Florence d’Alché-Buc ICLR 2025 Long-time Asymptotics of Noisy SVGD Outside the Population Limit Pascal Bianchi Victor Priser, Pascal Bianchi, Adil Salim ICLR 2025 Solving Differential Equations with Constrained Learning Luiz Chamon Viggo Moro, Luiz Chamon ICLR 2025 Simple ReFlow: Improved Techniques for Fast Flow Models Marco Cuturi Beomsu Kim, Yu-Guan Hsieh, Michal Klein, Marco Cuturi, Jong Chul YE, Bahjat Kawar, James Thornton ICLR 2025 Controlling Language and Diffusion Models by Transporting Activations Marco Cuturi Pau Rodriguez, Arno Blaas, Michal Klein, Luca Zappella, Nicholas Apostoloff, Marco Cuturi, Xavier Suau ICLR 2025 Disentangled Representation Learning with the Gromov-Monge Gap Marco Cuturi Théo Uscidda, Luca Eyring, Karsten Roth, Fabian Theis, Zeynep Akata, Marco Cuturi ICLR 2025 An Illustrated Guide to Automatic Sparse Differentiation Guillaume Dalle Adrian Hill, Guillaume Dalle, Alexis Montoison ICLR 2025 Towards Understanding Why Label Smoothing Degrades Selective Classification and How to Fix It Gianni Franchi Guoxuan Xia, Olivier Laurent, Gianni Franchi, Christos-Savvas Bouganis ICLR 2025 Last-Iterate Convergence Properties of Regret-Matching Algorithms in Games Julien Grand-Clément Yang Cai, Gabriele Farina, Julien Grand-Clément, Christian Kroer, Chung-Wei Lee, Haipeng Luo, Weiqiang Zheng ICLR 2025 Provable Convergence and Limitations of Geometric Tempering for Langevin Dynamics Anna Korba, Austin Stromme Omar Chehab, Anna Korba, Austin Stromme, Adrien Vacher ICLR 2025 NextBestPath: Efficient 3D Mapping of Unseen Environments Vincent Lepetit Shiyao Li, Antoine Guedon, Clémentin Boittiaux, Shizhe Chen, Vincent Lepetit ICLR 2025 Understanding Virtual Nodes: Oversquashing and Node Heterogeneity Johannes Lutzeyer Joshua Southern, Francesco Di Giovanni, Michael Bronstein, Johannes Lutzeyer ICLR 2025 Restyling Unsupervised Concept Based Interpretable Networks with Generative Models Pavlo Mozharovskyi, Florence d’Alché-Buc Jayneel Parekh, Quentin Bouniot, Pavlo Mozharovskyi, Alasdair Newson, Florence d’Alché-Buc ICLR 2025 Tailoring Mixup to Data for Calibration Pavlo Mozharovskyi, Florence d’Alché-Buc Quentin Bouniot, Pavlo Mozharovskyi, Florence d’Alché-Buc ICLR 2025 AtomSurf: Surface Representation for Learning on Protein Structures Maks Ovsjanikov Vincent Mallet, Yangyang Miao, Souhaib Attaiki, Bruno Correia, Maks Ovsjanikov ICLR 2025 Feature-Based Online Bilateral Trade Vianney Perchet Solenne Gaucher, Martino Bernasconi, Matteo Castiglioni, Andrea Celli, Vianney Perchet Conference Title Hi! PARIS Authors All Authors ICASSP 2025 A Hybrid Model for Weakly-Supervised Speech Dereverberation Mathieu Fontaine, Gaël Richard Louis Bahrman, Mathieu Fontaine, Gaël Richard ICASSP 2025 AnCoGen: Analysis, Control and Generation of Speech with a Masked Autoencoder Gaël Richard Samir Sadok, Simon Leglaive, Laurent Girin, Gaël Richard, Xavier Alameda-Pineda ICASSP 2025 Contrastive Knowledge Distillation for Embedding Refinement in Personalized Speech Enhancement Mathieu Fontaine, Slim Essid Thomas Serre, Mathieu Fontaine, Éric Benhaim, Slim Essid ICASSP 2025 F-STRIPE: Fast Structure-Informed Positional Encoding for Symbolic Music Generation Gaël Richard Manvi Agarwal, Changhong Wang, Gaël Richard ICASSP 2025 Investigating the Sensitivity of Pre-trained Audio Embeddings to Common Effects Gaël Richard Victor Deng, Changhong Wang, Gaël Richard, Brian McFee ICASSP 2025 Learning Source Disentanglement in Neural Audio Codec Gaël Richard Xiaoyu Bie, Xubo Liu, Gaël Richard ICASSP 2025 Masked Latent Prediction and Classification for Self-Supervised Audio Representation Learning Geoffroy Peeters, Slim Essid Aurian Quelennec, Pierre Chouteau, Geoffroy Peeters, Slim Essid ICASSP 2025 Multiple Choice Learning for Efficient Speech Separation with Many Speakers David Perera, Gaël Richard, Slim Essid David Perera, François Derrida, Théo Mariotte, Gaël Richard, Slim Essid ICASSP 2025 O-EENC-SD: Efficient Online End-to-End Neural Clustering for Speaker Diarization Mathieu Fontaine, Slim Essid Elio Gruttadauria, Mathieu Fontaine, Jonathan Le Roux, Slim Essid ICASSP 2025 Perceptual Noise-Masking with Music through Deep Spectral Envelope Shaping Roland Badeau, Slim Essid Clémentine Berger, Roland Badeau, Slim Essid ICASSP 2025 Re-Evaluating Privacy in Centralized and Decentralized Learning: An Information-Theoretical and Empirical Study Changlong Ji, Stephane Maag Changlong Ji, Richard Heusdens, Stephane Maag, Qiongxiu Li ICASSP 2025 Standardization Status of MPEG Video-based Dynamic Mesh Coding (V-DMC) Marius Preda Wenjie Zou, Shizhuo Zhang, Fuzheng Yang, Marius Preda ICASSP 2025 Targeted Data Poisoning for Black-Box Audio Datasets Ownership Verification El-Mahdi El-Mhamdi Wassim Wes Bouaziz, El-Mahdi El-Mhamdi, Nicolas Usunier ICASSP 2025 Twenty-Five Years of MIR Research: Achievements, Practices, Evaluations, and Future Challenges Geoffroy Peeters
