Location: Munich
Contact: ellia.wamese@tum.de
Hinrich Schuetze is Professor for Computational Linguistics and co-director of the Center for Information and Language Processing at the University of Munich (LMU Munich). He received his PhD from Stanford in 1995 for his early research on embeddings (ACL Test-of-Time Paper Award). He then worked on natural language processing and information retrieval technology at Xerox PARC, at several Silicon Valley startups and at Google 1995-2004 and 2008/9. Hinrich is a coauthor of Foundations of Statistical Natural Language Processing (with Chris Manning) and Introduction to Information Retrieval (with Chris Manning and Prabhakar Raghavan). He was awarded a European Research Council Advanced Grant in 2017. Hinrich served as president of the Association for Computational Linguistics in 2020. He is a fellow of ACL, ELLIS and HessianAI.
Patrick van der Smagt is Head of AI & Engineering at Foundation Future Industries. He has led machine learning and robotics research across academia and industry, including directing AI research at Volkswagen Group and as professor for ML and robotics at TUM. His research spans probabilistic deep learning and inference for dynamical systems, optimal control, and robotics. He is affiliated with the LMU Graduate School of Systemic Neurosciences and serves as a professor at ELTE University (Budapest). He is an ELLIS and ELIAS fellow, and member of the Bavarian AI Council.
Moritz Probst is a Master’s student in Mathematics at the Technical University of Munich (TUM), focusing on probability theory, statistics, and the theoretical foundations of machine learning, particularly at their intersection. His research interests center on the theoretical properties of machine learning systems and the development of mathematical guarantees for their reliable application in high-stakes domains such as medicine and pharmaceutical research, with a focus on uncertainty quantification and model reliability. Alongside his studies, he is involved in research with the Theis Lab at the Institute of Computational Biology at Helmholtz Munich and conducts student research with the Chair of Mathematical Foundations of Artificial Intelligence at LMU Munich, led by Prof. Dr. Gitta Kutyniok. Previously, he gained industry experience through internships at Deloitte and UniCredit.
I am an MSc student in Mathematics in Data Science at TUM, and active TUM.ai member. My research experience includes working as an AI Research Intern at Siemens AG to improve proprietary foundation models, and as a Research Collaborator at IBM Research, where I work on tool calling in Small Language Models. I am also involved with the Data Science Lab (Dlab) at EPFL, working with Prof. Robert West. I received my BSc in Mathematical Sciences for Artificial Intelligence from Sapienza University of Rome. In Rome, I worked in the GLADIA research group, advised by Emanuele Rodolà, with a thesis on tokenizing latent representations for efficient high-fidelity music generation. During my time there, I also contributed as an Autonomous Driving Engineer for the Sapienza Fast Charge team. In addition to my academic path, I enjoy hackathons, Caribbean dances, sports, connecting with people, trips, and stepping out of my comfort zone.
Collaborated on cross-site research in autonomous driving systems.
I obtained a double degree in Mathematics and Physics from the University of Barcelona in 2021, followed by a Master’s in Applied Mathematics from the Technical University of Munich.
During my Master’s thesis, in collaboration with the Helmholtz Center Munich and funded by an ELIZA scholarship, I studied the prediction of drug-induced effects in single-cell biology. The methods of choice were state-of-the-art integrations of Optimal Transport and Deep Learning Methods.
Since graduation, I have been working as an R&D engineer at Canon Production Printing. As part of my work, I develop numerical simulations and data-based approaches to design and optimize print processes.
Thomas Wimmer is a doctoral researcher and PhD fellow of the Max Planck ETH Center for Learning Systems (CLS) and the ELLIS program, advised by Jan Eric Lenssen, Bernt Schiele, Christian Theobalt (MPI for Informatics), and Siyu Tang (ETH Zurich). He holds Master’s degrees from the Technical University of Munich and the Institut Polytechnique de Paris, both completed with highest honors. As a Master’s student, he was also an ELIZA fellow.
His research focuses on 3D computer vision at the intersection of computer graphics and geometry processing, with particular interest in (dynamic) scene understanding, reconstruction, and generation. His work has been published at top-tier venues such as CVPR, ACL, and 3DV. He has served as a reviewer for several conferences and journals, and conducted research stays at institutions including MPI, ETH Zurich, and École Polytechnique, collaborating with researchers such as Daniel Cremers, Maks Ovsjanikov, and Federico Tombari.