MCML Delegation Visit: Panel Discussion and Reception

Daniel Cremers holds the Chair for Computer Vision and Artificial Intelligence at TUM. He conducts research in the fields of image processing, machine learning and robotics. The aim of this research is to teach machines how to analyze and interpret image data. The methodological focus of his research is on convex optimization, statistical learning and neural networks. He was awarded the Gottfried Wilhelm Leibniz Prize in 2016 — Germany’s highest academic honor.

Stefanie Jegelka is a Humboldt Professor at TUM for Foundations of Deep Neural Networks. Her fundamental research led to a better understanding and optimisation of Graph Neural Networks, aiming to make them more reliable. Among other things, she received the German Pattern Recognition Award in 2015 and a Sloan Research Fellowship in 2018.

Björn Ommer is a full professor at LMU Munich, where he leads the Computer Vision & Learning Group. His Research Interest includes all aspects of semantic image and video understanding based on (deep) machine learning. Björn delivered the opening keynote at NeurIPS’23, was awarded the German AI-Prize 2024, the Technology-Prize of Eduard-Rhein-Foundation 2024, and the work leading to Stable Diffusion has been nominated for the German Future Prize of the President of Germany.

Hendrik Strobelt is the Explainability Lead at the MIT-IBM Watson AI Lab and Senior Research Scientist at IBM Research. His recent research is on visualization for and human collaboration with AI models to foster explainability and intuition. His work involves NLP models and generative models while he is advocating to utilize a mix of data modalities to solve real-world problems. His research is applied to tasks in machine learning, in NLP, in the biomedical domain, and in chemistry. Hendrik joined IBM in 2017 after postdoctoral positions at Harvard SEAS and NYU Tandon. He received a Ph.D. (Dr. rer. nat.) from the University of Konstanz in computer science (Visualization) and holds an MSc (Diplom) in computer science from TU Dresden. His work has been published at venues like IEEE VIS, ICLR, ACM Siggraph, ACL, NeurIPS, ICCV, PNAS, Nature BME, or Science Advances. He received multiple best paper/honorable mention awards at EuroVis, BioVis, VAST, ACL Demo, or NeurIPS demo. He received the Lohrmann medal from TU Dresden as the highest student honor. Hendrik has served in program committees and organization committees for IEEE VIS, BioVis, EuroVis. He served on organization committees for IEEE VIS, VISxAI, ICLR, ICML, NeurIPS. Hendrik is visiting researcher at MIT CSAIL. (more: http://hendrik.strobelt.com)

Todd Zickler is the Director of the Harvard Computer Vision Laboratory and member of the Graphics, Vision and Interaction Group. His research is focused on modeling the interaction between light and materials, and developing systems to extract scene information from visual data. His work is motivated by applications in face, object, and scene recognition; image-based rendering; image retrieval; image and video compression; robotics; and human-computer interfaces. Dr. Zickler is a recipient of the National Science Foundation Career Award and a Research Fellowship from the Alfred P. Sloan Foundation.

Kate Saenko is a Professor at the Department of Computer Science at Boston University, and the director of the Computer Vision and Learning Group and member of the IVC Group. She received her PhD from MIT. Previously, she was an Assistant Professor at the Department of Computer Science at UMass Lowell, a Postdoctoral Researcher at the International Computer Science Institute, a Visiting Scholar at UC Berkeley EECS and a Visiting Postdoctoral Fellow in the School of Engineering and Applied Science at Harvard University. Her research interests are in the broad area of Artificial Intelligence with a focus on Adaptive Machine Learning, Learning for Vision and Language Understanding, and Deep Learning.