AI4ABM@ICLR2023 Workshop - Speakers

J. Doyne Farmer is Director of the Complexity Economics programme at the Institute for New Economic Thinking at the Oxford Martin School, Baillie Gifford Professor in the Mathematical Institute at the University of Oxford and an External Professor at the Santa Fe Institute. His current research is in economics, including agent-based modeling, financial instability and technological progress. He was a founder of Prediction Company, a quantitative automated trading firm that was sold to the United Bank of Switzerland in 2006. His past research includes complex systems, dynamical systems theory, time series analysis and theoretical biology. He was an Oppenheimer Fellow and the founder of the Complex Systems Group at Los Alamos National Laboratory. While a graduate student he built the first wearable digital computer, which was successfully used to predict the game of roulette.

Christopher Summerfield, Department of Experimental Psychology, University of Oxford Christopher Summerfield is Professor of Cognitive Neuroscience at the University of Oxford and a Research Scientist at Deepmind UK. His work focusses on the neural and computational mechanisms by which humans make decisions.

I am the co-founder and Executive Director of Climate Change AI (CCAI), a global nonprofit initiative to catalyze impactful work at the intersection of climate change and machine learning. I am currently running CCAI through the Runway Startup Postdoc Program at Cornell Tech and the Jacobs Institute. I will also join MIT EECS as an Assistant Professor in Fall 2023. My research focuses on machine learning for forecasting, optimization, and control in high-renewables power grids. Specifically, my work explores methods to incorporate the physics and hard constraints associated with electric power systems into deep learning workflows. Please see here for a list of my recent publications.

Research Affiliate and Co-PI of the Julia Lab at the Massachusetts Institute of Technology Director of Modeling and Simulation at Julia Computing and Creator / Lead Developer of JuliaSim Director of Scientific Research at Pumas-AI and Creator / Lead Developer of Pumas Lead Developer of the SciML Open Source Software Organization. Chris' research and software is focused on Scientific Machine Learning (SciML): the integration of domain models with artificial intelligence techniques like machine learning. By utilizing the structured scientific (differential equation) models together with the unstructured data-driven models of machine learning, our simulators can be accelerated, our science can better approximate the true systems, all while enjoying the robustness and explainability of mechanistic dynamical models.

Joshua Epstein is Professor of Epidemiology in the NYU School of Global Public Health, and founding Director of the NYU Agent-Based Modeling Laboratory, with affiliated appointments at The Courant Institute of Mathematical Sciences, and the College of Arts & Sciences. Prior to joining NYU, he was Professor of Emergency Medicine at Johns Hopkins, and Director of the Center for Advanced Modeling in the Social, Behavior, and Health Sciences, with Joint appointments in Economics, Applied Mathematics, International Health, and Biostatistics. Before that, he was Senior Fellow in Economic Studies at the Brookings Institution and Director of the Center on Social and Economic Dynamics. His research interest has been modeling complex social dynamics using mathematical and computational methods, notably the method of Agent-Based Modeling in which he is a recognized pioneer. For this transformative innovation, he was awarded the NIH Director’s Pioneer Award in 2008, an Honorary Doctorate of Science from Amherst College in 2010, and was elected to the Society of Sigma XI in 2018. He has applied this method to the study of infectious diseases (e.g., Ebola, pandemic influenza, and smallpox), vector-borne diseases (e.g., zika), urban disaster preparedness, contagious violence, the evolution of norms, economic dynamics, computational archaeology, and the emergence of social classes, among many other topics. His books include Nonlinear Dynamics, Mathematical Biology, and Social Science (Wiley 1997), Generative Social Science: Studies in Agent-Based Computational Modeling (Princeton, 2006), Agent_Zero: Toward Neurocognitive Foundations for Generative Social Science (Princeton, 2013), and with Robert Axtell, Growing Artificial Societies: Social Science from the Bottom Up (MIT, 1996). Dr. Epstein earned his BA from Amherst College and his Ph.D. from The Massachusetts Institute of Technology.

Manuela Maria Veloso is the Head of J.P. Morgan AI Research & Herbert A. Simon University Professor in the School of Computer Science at Carnegie Mellon University, where she was previously Head of the Machine Learning Department. She served as president of Association for the Advancement of Artificial Intelligence (AAAI) until 2014, and the co-founder and a Past President of the RoboCup Federation. She is a fellow of AAAI, Institute of Electrical and Electronics Engineers (IEEE), American Association for the Advancement of Science (AAAS), and Association for Computing Machinery (ACM). She is an international expert in artificial intelligence and robotics.