Artificial Intelligence Finance Research Group (AI-Finance)

AI-Finance explores how artificial intelligence, machine learning, and data science can be combined with economic reasoning to address complex, data-intensive problems—particularly in the domain of financial markets. We focus on understanding and modeling uncertainty, extracting signals from noisy or incomplete data, and building algorithmic decision systems grounded in economic logic.

We are especially interested in the analytical and computational challenges posed by financial market data—most notably from options and high-frequency trading environments. These markets offer both vast information content and structural complexity, making them an ideal testing ground for the interplay between statistical learning, optimization, and market design.

Our group works closely with the KABFI Ph.D. program, contributes to advanced teaching at the Bachelor and Master levels, and mentors students through project-based learning and thesis supervision. Many of our students transition into research roles or competitive positions in quantitative finance, consulting, and AI-focused industry tracks.

Our approach is interdisciplinary and collaborative. We work with researchers in finance, computer science, and statistics to develop methods that are technically rigorous, economically interpretable, and applicable across a range of domains. Ongoing and planned collaborations with other universities expand this network and enhance opportunities for students to work on joint projects with researchers across Europe.