Artificial Intelligence and Business Analytics Workshop 2023

Theodoros Evgeniou is Professor of Decision Sciences and Technology Management at INSEAD since 2001, working on Machine Learning and AI for the past 25 years, on areas ranging from new Machine Learning methods and theory to AI risks and regulations, behavioral economics, as well as AI innovations in business and finance. He has four degrees from MIT, two BSc degrees simultaneously, Computer Science and Mathematics, a Master, and a PhD degree in Computer Science. His work has appeared in multiple journals, such as in Science Magazine, Nature Machine Intelligence, Machine Learning, Lancet Digital Health, Management Science, Marketing Science, Journal of Corporate Finance, Harvard Business Review, Trends in Cognitive Sciences, and others. He has been a member of the OECD Network of Experts on AI, an advisor for the BCG Henderson Institute, a World Economic Forum Academic Partner for Artificial Intelligence, and co-founder of Tremau a technology company for digital regulations.

Sebastian is an assistant professor at the Rotterdam School of Management, Erasmus University, a co-director the Erasmus Centre for Optimization of Digital Experiments, and a practice expert for retail and customer analytics at the Erasmus Centre of Data Analytics. His research is located at the intersection of machine learning, field experiments, and econometrics, and he develops new methods for modeling the behavior of individual customers. Sebastian's work is published in leading marketing journals, including the Journal of Marketing Research and Management Science. Before joining academia, Sebastian was a serial entrepreneur building AI retail media start-ups. His startups were acquired by a global fintech company and a global grocery retailer.

Kevin Leyton-Brown is a professor of Computer Science and a Distinguished University Scholar at the University of British Columbia. He also holds a Canada CIFAR AI Chair at the Alberta Machine Intelligence Institute and is an associate member of the Vancouver School of Economics. He received a PhD and an M.Sc. from Stanford University (2003; 2001) and a B.Sc. from McMaster University (1998). He studies artificial intelligence, mostly at the intersection of machine learning and (1) the design and operation of electronic markets and (2) the design of heuristic algorithms.

Copyright Christian Kielmann

Max Klimm is an Assistant Professor for Discrete Optimization at the Technische Universität Berlin. He is interested in the analysis and optimization of multi-agent systems in traffic, telecommunications, and economics using tools from mathematical optimization, game theory, and mechanism design. Before joining TU Berlin in 2020, he was an Assistant Professor for Operations Research at the Humboldt-Universität zu Berlin. From 2014 to 2016, he was the head of the Junior Research Group for Optimization under Uncertainty at the Einstein-Center for Mathematics. He received his PhD in 2012 in Mathematics from Technische Universität Berlin.

Oded Netzer

Professor Netzer is the Vice Dean of Research and the Arthur J. Samberg Professor of Business at Columbia Business School, an affiliate of the Columbia Data Science Institute, and the author of the book Decisions over Decimals. Professor Netzer is a world-renowned expert in data-driven decision-making and extracting meaningful insights from data. He wrote dozens of papers published in the top tier academic journals. His award-winning research is broadly read and highly cited. He is an award-winning teacher at Columbia Business School's MBA, Executive MBA, Ph.D and Executive Education programs.