In February 2025, nearly five years after the creation of the Center, we hosted a dinner to thank our corporate donors for their continued support and commitment. It was an opportunity to reflect on the progress we’ve made together and to reaffirm the importance of the partnerships that have helped shape Hi! PARIS into what it is today. When Hi! PARIS was launched in 2020 by Institut Polytechnique de Paris and HEC Paris, and later joined by Inria, CNRS, and UTT, the goal was clear: to build an ambitious and internationally visible center for research, education, and innovation in artificial intelligence and data science. From the beginning, our corporate donors have played a central role in supporting this vision, not only financially, but also intellectually, by sharing their priorities and contributing to the development of our initiatives, research agenda, and educational programs. Pictured from left to right: Éloïc Peyrache, Dean of HEC Paris; Thierry Coulhon, President of Institut Polytechnique de Paris; Philippe Baptiste, French Minister for Research and Higher Education and Michael I. Jordan, Professor at UC Berkeley. Over the past five years, these partnerships have enabled us to launch and fund research projects at the crossroads of science, business, and society; support chair holders, fellows, postdoctoral researchers, and PhD students working on key AI challenges; host events that connect academic and industrial communities; and develop interdisciplinary teaching programs to train the next generation of AI and data talent. These achievements would not have been possible without the trust and involvement of our donors. Together, we’ve helped build a center that stands for scientific excellence, responsible innovation, and collaboration across sectors. https://www.youtube.com/watch?v=CrEHR_vHhcg A committed community of donors The strength of Hi! PARIS lies not only in its academic and scientific foundations, but also in the commitment of its corporate donors. Partners such as L’Oréal, Capgemini, TotalEnergies, VINCI, and Schneider Electric bring a diverse range of perspectives from industry, technology, and energy to infrastructure and innovation united by a shared belief: that artificial intelligence and data science must be developed in a way that serves society. Each of them brings a unique perspective, and their support goes far beyond funding. They contribute ideas, challenge us to stay relevant, and help us anchor our work in the real world. This richness of backgrounds and their shared values of excellence, responsibility, and openness reinforce Hi! PARIS’s mission to bridge science, business, and society. One of the most concrete illustrations of this collaboration is our white book Visions of Business: Driving Business Innovation with Data & AI. This 48-page publication brings together real-world use cases from our corporate donors and highlights how they are leveraging AI to address key challenges in beauty, energy, retail, infrastructure, and beyond. Pictured from left to right: Jean-Paul Agon, Chairman of the Board at L’Oréal; Laurent Bataille, President of Schneider Electric France; Philippe Rambach, Chief AI Officer at Schneider Electric; Delphine Colson, Executive Director of the HEC Foundation; Marie-Noëlle Semeria, Chief Innovation Officer at TotalEnergies; Céline Brucker, General Manager at L’Oréal France; Joëlle Barral, Director of Research at Google DeepMind; and Julia Peyre, Head of AI Strategy and Innovation at Schneider Electric. Building the future of AI together The scientific perspectives opened by the researchers, professors, and students involved in Hi! PARIS require resources that match their ambition. The trust and engagement of our partners are essential to sustaining this effort. As