Visiting Scholars
How to Apply
Visiting professors apply through their host PI and through the relevant visiting programs at LMU or TUM.
Visiting PhD students or PostDocs can join MCML as Visiting Scholars for the duration of their stay in Munich. Their host PI applies to MCML on their behalf.
Interested in Visiting MCML?
Thomas Meier
Dr.
Science Manager Collaborations, PhD Coordinator, and DEI Official
Alexandra Stang
Dr.
Managing Director, Collaborations, and DEI Official
Current Visiting Scholars
Visiting Professors
Paul Barach
Prof. Dr.
Paul Barach
is a physician-scientist, anesthesiologist and critical care specialist at Thomas Jefferson University, with more than 25 years of clinical and health-system leadership experience.
His research focuses on human factors, patient safety, health systems engineering, qualitative methods, teamwork, and the design and evaluation of complex sociotechnical healthcare systems. His expertise includes analysing complex clinical interventions with particular attention to technology usability, cognitive workload, teamwork, risk, and system-level factors affecting safety and performance. He brings complementary expertise to TUM particularly in the areas of pre-clinical assessment, human-centred evaluation, and clinical translation of intelligent healthcare systems. Paul is hosted by MCML PI Nassir Navab.
Kilian Weinberger
Prof. Dr.
Kilian Weinberger
is a Professor of Computer Science at Cornell University and a Fellow of the AAAI and the ACM, with prior appointments at Washington University in St. Louis and Yahoo Research.
His research spans deep learning, computer vision, natural language processing, graph learning, and Bayesian machine learning, with widely adopted contributions including DenseNets, BERTScore, GPyTorch, Pseudo-LiDAR, and Large Margin Nearest Neighbor metric learning (aka triplet loss). His most recent work addresses the reliability of large language models, including Large Memory Language Models, which separate factual knowledge from linguistic competence by offloading facts to an external database, and latent diffusion models for text generation. His expertise includes the design of efficient and well-calibrated neural architectures, scalable probabilistic modeling with Gaussian processes, and evaluation methods for generated text. He brings complementary expertise to TUM particularly in the areas of resource-efficient deep learning, uncertainty quantification, and 3D perception for robotics and autonomous systems. Kilian is hosted by MCML PI Daniel Cremers.
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2026-09-20 - Last modified: 2026-09-21