معرفی
Ostap Okhrin serves as a Professor of Econometrics and Statistics at Dresden University of Technology, holding the Chair of Econometrics and Statistics with a special emphasis on Transportation Systems. His academic career is marked by a strong focus on methodological advancements in econometrics and statistics, applied to complex real-world problems in transportation and finance.
Professor Okhrin's research interests span econometrics, statistical theory, copula modeling, time series analysis, and financial risk management. He has significantly expanded into machine learning and reinforcement learning applications for autonomous systems, with deep expertise in traffic flow modeling, autonomous driving, maritime navigation, and financial volatility estimation. His work bridges theoretical statistics with practical engineering challenges, particularly in transportation systems and risk forecasting, addressing high-dimensional data and dynamic environments through innovative methodological frameworks.
Analysis of Okhrin's recent publications (2024-2025) reveals a pronounced interdisciplinary trajectory integrating reinforcement learning with transportation engineering. Key themes include drone-based trajectory data collection for traffic monitoring, algorithms for autonomous ships on inland waterways, and Sim2Real transfer frameworks for autonomous driving. Concurrently, he advances financial econometrics through high-frequency risk forecasting models incorporating realized moments. This dual focus demonstrates his ability to transfer statistical innovations across domains while maintaining rigorous theoretical foundations in copula theory and time series analysis.
