Drona Kandhai is professor in data-driven Computational Finance at the Computational Science Lab and the Stochastics group of the University of Amsterdam. He has been active in the financial industry for more than 20 years, working on pricing and risk model validation, development, and integration in IT systems. Kandhai has extensive experience across a broad range of financial products and has held positions in various departments at ABN AMRO and ING Bank. In addition to his academic role, he is the head of the Quantitative Analytics department for Financial Markets at ING Amsterdam.

He holds a PhD in Computational Physics from the University of Amsterdam, where he focused on numerical modelling and simulation of complex fluid flows. His main research interests include using data-driven microscopic simulations to understand complex financial market dynamics, integrating underlying mechanisms into holistic multi-scale models for derivative pricing and risk management, and applying data-driven methods to financial fraud. Kandhai has published widely in scientific journals.

Sander Klous is full professor in AI & Audit at the University of Amsterdam, holding a joint position between the Amsterdam Business School (as scientific director of the AI4Fintech group) and the Informatics Institute (as group leader of the Complex Cyber Infrastructure group). He is also a partner at KPMG Advisory in the Netherlands, where he advises board-level executives on Digital Transformations, with a focus on the Environmental, Social and Governance (ESG) impact of data and AI.

Sander manages an extensive research portfolio and supervises around 5–10 PhD students at any time. He has a strong track record in acquiring and managing large-scale, high-impact multidisciplinary research projects that require advanced and pragmatic stakeholder management. His first book, We are Big Data, is one of the best-selling books on big data in the Netherlands and was a runner-up for management book of the year in 2015.

He has worked on multiple projects for CERN, the world’s largest physics institute in Geneva, and was part of the ATLAS collaboration that discovered the Higgs Boson in 2012 (for which Higgs and Englert received the Nobel Prize in 2013). He has received numerous grants and awards related to high-performance distributed computing and is among the most cited researchers at the University of Amsterdam.

Erman Acar is an assistant professor of Explainable AI (XAI) in Finance at the ILLC and the Informatics Institute (IvI) at the University of Amsterdam. His research interests include neurosymbolic AI, explainability and interpretability in AI, computational logic, and multi-agent systems, with applications in financial technologies. He is a regular contributor to and reviewer for top-tier AI conferences.

He obtained his PhD in AI from the University of Mannheim, Germany, and holds a master’s degree in Computational Logic from TU Vienna and TU Dresden. He has been a visiting researcher at several institutions, including the University of Bozen-Bolzano, University of Amsterdam, University of Calabria, and the University of Oxford. More information is available at sup-erman.github.io.

Sven Karbach is an assistant professor of Data-Driven Mathematical Modelling and Computing in Finance, affiliated with the Stochastics group at the KdVI and the Computational Science Lab at the IvI. His research focuses on developing non-parametric models for financial markets, with a strong emphasis on applications in renewable energy markets and sustainable finance. He also works on stochastic optimization problems related to hedging forward curve derivatives and optimal trading strategies.

Before joining the faculty, Sven was a postdoctoral researcher at the University of Hamburg. He earned his PhD in Mathematics from the University of Amsterdam in 2022.

Simon Trimborn is an assistant professor of Econometrics and Data Science at the Amsterdam School of Economics, University of Amsterdam. Prior to joining the UvA, he held academic positions at City University of Hong Kong and the National University of Singapore. He completed his PhD at Humboldt-Universität zu Berlin, with a dissertation on “Statistics of Digital Finance.”

His research centers on high-dimensional time series analysis, addressing problems in social media, cryptocurrency, blockchain, and finance. He contributes to network modeling, sustainable finance, and blockchain analytics. His work appears in journals such as Journal of Financial Econometrics, Journal of Empirical Finance, and R Journal. He serves on the editorial boards of Digital Finance, Statistics, Statistical Methods and Applications, and Annual Review of FinTech. He is also a member of the Scientific Board of the CRIX index.

Fernando is an associate professor at the Informatics Institute of the University of Amsterdam. He is part of the SIAS group and leads the Prosocial Dynamics Lab. He also serves as the scientific lab manager of the Civic AI Lab. In addition, he holds a joint position with ING through the Kickstart AI initiative, where he works on bias, transparency, and strategic classification in banking applications.

His research lies at the intersection of AI, multi-agent systems, and complex systems. He studies behavioral dynamics in systems of adaptive learning agents and aims to design prosocial and fair AI systems. Previously, Fernando was a postdoctoral fellow at Princeton University, and he earned his PhD in Computer Science and Engineering at Instituto Superior Técnico in Lisbon.

Marcel Boersma is an assistant professor at the Amsterdam Business School of the University of Amsterdam, specializing in the development of AI-driven methods for financial auditing. Alongside his academic position, he is a Senior Manager at KPMG, where he leads product development within the firm’s innovation team.

Marcel regularly collaborates with interdisciplinary research groups and industry partners, applying advanced computational and AI methods to real-world challenges. He has contributed to international conferences and journals and is committed to bridging academia and industry through impactful research.