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MaLGa Colloquia Series 2026

29/01/2026

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We are thrilled to present the MaLGa Colloquia Series 2026, a cycle of seminars exploring recent advances in artificial intelligence and machine learning.


The series is open to students, researchers, faculty, professionals, and anyone interested in Machine Learning and Artificial Intelligence. Each colloquium features internationally recognized speakers from leading universities and research centers.


Talks combine high-level research with accessible introductions, followed by an interactive Q&A. Each event ends with an informal aperitivo, offering a relaxed setting to continue the conversation and meet the speakers.


The MaLGa Colloquia are part of the activities of the ELLIS Genoa Unit.


Program


📍Department of Mathematics, Via Dodecaneso 35, Genoa

🕓 Mondays at 4:00 PM

🎟️ Free and open to the public


February 9, 2026

Francesco Locatello — Institute of Science and Technology Austria

Head of the Causal Learning and Artificial Intelligence Lab

Representation learning and causality, with a focus on disentangled and structured representations.


March 9, 2026

Barbara Mazzolai — IIT Italian Institute of Technology

Associate Director for Robotics, Director of the Bioinspired Soft Robotics Lab

Bio-inspired and soft robotics, plant-inspired sensing, adaptive materials, embodied intelligence.


March 23, 2026

Holger Rauhut — LMU Munich

Mathematical foundations of machine learning and signal processing, convergence theory, inverse problems, compressive sensing.


April 20, 2026

Carola Schönlieb — University of Cambridge

Machine learning for imaging and inverse problems, combining variational models, PDEs, and data-driven methods.


May 2026 (date TBA)

Emanuele Rodolà — Sapienza University of Rome

Representation learning and geometric deep learning, from graphs and vision to language and multimodal learning.


May 13, 2026

Jesse Thaler — MIT

Theory-driven machine learning for discovery in fundamental physics, with an emphasis on interpretable models for complex, high-dimensional data.

🔹 Joint event with the INFN Physics Colloquia.