Publications: Multiple papers accepted by top conferences and journals such as AAAI, NeurIPS, DMKD; Awards: One survey paper on explainable anomaly detection highly cited based on ESI.
Research Experience
During his PhD, he focused on trustworthy anomaly detection, particularly for complex data like event sequences and graph-structured data in smart manufacturing contexts. His goals were to enhance accuracy, explainability, and generalizability. During his postdoc, he is working on generative AI for Math, with a particular focus on LLM for Optimization Modeling and Flow Matching and Diffusion Models.
Education
PhD from Leiden University, supervised by Dr. Matthijs van Leeuwen (daily supervisor and promotor) and Prof. Dr. Thomas Bäck (promotor). In 2024, he was a visiting PhD researcher at the DAML group, Technical University of Munich, supervised by Prof. Dr. Stephan Günnemann.
Background
Research interests: Data Mining and Machine Learning, with a strong interest in AI for Math. Introduction: Currently a guest researcher in Computer Science at Leiden University, affiliated with the EDA Lab.