Mathematics

Mathematical research is essential for advancing the natural sciences, technology, economics, and society. Mathematical methods and analyses play a vital role in diverse applications, including meteorology and climate research, financial and energy markets, public health, and the foundations of artificial intelligence.

The close integration of theory and practice sparks new and exciting questions that demand innovative mathematical solutions. This dynamic interplay creates promising opportunities for both research and practical application. At KIT, scientists collaborate on interdisciplinary research projects to analyze current problems, develop novel mathematical tools, and drive significant progress in both applied fields and mathematics itself.

The KIT Graduate School Computational and Data Science provides doctoral and master’s students with a broad interdisciplinary program that brings together advanced mathematical research and real-world applications. The Computational and Data Science degree program integrates mathematics and computer science with a field in the natural sciences, engineering, or economics.

Emerging Field

Mathematics in Sciences, Engineering, and Economics

Mathematics in Sciences, Engineering, and Economics (MathSEE) represents interdisciplinary, mathematically driven cutting-edge research. At its core lies a distinctive tandem principle: 

On one hand, advanced methodological expertise in the mathematical sciences is closely interwoven with real-world applications, enabling breakthroughs across a wide spectrum of domains. These include atmospheric and earth sciences, communication technologies, financial and energy markets, as well as public health. On the other hand, the challenges arising in these applications areas spur foundational innovation in mathematics itself. This reciprocal dynamic fosters progress in key mathematical disciplines such as analysis, numerics, statistics, but also high-performance computing and artificial intelligence methods, ensuring that theoretical development and practical relevance go hand in hand.

MathSEE’s research portfolio reflects this dual approach and spans a broad range of forward-looking topics. These include probabilistic models for predicting and analyzing atmospheric and geophysical phenomena and their evaluation, transparent and robust predictions and their role in economic decision-making, as well as the mathematical analysis and simulation of wave phenomena under real-world conditions across diverse applications – from optics to biomedical engineering and applied geophysics.

Research Highlights

Illustration von Wellen KIT

Fascination of Waves

Waves are everywhere: we see light waves, hear sound waves, our hearts beat because of depolarization waves, and modern communication relies heavily on electromagnetic waves. To understand their behavior is to understand nature itself. That’s why the Collaborative Research Center "Wave Phenomena: Analysis and Numerics" aims to explore wave propagation in real-world scenarios, simulate it with advanced numerical methods, and ultimately control it – by tightly integrating analysis and numerics.

Price Formation in Financial Markets

The research group “Financial Markets and Frictions – An Intermediary Asset Pricing Approach” examines how financial intermediaries – such as banks, insurance companies, and other brokers – shape price formation in capital markets. Their work centers on understanding why risk premia vary substantially over time and across different asset classes. The team explores whether a perspective focusing on financial intermediaries, rather than individual households, provides deeper insights into these dynamics.

Flood Forecasting with Artificial Intelligence

Heavy rainfall and flooding threaten communities, ecosystems, and infrastructure. In small watersheds, warning times are especially short and forecasts often lack reliability. Current hydrological models still struggle to accurately capture rapid responses to extreme weather in these regions. To address this, the research project “AI-Based Flood Prediction for Small River Basins in Germany” is developing AI-driven methods to deliver consistent forecasts nationwide and improve prediction accuracy during extreme events.