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Link to MCML at AAAI 2026

19.01.2026

MCML at AAAI 2026

Eleven Accepted Papers (8 Main, and 3 Workshops)

We are happy to announce that MCML researchers have contributed a total of 11 papers to AAAI 2026: 8 Main, and 3 Workshop papers. Congrats to our researchers!

Link to MCML PI Frauke Kreuter Featured on ARD Alpha on AI

19.01.2026

Exploring Opportunities and Risks of Artificial Intelligence

MCML PI Frauke Kreuter was featured on ARD alpha, discussing how AI is shaping everyday life and the workplace. Alongside moderator Birgit Kappel and Sabine Pfeiffer, head of the Chair of Sociology at …

Link to Blind Matching – Aligning Images and Text Without Training or Labels

15.01.2026

Blind Matching – Aligning Images and Text Without Training or Labels

MCML Research Insight - With Dominik Schnaus, Nikita Araslanov, and Daniel Cremers

Vision-language models have shown that images and text can live in a shared space: a picture of a “cat” often lands close to the word “cat” in the embedding space. But such …

Link to MCML PIs Featured in Süddeutsche Zeitung

12.01.2026

Innovations in Science and Technology

MCML PIs Xiaoxiang Zhu and Felix Dietrich were featured in Süddeutsche Zeitung’s coverage of TU Munich’s major scientific breakthroughs in 2025. Their work contributes to current advances in …

Link to Call for Speakers Certificate Course „Responsible AI“

12.01.2026

Call for Speakers Certificate Course „Responsible AI“

We Are Seeking Speakers for the First Certificate Course on Responsible AI

The certificate course “Responsible AI” is jointly organized by the German National AI Centers. It addresses AI researchers on all levels from the centers, the participating universities, …

Link to High-Res Images, Less Wait: A Simple Flow for Image Generation

08.01.2026

High-Res Images, Less Wait: A Simple Flow for Image Generation

MCML Research Insight - With Johannes Schusterbauer, Pingchuan Ma, Vincent Tao Hu, and Björn Ommer

Image generation models today can create almost anything, like a futuristic city glowing at sunset, a classical painting of your cat, or a realistic spaceship made of glass. But when you ask them to …

Link to MCML Researchers in Highly-Ranked Journals

02.01.2026

MCML Researchers in Highly-Ranked Journals

Four Papers in 2026 Highlight Scientific Impact

We are happy to announce that MCML researchers are represented in 2026 with four papers in highly-ranked journals. Congrats to our researchers!

Link to Konstantin Riedl Wins Doctoral Award from the Friends of TUM e.V.

28.12.2025

Konstantin Riedl Wins Doctoral Award from the Friends of TUM e.V.

Former MCML Member Recognized for an Outstanding Doctoral Dissertation

Konstantin Riedl, former MCML member, has received the Doctoral Award of the Friends of TUM e.V., honoring one of the most outstanding doctoral dissertations at the Technical University of Munich. He …

Link to Digdeep Podcast: Armin Nassehi, How Does Social Transformation Succeed?

25.12.2025

Digdeep Podcast: Armin Nassehi, How Does Social Transformation Succeed?

News From the Digital World by MCML PI Frauke Kreuter and Christof Horn

In this episode of #digdeep, the sociologist Armin Nassehi declares, how social transformation succeeds. He discusses, why social changes are often not implemented despite clear goals and great urgency …

Link to Merry Christmas and a Happy New Year 2026

23.12.2025

Merry Christmas and a Happy New Year 2026

Season's Greetings From the Entire Team at the MCML

Thank you for a wonderful year of collaboration and partnership. Wishing you a joyful festive season, and we look forward to seeing you again in 2026!

Link to MCML Thinkathon

18.12.2025

MCML Thinkathon

A Short Recap

MCML has launched the Thinkathon, a new initiative designed to connect AI research with the practical needs of the Bavarian education system. In a hackathon-style setting, MCML Junior Members …

Link to "See, Don’t Assume": Revealing and Reducing Gender Bias in AI

18.12.2025

"See, Don’t Assume": Revealing and Reducing Gender Bias in AI

MCML Research Insight - With Leander Girrbach, Yiran Huang, Stephan Alaniz and Zeynep Akata

Using AI and LLMs at work feels almost unavoidable today: they make things easier, but they can also go wrong in important ways. One of the trickiest problems? Gender bias. For example, if you ask …

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