About AI-HUB@LMU

Our Mission

The recent success of Artificial Intelligence (AI) and its widespread use in various application areas has largely been achieved thanks to a shift from the classical knowledge-based paradigm to a strongly data-driven approach to intelligent agent design. This shift has been facilitated by the emergence of data science as an independent scientific discipline and the success of machine learning as one of its core methodologies.

The mission of the AI-HUB@LMU is to further strengthen this fruitful symbiosis between AI and Data Science, to develop it to the benefit of both sides, and ultimately to blur the boundaries between the fields. In particular, the central role of data for all facets of modern AI methodology, as well as the associated statistical, algorithmic and application-oriented challenges, will be in the focus. In addition, we advocate a view of data science that goes beyond the traditional perception as mere knowledge production in the sense of "knowledge discovery from data", namely a view as a data-driven problem-solving methodology that focuses more on the use of knowledge for better action and decision making.

AI-HUB@LMU emphasizes interdisciplinarity and approaches scientific questions from the perspective of a wide range of different research fields. It values strong theoretical foundations and sound methodology as the basis for trustworthy and sustainable AI, while not losing sight of the significant implications for science as a whole and the enormous challenges that AI and data-driven technologies pose for society and humanity. This approach fits perfectly with LMU's profile and strategic direction as a university that covers the full spectrum of scientific disciplines and promotes interdisciplinary research to overcome the boundaries between them.

AI-HUB@LMU 8-Point Action Plan

🧑‍🔬 Research:

(1) Building Connections: Host networking events like Round Tables and the Annual AI Symposium to foster collaborations.
(2) AI Expertise Hub: Develop a comprehensive database of AI researchers at LMU, and serve as contact point for all LMU-related AI issues.
(3) Innovative Project Incubator: Support large-scale, interdisciplinary AI projects through a dedicated incubator.

🧑‍🏫 Education:

(4) Streamlining AI Education: Strengthen the teaching of AI topics across disciplines.
(5) Student Support Hub: Serve as a primary contact point for students interested in AI studies and initiatives.

🏭 Transfer:

(6) Showcasing LMU's AI Excellence: Boost international visibility through a dedicated website, the AI@LMU Newsletter, and other promotional channels.
(7) Driving Innovation Transfer: Facilitate the adoption of cutting-edge AI techniques through targeted transfer initiatives with industry partners and government agencies.
(8) Public Engagement in AI: Organize outreach activities to educate and inspire the general public about AI advancements.