[CoLLAs Seminar][1st July 10am CET] Zeynep Akata on "Explainable and Adaptive Multimodal AI"

[Sarath Chandar]

Dear all,

We are excited to bring you the third talk of the monthly CoLLAs Seminar Series, which has an excellent line-up of speakers from around the world: https://lifelong-ml.cc/seminar 

With this series, we aim to bring together researchers working on continual, lifelong, and adaptive machine learning to share new ideas, and foster community-wide dialogue!

Our next talk will be by Zeynep Akata on July 1 at 10:00 AM CET.

Title: Toward Explainable and Adaptive Multimodal AI

Abstract: Modern AI systems are increasingly expected to integrate information across vision, language, time, and domain-specific signals, while remaining reliable, interpretable, and adaptable after deployment. In this talk, I will discuss how we can move from static foundation models toward multimodal systems that can be adapted, inspected, and improved in a principled way. I will present recent work from my group on vision-language learning, model adaptation, multimodal alignment, and explainability, with an emphasis on understanding when models rely on meaningful visual evidence, when they fail to integrate modalities, and how such failures can guide more robust learning. I will also outline a broader research agenda for explainability-guided adaptation: using interpretability not only to explain models after the fact, but as a mechanism for correcting, merging, and continuously improving multimodal AI systems.

Speaker bio: Zeynep Akata is a Liesel Beckmann Distinguished professor of Computer Science at Technical University of Munich and the director of the Institute for Explainable Machine Learning at Helmholtz Munich. After completing her PhD at the INRIA Rhone Alpes with Prof Cordelia Schmid (2014), she worked as a post-doctoral researcher at the Max Planck Institute for Informatics with Prof Bernt Schiele (2014-17) and at University of California Berkeley with Prof Trevor Darrell (2016-17) and as an assistant professor at the University of Amsterdam with Prof Max Welling (2017-19). Before moving to Munich in 2024, she was a professor of computer science (W3) within the Cluster of Excellence Machine Learning at the University of Tübingen. She received a Lise-Meitner Award for Excellent Women in Computer Science from Max Planck Society in 2014, a young scientist honour from the Werner-von-Siemens-Ring foundation in 2019, an ERC-2019 Starting Grant from the European Commission, The DAGM German Pattern Recognition Award in 2021, The ECVA Young Researcher Award in 2022 and the Alfried Krupp Award in 2023. Her research interests include multimodal learning and explainable AI.

Zoom: https://polymtl-ca.zoom.us/j/84066718835?pwd=2cpVMN2XjRXyZrngOFBJSO3Fwifywo.1

We look forward to seeing you there!

Best regards,

Sarath Chandar

On behalf of the CoLLAs Seminar Organizers