Paul Peter Hager

Paul Peter Hager serves as an Assistant Professor in the Department of Statistics and Operations Research at the University of Vienna, where he teaches courses including Linear Algebra and Applied Optimization. Previously, he held a junior research group leader position at Technische Universität Berlin.

His research centers on:

• Mathematical Finance
• Machine Learning
• Stochastic Control
• Mean-Field Games
• Fractional Processes
• Gaussian Multiplicative Chaos
• Volatility Modeling

Hager pioneers applications of rough path signatures in financial mathematics, developing novel frameworks for stochastic control and calibration problems. His work bridges theoretical probability with practical machine learning implementations, particularly in volatility modeling using fractional processes and log-correlated fields.

Recent publications reveal a dominant trend in signature-based methods for optimal stopping and mean-field games, with significant contributions to fractional Brownian motion theory. His collaborative work with leading researchers like Peter Friz and Christian Bayer consistently targets high-impact journals in applied probability and financial mathematics.

Dr. Hager maintains active research collaborations and has delivered invited talks at institutions including KAUST, focusing on computational implementations of signature methods in finance.