we look ahead, we remain committed to deepening these relationships and continuing to work hand in hand to address the evolving challenges of artificial intelligence. From sustainability to trustworthy AI, from ethics to real-world applications, we believe the conversation between researchers and industry has never been more essential. The anniversary dinner was a warm and meaningful moment a way to celebrate what we’ve built together and to thank each partner, personally, for believing in our mission. To all our donors: thank you for your support, your time, and your ideas. We look forward to the next chapter and to continuing this journey with you.
The EU Artificial Intelligence Act (AI Act) is the world’s most comprehensive attempt to regulate artificial intelligence, but as Gabriele Mazzini one of its original drafters reminded the audience at the Hi! PARIS Meet Up on the AI Act, it’s also a work in progress. In his talk, Mazzini walked through the logic of the Act, its risk-based foundation, and how recent events have transformed its scope. His reflections offered both a behind-the-scenes view and a forward-looking critique. Why the AI Act focuses on what you do, not what you build The original draft of the AI Act, developed by the European Commission in 2021, was guided by a clear principle: regulate not the technology, but its applications. The idea was to focus on how AI is used, not what it is. As Mazzini explained, this meant identifying risk levels and aligning them with regulatory obligations. Three categories of risk were defined: Prohibited AI applications, such as social scoring or exploitative and manipulative AI. One of the most controversial proposals involved restricting remote biometric identification systems in public spaces. High-risk systems, the heart of the regulation, accounting for around 98% of the legal provisions. These systems would be subject to compliance, certification, and CE marking, similar to how medical devices are regulated. Transparency obligations for systems like chatbots, where the law requires users to be informed when interacting with an AI. According to Mazzini, this is not just a technical issue, it’s about human dignity and respecting the way people relate to machines. Gabriele Mazzini, Architect of the EU AI Act and Research Affiliate at MIT Media Lab | Hi! PARIS Meet Up on the AI Act at VINCI (March 2025) The turning point: ChatGPT and the U.S. influence The final version of the Act preserved the risk-based structure, but it was significantly influenced by two external events: The launch of ChatGPT in October 2022, and the Executive Order on AI from the Biden administration in October 2023, which introduced rules for dual-use foundation models. Together, these developments pushed EU legislators to expand the scope of the AI Act to cover not just applications, but AI tools themselves, especially general-purpose AI models, also known as foundation models. This new chapter introduced two rule sets: Transparency for all models, including documentation requirements and obligations to share information downstream, particularly regarding copyright compliance. Additional obligations for models with systemic risk, including risk assessment, incident reporting, and cybersecurity measures. To determine systemic risk, regulators proposed two criteria: The computational power used in training (mirroring U.S. thresholds like 10^26 FLOPs). And the designation by the AI Office, part of the European Commission, following an approach similar to the Digital Services Act. These rules apply even to open-source foundation models, though some exceptions are allowed. The AI Act isn’t what it started as Since the first draft, the AI Act has changed quite a bit, not just in terms of content, but also in overall complexity. Mazzini pointed out that the number of prohibited use cases has gone from four to eight, with new ones like emotion recognition and categorization, which he described as “vague” and “too broad.” The list of high-risk applications hasn’t exploded, but it’s expanded enough to make compliance more demanding. One big shift is that the regulation doesn’t just focus on applications anymore, it now also covers the AI models and tools themselves. When it comes to general-purpose AI, a lot of the specifics are still being worked out through