Next Generation AI
We currently witness the impressive success of artificial intelligence (AI) in real-world applications, ranging from autonomous driving over speech recognition to the health care sector. At the same time, modern, typically data-driven AI methods have a similarly strong impact on science such as astronomy, physics, medicine – as well as humanities or social sciences, often replacing classical methods in the state of the art. In fact, at present, basically any research area is already impacted or starting to get involved in research questions in the realm of AI. However, despite this outstanding success, most of the research on AI is empirically driven and not only is a comprehensive theoretical foundation -- in particular, in the sense of explanations of decisions -- missing, but even the limitations of these methods are far from being well understood. It is also far from clear how AI-based methods can be optimally combined with classical methods based on physical models as domain knowledge.
At present, two general streams of research in artificial intelligence can be identified worldwide. On the one hand, existing methodologies are adapted and applied to diverse scientific areas, while on the other hand, researchers aim to tackle the aforementioned methodological/theoretical problems and initiate the next generation of artificial intelligence. At LMU Munich, those directions are also prominently represented and displayed at https://www.lmu.de/ai. It is important to also stress that in fact both directions require a highly interdisciplinary effort and have many interconnections.
The CAS Research Focus therefore aims to connect, in particular, more methodological/theoretical with more application-oriented researchers across all faculties of LMU Munich as well as existing research and teaching activities, focusing on the following key problem complexes at the verge of the next generation of AI:
- AI and Uncertainty
- AI and Domain Knowledge
- Limitations of AI
- Social Aspects of AI (Explainability, Fairness, etc.)
Speaker
- Prof. Dr. Gitta Kutyniok
(Mathematics, Faculty of Mathematics, Computer Science and Statistics, LMU)
Work Group
- Prof. Dr. Bernd Bischl
(Statistics, Faculty of Mathematics, Computer Science and Statistics, LMU)
- Prof. Dr. Florian Englmaier
(Organisational Economics, Faculty of Economics, LMU) - Prof. Dr. Eyke Hüllermeier
(Computer Science, Faculty of Mathematics, Computer Science and Statistics, LMU) - Prof. Dr. Göran Kauermann
(Statistics, Faculty of Mathematics, Computer Science and Statistics, LMU) - Prof. Dr. Katia Parodi
(Medical Physics, Faculty of Physics, LMU) - Prof. Dr. Hinrich Schütze
(Computer Linguistics, Faculty of Languages and Literatures, LMU) - Prof. Dr. Thomas Seidl
(Computer Science, Faculty of Mathematics, Computer Science and Statistics, LMU)
Scientific Advisory Board
- Prof. Dr. Ruth Bielfeldt
(Classical Archaeology, Faculty of Cultural Studies, LMU) - Prof. Dr. Christof Breitsameter
(Moral Theology, Faculty of Catholic Theology, LMU) - Prof. Dr. Stefan Feuerriegel
(Artificial Intelligence (AI) in Businesses, Faculty of Business Administration, LMU) - Prof. Dr. Stephan Hartmann
(Philosophy of Science, Faculty of Philosophy, Philosophy of Science and the Study of Religion, LMU) - Prof. Dr. Heiner Igel
(Geophysics, Faculty of Geosciences, LMU) - Prof. Dr. Michael Ingrisch
(Clinical Data Science in Radiology, LMU University Hospital) - Prof. Dr. Alexander Keller
(Cellular and Organismic Networks, Faculty of Biology, LMU) - Prof. Dr. James Kirby
(Faculty of Languages and Literatures, LMU) - Prof. Dr. Hubertus Kohle
(Art History, Faculty of History and the Arts, LMU) - Prof. Dr. Frauke Kreuter
(Statistics and Data Science in Social Sciences and the Humanities, Faculty of Mathematics, Computer Science and Statistics, LMU) - Prof. Dr. Christian List
