Quy Le Xuan

Quy Le Xuan is a Research Associate at the Institut für Informationsverarbeitung (Institute for Information Processing) of Leibniz Universität Hannover, where he has been pursuing his PhD since March 2021 under the supervision of Professor Jörn Ostermann. His research focuses on advanced machine learning methodologies applied to industrial predictive maintenance and autonomous systems.

Education:

• M.Sc. in Electrical Engineering and Information Technology (Communications Engineering), Leibniz Universität Hannover, 2020 (Graduated with distinction)
• B.Sc. in Electrical Engineering and Information Technology (Communications Engineering), Leibniz Universität Hannover, 2017 (Graduated with distinction)

Research Focus: Mr. Le Xuan's work bridges theoretical machine learning and practical industrial applications. Core areas include deep learning architectures (representation learning, uncertainty-aware networks), learning paradigms (transfer, self-supervised, and lifelong learning), and specialized applications in predictive maintenance (RUL prediction, PHM, anomaly detection) for manufacturing ecosystems.

Publications Overview: His recent publications demonstrate a strong focus on Bayesian neural networks for fault prognostics, domain adaptation techniques for machinery lifetime prediction, and uncertainty quantification in industrial deep learning models, primarily within predictive maintenance contexts.

Awards and Honors:

• Distinction (Auszeichnung) in both Bachelor’s and Master’s degrees

Student Advising and Projects: Mr. Le Xuan actively mentors students for theses and HiWi positions, contributing to institutional projects including IIP Ecosphere and Predictive Maintenance initiatives. He collaborates within Professor Ostermann's research group on industrial AI solutions.