Research Recap

Speaker Jake Russin Bio Dr. Russin is a postdoc at Brown University working with Michael Frank and Ellie Pavlick. He received PhD from UC Davis, where he worked with Randall O’Reilly in the Computational Cognitive Neuroscience Lab. His interests lie broadly in the intersection of computational neuroscience and machine learning, with a particular focus on: 1）Compositionality, systematicity, and reasoning in neural networks (including large language models), 2）Neural network models of cognitive flexibility and cognitive control, 3）Neural network models of learning and inference with cognitive maps. He also conducts experiments with human subjects and collaborates with experimental cognitive neuroscientists to study how the human brain can accomplish these cognitive functions. ...

Speaker Steven Miletić Bio Dr. Steven Miletić obtained all his academic degrees (BSc, MSc, PhD) cum laude at the University of Amsterdam. Dr. Miletić did his PhD under supervision of Dr. Birte Forstmann, followed by one postdoc in her group, before becoming (tenured) assistant professor at Leiden University in 2023. Dr. Miletić’s research focuses on cognitive and neural modelling of decision and learning processes in humans, with emphasis on the human subcortex and on advanced methodology including hierarchical Bayesian approaches and ultra-high field fMRI. ...

Speaker Tom Griffiths Bio Tom Griffiths is Henry R. Luce Professor of Information Technology, Consciousness, and Culture, at the Department of Psychology and Computer Science at Princeton University. He is also the director of Princeton AI Lab, a new effort that supports innovative research efforts in AI and related fields. His research focuses on developing mathematical models of human cognition, emphasizing what makes human intelligence distinct from modern AI. By studying how humans operate under constraints like limited time, computational capacity, and communication bandwidth, he seeks to understand how we achieve efficient learning, resourceful thinking, and collaboration. These insights aim to inform the design of AI systems that better mirror human-like intelligence. ...

Recording https://www.bilibili.com/video/BV1s8X6YFE5y/?share_source=copy_web&vd_source=afe9405056278e6f25d039a72daab83b Speaker Paul Masset Bio Paul Masset is an Assistant Professor in the Department of Psychology at McGill University working at the intersection of neuroscience, AI and cognitive science. The focus of his research group is to understand how the structure of neural circuits endows the brain with efficient distributed computations underlying cognition and how we can leverage these principles to design more efficient learning algorithms. Prior to joining McGill, he was a Postdoctoral Fellow at Harvard University. He obtained his PhD at Cold Spring Harbor Laboratory, his Masters in Cognitive Science at the École des hautes études en sciences sociales (EHESS) and his M.Eng/B.A. in Information and Computer Engineering at the University of Cambridge. ...

Recording https://www.bilibili.com/video/BV1FxSwYBExo/?share_source=copy_web&vd_source=afe9405056278e6f25d039a72daab83b Speaker Marcel Binz Bio Marcel Binz is a research scientist and deputy head of the Institute for Human-Centered AI at Helmholtz Munich. His research employs computational models to uncover the fundamental principles behind human cognition. He believes that for a more complete understanding of human cognition, we must consider the human mind as a whole. His current goal is therefore to establish foundation models of human cognition – models that cannot only simulate, predict, and explain human behavior in a single domain but those that offer a unified take on our mind. To accomplish this, he uses tools such as neural networks, Bayesian inference, meta-learning, information theory, and large language models. ...

Recording Speaker Christopher Summerfield Bio Christopher Summerfield is a Fellow by special election and principal investigator at the Summerfield lab which conducts research into how humans make decisions. Chris Summerfield was trained in psychology and neuroscience at University College London, Columbia University (New York), and the École normale supérieure (Paris). He is a Professor of Cognitive Neuroscience in the Department of Experimental Psychology, where he heads a lab focused on understanding the computational mechanisms by which humans make decisions, and how these processes are implemented in the brain. His work, which involves a combination of computer simulations, behavioural testing, and functional brain imaging, is funded by a grant from the European Research Council, the Wellcome Trust, and the National Institute of Health. Recently, he accepted the position as the director at UK AI Safety Institute. ...

Recording https://www.bilibili.com/video/BV1rs421T7xX/?share_source=copy_web Speaker Marc-Lluis Vives Bio Marc-Lluis Vives is an Assistant Professor at Leiden University. He is interested in how the structure of mental representations predicts behavior in general and decision-making in particular. Abstract Decision-making is driven by how the situation is mentally constructed. Past research has successfully manipulated these decision frames by changing how a situation is described. It remains unknown, however, how decision frames are spontaneously constructed in the first place. In this talk, I’ll present evidence that semantic representations play a crucial role in frame construction, demonstrating that the structure of semantic spaces predicts decision-making. Furthermore, I’ll explore the reverse logic by showing how a key component of decision-making—uncertainty aversion—can predict the structure of semantic representations. Overall, I’ll discuss the often-overlooked link between semantic representations and decision-making processes.

Recording Speaker Arkady Konovalov Bio I am an Associate Professor in the School of Psychology at the University of Birmingham. My research focuses on neuroeconomics and decision making in general, including models of the choice process, value-based learning, and social and strategic interactions, using methods of computational neuroscience such as response times modeling, fMRI, EEG, eye-tracking, and mouse-tracking. I received my PhD from the Ohio State University, where I worked with Ian Krajbich, PJ Healy, and John Kagel; I then got my postdoctoral training with Christian Ruff at the University of Zurich. ...

Recording Speaker Anne Collins Bio I am currently an associate professor at UC Berkeley in the psychology department, with an affiliation in the Helen Wills Neuroscience institute. This semester, I’m also a visiting scholar at the University of Bordeaux, France. I did my undergrad at Ecole Polytechnique in France in Maths and engineering, and my PhD at Universite Pierre et Marie Curie, France. Then I was a postdoc at Brown university. I study human flexible learning and decision making using behavioral, computational and neuroscience methods. ...

Recording https://www.bilibili.com/video/BV12y421z7sj/?share_source=copy_web&vd_source=afe9405056278e6f25d039a72daab83b Speaker Toby Wise Bio Toby Wise is a Senior Research Fellow in the Department of Neuroimaging at the Institute of Psychiatry, Psychology & Neuroscience (IoPPN) at King’s College London.Toby started his academic career with a BSc in Psychology and MSc in Cognitive Neuroscience at the University of Sussex, before completing a PhD at the Institute of Psychiatry, Psychology and Neuroscience at King’s College London, where he focused on neuroimaging markers of depression and bipolar disorder. He then completed postdoctoral work at UCL and Caltech supported by a Sir Henry Wellcome postdoctoral fellowship from the Wellcome Trust. He returned to King’s College London in 2021 supported by a King’s Prize Fellowship, before starting his lab in 2023 supported by a Career Development Award from the Wellcome Trust. ...