(Mathematical Philosophy, Faculty of Philosophy, Philosophy of Science and the Study of Religion, LMU) - Dr. Julian Müller
(General Pedagogy, University of Bamberg) - Prof. Dr. Björn Ommer
(Artificial Intellgigence (AI) and Culture Analytics, Faculty of History and the Arts as well as the Faculty of Mathematics, Computer Science and Statistics, LMU) - Prof. Dr. Monika Schnitzer
(Comparative Economic Research, Faculty of Economics, LMU) - Prof. Dr. Jochen Weller
(Physical Cosmology, Faculty of Physics, LMU) - Prof. Dr. Mark A. Zöller
(German, European and International Criminal Law and Criminal Procedural Law, Business Criminal Law and Law of Digitization, Faculty of Law, LMU)
Events
- Lecture by Prof. Michael I. Jordan, Ph.D. – "On the Blending of Machine Learning and Economics"
(Winter Semester 2021/22) - Panel Discussion with Prof. Dr. Sami Haddadin, Prof. Dr. Gitta Kutyniok and Eva Wolfangel – "Next Generation AI"
(Winter Semester 2021/22) - Roundtable – "Next Generation AI" Topic I: AI and Uncertainty"
(Winter Semester 2021/22) - Roundtable – "Next Generation AI" Topic II: AI and Domain Knowledge"
(Winter Semester 2021/22) - Roundtable – "Next Generation AI" Topic III: Limitations of AI"
(Winter Semester 2021/22) - Roundtable – "Topic IV: Social Aspects of AI"
(Winter Semester 2021/22) - Symposium on AI Research at LMU
(Summer Semester 2022) - Lecture by Prof. Dr. Joachim M. Buhmann - "Algorithm Validation for Data Science"
(Summer Semester 2022) - Workshop – "AI in Science: Foundations and Applications"
(Summer Semester 2022) - Lecture by Prof. Issam El Naqa, Ph.D. and Prof. Julia Lane, Ph.D. - "Perils and Pitfalls of AI
in Radiological Sciences"
(20th October 2022, 19:00 s.t.) | (Winter Semester 2022/23) - Lecture Series – "The Munich AI Lectures"
- Lecture by Prof. Stéphane Mallat, Ph.D. – "Mathematical Mysteries of Deep Neural Networks"
(Summer Semester 2022) - Lecture by Prof. Max Welling, Ph.D. (University of Amsterdam) – "The PDE Prior"
(5th October 2022, 17:00 s.t) | (Winter Semester 2022/23) - Lecture by Prof. Michael Bronstein, Ph.D. - "Physics-Inspired Learning on Graphs"
(2nd November 2022, 17:00 s.t.) | (Winter Semester 2022/23) - Lecture by Prof. Peter Flach, Ph.D. – "The Highs and Lows of Performance Evaluation: Towards A Measurement Theory for Machine Learning"
(8th February 2023, 17:00) | (Winter Semester 2022/23) - Lecture by Prof. René Vidal, Ph.D. (Johns Hopkins University) – "Explainable AI via Semantic Information Pursuit"
(8th March 2023, 17:00) | (Winter Semester 2022/23) - Lecture Series in the Winter Semester 2022/23
- Panel discussion with Prof. Dr. Daniel Gruen (LMU), Prof. Dr. Lukas Heinrich (TUM) and Prof. Kevin Heng, Ph.D. (LMU) – "The Future of Astrophysics"
(25th October 2022, 19:00 s.t.) | (Winter Semester 2022/23) - Lecture by Prof. Dr. Nils B. Weidmann (Konstanz/CAS Fellow) – "Artificial Intelligence in Conflict Research"
(23rd November 2022, 18:30) | (Winter Semester 2022/23) - Panel discussion with Prof. Dr. Barbara Plank (LMU), Prof. Dr. Mario Haim (LMU), Uli Köppen (BR) and Prof. Dr. Hinrich Schütze (LMU) – "Writing with Artificial Intelligence"
(2nd February 2023, 19:00 s.t.) | (Winter Semester 2022/23) - Panel discussion with Prof. Dr. Karl-Peter Hopfner (LMU) and Dr. Alexander Pritzel (DeepMind) – "The Impact of AlphaFold on Protein Research"
(2nd February 2023, 19:00 Uhr s.t.) | (Winter Semester 2022/23) - Panel discussion with Prof. Dr. Laura Busse (LMU), Prof. Dr. Frederick Klauschen (LMU) and Prof. Dr. Björn Menze (Zürich) - "Visualizing (Bio-)Medicine with Artificial Intelligence"
(6th February 2023, 19:00 s.t.) | (Winter Semester 2022/23) - Conference – "Quo Vadis, Digital Privacy? Perceptions, Practices, and Policies"
(26th January 2023, 17:00 s.t.) | (Winter Semester 2022/23)