Olga Fink

Olga Fink is a Tenure Track Assistant Professor in the Department of Civil Engineering (CE) at École Polytechnique Fédérale de Lausanne (EPFL). Her research focuses on intelligent maintenance and operations systems, with an emphasis on data-driven infrastructure condition monitoring and machine learning applications for predictive maintenance. She teaches courses such as Data Science for Infrastructure Condition Monitoring and Machine Learning for Predictive Maintenance Applications. Fink is also involved in doctoral programs in Civil and Environmental Engineering and Robotics, Control, and Intelligent Systems, serving on PhD program committees. She is based in Building GC, Room A3 424, Lausanne, and can be contacted at olga.fink@epfl.ch.

Olga Fink is a researcher specializing in Physics-Informed Machine Learning, Fault Detection & Diagnosis, Prognosis, Deep Learning, and Artificial Intelligence. Her work focuses on integrating physical models with machine learning to enhance predictive maintenance and fault diagnosis in complex systems. She has published extensively on topics such as deep learning for prognostics and health management, digital twins, and uncertainty quantification in engineering applications. Her research includes the development of novel methods for fault detection, anomaly detection, and domain adaptation in industrial settings. Fink's contributions span across fault diagnosis, reliability prediction, and real-time model calibration using advanced machine learning techniques.