Check In (Continental breakfast will be provided)

Topic: Diffusion model for guided generation with bio applications
Speaker: Dr. Mandy (Mengdi) Wang, Associate Professor of Electrical and Computer Engineering and the Center for Statistics and Machine Learning, Associated Faculty in Computer Science, Princeton University Mandy Wang, an associate professor at Princeton University, holds positions at the Center for Statistics and Machine Learning, Department of Electrical and Computer Engineering, and Department of Computer Science (secondary). Additionally, she is affiliated with the Princeton ML Theory Group and has worked as a visiting research scientist at prestigious institutions. Her PhD from MIT focused on Electrical Engineering and Computer Science with a minor in Math. Mandy’s group conducts research on machine learning and optimization for decision-making in complex systems, including exploration in interactive learning, reinforcement learning limits, and generative AI algorithms. They also explore AI applications in healthcare, biotech, drug discovery, fintech, and intelligent systems, aiming to accelerate scientific discoveries. Funding for their projects comes from multiple sources, including NSF, AFOSR, NIH, and ONR. Mandy is actively involved as Program Chair for ICLR 2023 and Senior AC for Neurips 2023.

Topic: A Fruitful Reciprocity: The Neuroscience-AI Connection
Speaker: Dr. Dan Yamins, Assistant Professor of Psychology and of Computer Science, Stanford University
Daniel Yamins is a cognitive computational neuroscientist at Stanford University, where he’s an assistant professor of Psychology and Computer Science, a faculty scholar at the Wu Tsai Neurosciences Institute, and an affiliate of the Stanford Artificial Intelligence Laboratory. His research group focuses on reverse engineering the algorithms of the human brain, both to learn both about how our minds work and build more effective artificial intelligence systems. He is especially interested in how brain circuits for sensory information processing and decision making arise via the optimization of high-performing cortical algorithms for key behavioral tasks. He received his AB and PhD degrees from Harvard University, was a postdoctoral researcher at MIT, and has been a visiting researcher at Princeton University and Los Alamos National Laboratory. He is a recipient of an NSF Career Award, the James S. McDonnell Foundation award in Understanding Human Cognition, the Sloan Research Fellowship, and is a Simons Foundation Investigator.

Topic: From AI for mental health to digital therapeutics
Speaker: Dr. A. Aldo Faisal, Professor of AI & Neuroscience, Imperial college London
Prof Aldo Faisal (he/him) is a Professor of AI & Neuroscience at Imperial College London’s Departments of Computing and Bioengineering. He holds honorary positions, including associate group leader at the MRC London Institute of Medical Sciences, affiliate faculty at the Gatsby Unit at the Wellcome Trust/Sainsbury Centre in UCL and a chair in Digital Health at the University of Bayreuth (Germany). He is PI and director of the UKRI Centre in AI for Healthcare (AI4Health.io). He holds a UKRI Turing AI Fellowship (2020-2025) in Reinforcement Learning for Healthcare and numerous prizes for his work at the interface of AI, Biomedical Engineering and Neuroscience (£300,000 Rosetrees Interdisciplinary Award, 2022; $50,000 Toyota Research Discovery Prize, 2019).

Lunch Break

Topic: Computational Psychiatry
Speaker: Dr. Frederike Petzschner, Assistant Professor of Brain Science (Research), Brown University
Dr Frederike Petzschner is an Assistant Professor of Brain Science at the Carney Institute for Brain Science at Brown University. She is also a director of the Carney Brainstorm Program which accelerates the translation of computational brain science to clinical applications and commercialization and a member of the national council for digital ecology in Germany. Prior to this, Frederike worked at the Translational Neuromodeling Unit at the University of Zurich and ETH Zurich with Prof. Klaas Enno Stephan. Her research focus is human cognition and mental health: She uses mathematical models in combination with behaviour and brain imaging to understand brain-body and brain-world interactions in the healthy population and in patients suffering from Disordered Gambling, Obsessive-Compulsive Disorder and Chronic Pain. Before coming to Zurich, Frederike received a Master’s with Honors degree in Physics at the University of Würzburg and a PhD in Systemic Neuroscience at LMU Munich.

Topic: What can GenAI teach us about the nature of intelligence?
Speaker: Dr. Blaise Agueray Arcas , VP and Fellow at Google Research
Blaise Agüera y Arcas is a VP and Fellow at Google Research, where he leads an organization working on both basic research and new products in AI. His focus is on augmentative, privacy-first, and collectively beneficial applications, including on-device ML for Android phones, wearables, and the Internet of Things. One of the team’s technical contributions is Federated Learning, an approach to training neural networks in a distributed setting that avoids sharing user data. Blaise also founded the Artists and Machine Intelligence program, and has been an active participant in cross-disciplinary dialogs about AI and ethics, fairness and bias, policy, and risk. Until 2014 he was a Distinguished Engineer at Microsoft. Outside the tech world, Blaise has worked on computational humanities projects including the digital reconstruction of Sergei Prokudin-Gorskii’s color photography at the Library of Congress, and the use of computer vision techniques to shed new light on Gutenberg’s printing technology.

Topic: Artificial Intelligence in Medical Imaging
Speaker: Dr. Hugo Aerts, Associate Professor, Brigham and Women’s Hospital, Harvard Medical School Director, Program for Artificial Intelligence in Medicine (AIM), Brigham And Women’s Hospital; Full Professor at Maastricht University
Hugo Aerts is the Director of the Artificial Intelligence in Medicine (AIM) Program at Harvard-Mass General Brigham. This academic program centralizes AI expertise stimulating cross-pollination among clinical and technical expertise areas, and provides a platform to address various clinical challenges.

Dr. Aerts is a leader in medical AI and PI on major NIH-supported efforts, including the QIN and ITCR initiatives of the NCI. In 2020 he was awarded a prestigious ERC Consolidator grant from the European Union. His research has resulted in numerous peer-reviewed publications in top-tier journals. In 2022 he was awarded by Web of Science as he was among the top 1% highest cited scientists worldwide.

Dr. Aerts is an Associate Professor at Harvard University and a Full Professor at Maastricht University. Dr. Aerts earned his Master’s in Engineering from the Eindhoven Institute of Technology, Ph.D. from Maastricht University, and postdoctoral fellowship from Harvard School of Public Health.