Paper titled 'Unsupervised Anomaly Detection Algorithms on Real-world Data: How Many Do We Need?' accepted for publication in the Journal of Machine Learning Research; Master student Igor Smit won the KHMW Young Talent Graduation Award for Data Science.
Research Experience
Assistant Professor at Information System Group, Eindhoven University of Technology; Contributed to multiple H2020 and NWO research projects; Research focus includes data-driven decision-making, deep reinforcement learning, business process monitoring and optimization, and self-supervised learning.
Background
A computer science researcher, passionate about bridging the gap between artificial intelligence and engineering problems. Expertise involves the development of decision-support methods, data-driven predictive modeling, asset management tools, and predictive maintenance solutions.
Miscellany
Organizing a workshop on Trustworthy decision-making at ECAI 2024; Invited to present at EAISI AIMM Lab on utilizing transfer learning for industrial applications.