Aaron Roth University of Pennsylvania	Aaron Roth is the Henry Salvatori Professor of Computer and Cognitive Science at the University of Pennsylvania computer science department. He received his PhD from Carnegie Mellon University. His main interests are in algorithms and machine learning, and specifically in the areas of private data analysis, fairness in machine learning, game theory and mechanism design, and learning theory.
	Craig Boutilier Google	Craig Boutilier is Principal Scientist at Google. He was a Professor in the Department of Computer Science at the University of Toronto (on leave) and Canada Research Chair in Adaptive Decision Making for Intelligent Systems. His current research efforts focus on various aspects of decision making under uncertainty: preference elicitation, mechanism design, game theory and multiagent decision processes, economic models, social choice, computational advertising, Markov decision processes, reinforcement learning and probabilistic inference.
	Cynthia Rudin Duke University	Cynthia Rudin is a professor of computer science, electrical and computer engineering, statistical science, mathematics, and biostatistics & bioinformatics at Duke University. She directs the Interpretable Machine Learning Lab, whose goal is to design predictive models with reasoning processes that are understandable to humans. Her lab applies machine learning in many areas, such as healthcare, criminal justice, and energy reliability. She holds an undergraduate degree from the University at Buffalo, and a PhD from Princeton University. She is the recipient of the 2022 Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity from the Association for the Advancement of Artificial Intelligence (the “Nobel Prize of AI”). She is a fellow of the American Statistical Association, the Institute of Mathematical Statistics, and the Association for the Advancement of Artificial Intelligence. Her work has been featured in many news outlets including the NY Times, Washington Post, Wall Street Journal, and Boston Globe.
	Finale Doshi-Velez Harvard University	Finale Doshi-Velez is a Gordon McKay Professor in Computer Science at the Harvard Paulson School of Engineering and Applied Sciences. She completed her MSc from the University of Cambridge as a Marshall Scholar, her PhD from MIT, and her postdoc at Harvard Medical School. Her interests lie at the intersection of machine learning, healthcare, and interpretability.
	Masoud Mansoury University of Amsterdam	Masoud Mansoury is a postdoctoral researcher at Amsterdam Machine Learning Lab at University of Amsterdam, Netherlands. He is also a member of Discovery Lab collaborating with the Data Science team at Elsevier Company in the area of recommender systems. Masoud received his PhD in Computer and Information Science from Eindhoven University of Technology, Netherlands, in 2021. He has published his research works in top conferences such as FAccT, RecSys, and CIKM. His research interests include recommender systems, algorithmic bias, and contextual bandits.
	Solon Barocas Microsoft, Cornell University	Solon Barocas is a Principal Researcher in the New York City lab of Microsoft Research and an Adjunct Assistant Professor in the Department of Information Science at Cornell University. His research explores ethical and policy issues in artificial intelligence, particularly fairness in machine learning, methods for bringing accountability to automated decision-making, and the privacy implications of inference.