Workshop on the Elements of Reasoning:
Objects, Structure, and Causality (OSC)

April 29, 2022, Virtual ICLR 2022 Workshop

Invited Speakers

Bernhard Schölkopf is a director at the Max Planck Institute for Intelligent Systems in Tübingen, professor at ETH Zürich, honorary professor at the University of Tübingen and the Technical University Berlin, and chairman of the European Laboratory for Learning and Intelligent Systems (ELLIS). He has been one of the leading researchers at the intersection between Causality and Machine learning for over 15 years and will contribute to our workshop program providing his unique perspective on the evolution of the field as a whole.
Qianru Sun is an assistant professor of computer science in the School of Computing and Information Systems, Singapore Management University (SMU), with research interests covering object recognition and causality. She co-organized the 1st workshop of Causality in Vision at CVPR '21, and will introduce her works bridging causality and computer vision applications.
Karl Stelzner is a PhD Student at the Technical University Darmstadt. He draws inspiration from cognitive science and robotics to study how machines can obtain useful representations from noisy, unstructured input data without requiring expensive manual labeling. In particular, he combines techniques from graphical models, probabilistic programming, and deep learning.
Nikolaus Kriegeskorte is a Professor at Columbia University, affiliated with the Departments of Psychology and Neuroscience. He studies how our brains enable us to see and understand the world around us. He is a Principal Investigator and Director of Cognitive Imaging at the Zuckerman Mind Brain Behavior Institute at Columbia University. Kriegeskorte is a co-founder of the conference “Cognitive Computational Neuroscience”. His recent research particularly focuses on object-centric representations both in brains and machines.
Rosemary Ke is a research scientist at DeepMind and PhD candidate at MILA with Yoshua Bengio and Chris Pal and was named a rising star in ML in 2020. She was one of the early researchers applying neural networks for causal discovery and she will bring her perspective on fundamental challenges learning abstractions and discovering causal relations with deep learning.
Alison Gopnik is a professor of psychology and affiliate professor of philosophy at the University of California at Berkeley, where she has taught since 1988. She is a world leader in cognitive science, particularly the study of children’s learning and development. Recently, she and her team have been particularly interested in how children figure out psychological causality and how that helps them build a “theory of mind”.

Panel Moderators

Wilka Carvalho (University of Michigan)
Sindy Löwe (University of Amsterdam)


Nikolaus Kriegeskorte (Columbia University)
Karl Stelzner (Technical University Darmstadt)
Sara Magliacane (University of Amsterdam)
Rosemary Ke (DeepMind)
Sjoerd van Steenkiste (Google Research)

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