voluntary codes of practice. That’s led to some debate, especially after a recent letter from EU lawmakers raised concerns about whether those codes are enough to keep up with fast-evolving risks. Meanwhile, governance structures have gotten more complex, both at the EU level and within member states, partly because of the broader scope that now includes general-purpose models. Another important point is the new set of obligations for companies. What used to be called “users” are now “deployers,” and they have more responsibilities, like doing fundamental rights impact assessments and sharing more information. Lastly, Mazzini mentioned that the overlap between the AI Act and other EU laws still isn’t totally clear, and how these different legal frameworks will work together is still being figured out. Hi! PARIS Meet Up on the AI Act at VINCI (March 2025) Less would have been more: Mazzini’s assessment In closing, Mazzini offered a candid reflection: “Less would have been more.” He acknowledged the ambition of the AI Act but emphasized the importance of legal clarity, both for operators who need to comply and regulators who must enforce it. What should come next? Clarity and legal certainty, businesses must understand what they’re required to do, and enforcement must be consistent across EU member states. Sensible interpretations, regulators and courts should aim for realistic, state-of-the-art, and innovation-friendly readings of the law. Harmonized standards, especially for SMEs that lack resources to develop compliance mechanisms on their own. Use-case-based advocacy, companies should engage proactively, using their real-world cases to shape practical interpretations. Impact monitoring, we need data on how the AI Act is working. Is it increasing trust? Creating confusion? Encouraging innovatio or stifling it? “We are dealing with a fast-moving technology,” Mazzini said. “The law matters but so does how we interpret and implement it.” In his view, transparency, pragmatism, and responsiveness will be key to ensuring that the AI Act delivers on its promise without hindering Europe’s AI ecosystem. https://www.youtube.com/watch?v=-jeiKEp-_sM
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
Hi! PARIS is proud to co-organize CVPR@Paris 2025, a one-day local event designed as an inclusive and sustainable alternative to the CVPR conference, traditionally held in the U.S. Taking place on June 6, 2025, in the heart of Paris, the event will bring together researchers, students, and authors of accepted papers at CVPR 2025, CVPR workshops, and other major conferences (such as ICLR 2025) to present their work through oral talks and poster sessions. Each year, the CVPR conference (Computer Vision and Pattern Recognition) ranks among the most prestigious conferences in artificial intelligence globally. However, its regular location in North America limits access for many researchers based in Europe and raises questions around the environmental impact of long-distance academic travel. CVPR@Paris addresses this challenge by offering an opportunity to gather locally while still sharing the latest scientific advances. This event is co-organized by Hi! PARIS and SCAI (Sorbonne Center for AI). Why attend? Encourage knowledge-sharing among the local and European AI community Discover the latest breakthroughs in deep learning and computer vision Support a more accessible and sustainable scientific culture Register and learn more here Committees General ChairsMatthieu Cord (Sorbonne University) Vicky Kalogeiton (École Polytechnique, IP Paris) David Picard (École Nationale des Ponts et Chaussée, IP Paris) Program ChairsMustafa Shukor (Sorbonne University) Raphael Baena (École des Ponts ParisTech, ENPC) The organizing committee includes researchers from Sorbonne University, École polytechnique, and École des Ponts ParisTech, demonstrating once again the collaborative spirit of the Paris AI ecosystem. For any questions, feel free to contact: cvprinparis@gmail.com
Beyond his role as Deputy Director of the Computer Science and Systems Engineering Unit (U2IS) at ENSTA, François Goulette has a strong interest in AI ethics. Each summer, he leads a short awareness module on this topic as part of the Hi! PARIS Data Boot Camp, a program offered to students of Institut Polytechnique de Paris and HEC Paris.
