Markus Gesmann is the co-founder of Insurance Capital Market Research, a quantitative research house based in London. He has spent over 20 years in both insurance and capital markets. Markus is the former head of analysis at Lloyd’s of London, where he set up a market wide analytical performance and price monitoring framework. While at Lloyd’s he developed tools to assess the credibility of business plans, using Bayesian models.
Markus is an expert in modelling non-life insurance portfolios and probabilistic programming, and an Honorary Visiting Fellow at Bayes Business School, City, University of London. He is also the co-founder of the Insurance Data Science conference series and the Bayesian Mixer meetups.

Prof. Dr. Marius Lindauer has been a professor of Machine Learning at Leibniz University Hannover since 2019. He completed his PhD in 2015 at the University of Potsdam under the supervision of Prof. Dr. Thorsten Schaub and Prof. Dr. Holger Hoos. Prior to his current position, he held a PostDoc role and later was a junior research group lead at the University of Freiburg, working with Prof. Dr. Frank Hutter. Prof. Lindauer is actively involved in several prestigious AI communities, including ELLIS, CLAIRE, and the Platform Learning Systems (PLS). He co-leads AutoML.org and co-founded the research network COSEAL, the AutoML Conference, and the Institute of AI at Leibniz University Hannover. His work has garnered recognition through several international competition wins, notably in Automated Machine Learning. He has delivered numerous invited talks, including at the Open Data Science Conference in London and TEDx, as well as tutorials at major AI conferences and summer schools such as AAAI, IJCAI, and ESSAI. In 2022, Prof. Lindauer was awarded the prestigious ERC Starting Grant, Europe’s top research grant for young scientists. His research focuses on Automated Machine Learning, Bayesian Optimization, Neural Architecture Search, Interpretability, and Reinforcement Learning.

Prof. Peyman Mohajerin Esfahani is an associate professor at the Delft Center for Systems and Control. He joined TU Delft in October 2016 as an assistant professor. Prior to that, he held several research appointments at EPFL, ETH Zurich, and MIT between 2014 and 2016. He received the BSc and MSc degrees from Sharif University of Technology, Iran, and the PhD degree from ETH Zurich. He currently serves as an associate editor of Transactions on Automatic Control, Mathematical Programming, Operations Research, and Open Journal of Mathematical Optimization. He was one of the three finalists for the Young Researcher Prize in Continuous Optimization awarded by the Mathematical Optimization Society in 2016, and a recipient of the 2016 George S. Axelby Outstanding Paper Award from the IEEE Control Systems Society. He received the ERC Starting Grant and the INFORMS Frederick W. Lanchester Prize in 2020. He is the recipient of the 2022 European Control Award.

Prof. Dr. Dr. Matthias Fahrenwaldt studied mathematics at Cambridge University graduating with Bachelors and Masters degrees. He obtained a PhD in theoretical mathematics from the University of Münster and a higher doctorate (Habilitation) from RPTU Kaiserslautern. Matthias held managerial positions at KPMG and McKinsey before returning to academia: he was visiting professor at the University of Copenhagen and Associate Professor at Heriot-Watt University in Edinburgh. He has been with BaFin since 2020, initially in the internal models division and currently in a policy department for IT supervision. At BaFin he heads several projects dealing with the regulation of artificial intelligence. Matthias is also Affiliated Professor of Actuarial Mathematics at the University of Copenhagen and private lecturer at RPTU. He was awarded national and international prizes for his research. Besides his mathematical interests, he obtained a Masters degree in history from the University of Oxford and a PhD in history from the University of Düsseldorf. Matthias is on the editorial board of a book series on Ideologies in National Socialism.