News & Awards

Human Aspects of Machine Learning Award 01-01-2025   The research program "Item Discovery for Psychological Testing Using Large Language Models" led by Tom Sühr, receives generous funding from the 2025 MPI-IS Grassroots program. The research aims at developing new methods for psychological test design, using large language models. The research program "Item Discovery for Psychological Testing Using Large Language Models" led by Tom Sühr, receives generous funding from the 2025 MPI-IS Grassroots program. The research aims at developing new methods for psychological test design, using large language models. The project is an interdisciplinary and inter-institutional cooperation with Zhijing Jin and Bernhard Schölkopf from the Empirical Inference department and Augustin Kelava, from the Methods Center of the University of Tübingen. Samira Samadi, Tom Sühr and Lalitha Sivakumar from the Human Aspects of Machine Learning group, will join the efforts. Tom Sühr Samira Samadi Zhijing Jin Bernhard Schölkopf
Perceiving Systems Award 03-12-2024 ACM SIGGRAPH Asia Test-of-Time Award 2024 For the paper "MoSh: Motion and shape capture from sparse markers", published at SIGGRAPH Asia 2014. Co-authors: Matthew Loper, Naureen Mahmood, Michael J. Black. Michael J. Black Matthew Loper Naureen Mahmood
Human Aspects of Machine Learning Award 01-10-2024 Omri Ben-Dov received the ELSA mobility grant for a research visit in the university of Copenhagen     Omri received the ELSA mobility grant for a research visit in the university of Copenhagen to work with Amartya Sanyal Omri Ben-Dov
Learning and Dynamical Systems Award 01-10-2024 Best Paper Award: UNSURE Workshop MICCAI Best Paper Award: UNSURE Workshop MICCAI Michael Muehlebach
Neural Capture and Synthesis Award 13-09-2024 VMV 2024 Best Paper Honorable Mention VMV 2024 Best Paper Honorable Mention for the work Controllable Action-aware Manifold for 3D Motion Synthesis, a collaboration with the group of Christian Theobalt (MPI-I). Balamurugan Thambiraja Christian Theobalt