ELLIS - European Laboratory for Learning and Intelligent Systems

🗺️🔍 Discover the ELLIS Sites – today we’re highlighting the ELLIS Unit Vienna, based at the Institute of Science and Technology Austria 🇦🇹 (ISTA). Their mission emphasizes academic freedom, fostering an environment where curiosity-driven research thrives, leading to scientific excellence in the field of ML. Take a look at the highlights below to see how Unit Vienna is making an impact. For example learn how they: 🤝 team up with xista - the innovation and tech transfer hub of ISTA - to give members access to powerful computing resources 📢 hosted last year's ICML conference 👫 actively support in-person research collaborations right on site 💡To get the full scoop of ELLIS Unit Vienna's achievements and latest research highlights read the complete article here: https://lnkd.in/eqN2skVg

Meet Ivona Najdenkoska, Postdoctoral Researcher at the University of Amsterdam 🇳🇱. Her area of research covers multimodal foundation models, developing efficient methods for vision-language understanding and generative tasks. Learn more about one of her career highlights and the advice she shares for young scientists. ✨ ✨ ✨ #WomenInELLIS We're spotlighting women in ELLIS in 2025: celebrating their achievements, leadership, guidance, and innovation in the exciting fields of AI and machine learning across Europe.

💬 UCL AI Centre and ELLIS Seminar on a novel method for unbiased density estimation in Bayesian inference coming up next Monday, March 17! Nicolas Chopin (Professor of Statistics at ENSAE Paris) will present "Saddlepoint Monte Carlo and its application to exact ecological inference". This talk introduces a novel method for unbiased density estimation in Bayesian inference, enabling more accurate analysis of complex aggregate data. The approach is particularly valuable for ecological inference, where only aggregate-level observations are available - such as election data. Nicolas Chopin will demonstrate how this technique improves inference on voter behavior in French elections, revealing key insights into vote transfers between rounds. This method has broader implications for privacy-preserving data analysis and inverse problems. Don’t miss this opportunity to explore state-of-the-art Bayesian computation with one of the field’s leading experts! 📅 March 17, 2025 ⏰ 13:00–14:00 GMT 🎤 Speaker: Prof. Nicolas Chopin (ENSAE, Paris) 📍 Format: Hybrid 🔗 Learn more and register here: https://lnkd.in/euzKQS8Z

Get to know Gül Varol, Senior Researcher at Ecole des Ponts ParisTech 🇫🇷. She's an ELLIS Scholar and member of the ELLIS Unit Paris. Winner of one of the first ELLIS PhD Awards in 2020, her area of research covers computer vision, vision and language, video analysis, human motion generation and sign languages. Flip through the carousel to find out her advice for young scientists. ✨ ✨ ✨ #WomenInELLIS We're spotlighting women in ELLIS in 2025: celebrating their achievements, leadership, guidance, and innovation in the exciting fields of AI and machine learning across Europe.

⁉️ Join the ELIAS 1st Open Call Q&A session to learn how your AI project for sustainability and societal impact could secure up to €60,000 in funding. Connect with the ELIAS team on March 26, 2025, at 10 AM (CET) via Zoom - no registration needed!

💬 Join TODAY’s webinar: “Symmetry, scale, and science: A geometric path to better AI” with Erik Bekkers (Universiteit van Amsterdam) & Johannes Brandstetter (Emmi AI, Johannes Kepler Universität Linz) ⚡ The talk by Erik Bekkers (Director of the ELLIS Program “Geometric Deep Learning”) and Johannes Brandstetter will explore integrating geometric deep learning principles, such as symmetry and equivariance, into neural architectures to enhance reliability and data efficiency in scientific applications. It will highlight methods for learning geometric latent representations that maintain essential symmetries, facilitating accurate geometric reasoning and physical modeling. Additionally, the talk will showcase scalable architectures like NeuralDEM and NeuralCFD, capable of real-time simulations in complex systems, including particulate flows and automotive aerodynamics. These approaches aim to balance the preservation of geometric structures with the scalability required for large-scale scientific computations. 🗓️ Mon, March 10, 2025 🕓 16:00-17:00 CET 🎤 Erik Bekkers & Johannes Brandstetter 🔗 Register here: https://lnkd.in/e8gRwrNq This talk is part of the new AI for Good webinar series “From Molecules to Models”, highlighting significant contributions from various ELLIS Programs in the field of AI for life sciences.

This International Women's Day, we're challenging you to #AccelerateAction to get more women and girls working in and studying AI and machine learning. It's your turn! Leave a suggestion for action in the comments or tag an inspiring female scientist. #IWD2025 #AccelerateAction #WomenInELLIS

Hey ELLIS PhD students, need to travel but low on funds? Learn how ELSA – European Lighthouse on Secure and Safe AI can help with that.

Say hello to Prof. Dr. Natasa Przulj, Professor at MBZUAI (Mohamed bin Zayed University of Artificial Intelligence) 🇦🇪 and affiliated with ICREA 🇪🇸 and UCL 🏴󠁧󠁢󠁥󠁮󠁧󠁿 . She is an ELLIS Fellow and member of the ELLIS Unit Barcelona. She is a leader in AI and Machine Learning algorithms for multi-omic data analysis and fusion applied to precision medicine. In 2017, she was appointed as a member of the Academia Europaea, and last year was elected a Fellow of ISCB - International Society for Computational Biology. 👏 ✨ ✨ ✨ #WomenInELLIS We're spotlighting women in ELLIS in 2025: celebrating their achievements, leadership, guidance, and innovation in the exciting fields of AI and machine learning across Europe.

🏹 Job alert: The Department of Engineering at the University of Cambridge is seeking a University Assistant Professor in Machine Learning. The successful candidate will join the Computational and Biological Learning Lab (CBL) in the Information Engineering Division. CBL combines expertise in machine learning with computational neuroscience. The candidate will lead a research programme in one or more of the following areas: machine learning, decision making, and theory and practice of deep learning. 📍 Cambridge, England 📅 Apply by 16 March 2025 🔗 Get details at https://lnkd.in/evaSn-2Q