Hi! PARIS, the interdisciplinary research center dedicated to artificial intelligence (AI) and data science, founded by HEC Paris and the Institut Polytechnique de Paris (IP Paris), enters a new phase of development with the arrival of Vincent Rapp as its Executive Director. Previously a Special Advisor on Artificial Intelligence to the French Ministry of AI and Digital Affairs, Vincent Rapp takes over from Raphaëlle Gautier and will lead the center’s strategic direction at a pivotal moment in its growth. His appointment follows Hi! PARIS’s recent designation as an AI Cluster, solidifying its position as a leading institution in AI and data science research. A vision for AI excellence and innovation With a strong background in AI strategy, research, and public policy, Vincent Rapp aims to further strengthen Hi! PARIS’s excellence in artificial intelligence and data science while expanding new initiatives to foster innovation and collaboration between academia, industry, and public institutions. His mission is clear: to position Hi! PARIS as a leading European and global hub for AI research, education, and innovation. “Hi! PARIS’s recognition as an AI Cluster under the France 2030 program confirms the outstanding quality and international visibility of our academic ecosystem in AI and data science. Vincent Rapp’s appointment marks a key milestone in the center’s development, reinforcing our ambition to train 20,000 students in AI by 2030.” – Thierry Coulhon (President of the Executive Board of IP Paris) & Eloïc Peyrache (Dean of HEC Paris) A career dedicated to AI and innovation Vincent Rapp holds an MSc from Sorbonne University and a PhD in Artificial Intelligence from ISIR (Institute for Intelligent Systems and Robotics). His career spans both public and private sectors, focusing on AI research, strategy, and innovation. He began his career at the French National Research Agency (ANR), where he played a key role in launching the Interdisciplinary Institutes for Artificial Intelligence (3IA). At Bpifrance, he served as Head of AI Innovation & Strategy, shaping national AI initiatives. In October 2024, he was appointed Special Advisor on AI to the French Ministry of AI and Digital Affairs, working on AI policy and innovation strategies. A multidisciplinary leadership for the future Vincent Rapp joins an established scientific leadership team, with Gaël Richard (Télécom Paris) and Éric Moulines (École Polytechnique & Académie des Sciences) continuing to lead Hi! PARIS’s scientific strategy. The center also relies on its research, education, and innovation committees, ensuring a comprehensive and forward-thinking approach to its future development. “Artificial intelligence is at a turning point. Between technological breakthroughs and regulatory challenges, it is essential to build strong bridges between research, education, and industry. Thanks to its unique academic ecosystem, the support of visionary corporate sponsors, and public funding, Hi! PARIS has an exceptional opportunity to develop AI that is high-performing, responsible, and impactful for society. To achieve this, we must strengthen collaborations and develop new public-private partnerships to amplify our collective impact.” – Vincent Rapp, Executive Director of Hi! PARIS Hi! PARIS is supported by a unique academic ecosystem, bringing together HEC Paris and the Institut Polytechnique de Paris (École Polytechnique, ENSTA Paris, ENPC, ENSAE, Télécom Paris, Télécom SudParis), alongside leading research institutions such as Inria, CNRS, and Université de Technologie de Troyes. The center also benefits from the backing of visionary corporate sponsors, including L’Oréal, Capgemini, TotalEnergies, VINCI, and Schneider Electric. Under the leadership of Vincent Rapp, Hi! PARIS is set to accelerate its impact in AI research, talent development, and industry collaboration, shaping the future of artificial intelligence in France and beyond. Read the Press Release
The Hi! PARIS Meet Up! event organized by Hi! PARIS is about the “AI Act”. Save-the date: March 25, 2025 (6:00-8:30 pm), hosted by our corporate donor VINCI.