Education
- Thesis: Ontology Alignment: Simulated annealing-based system, statistical evaluation, and application to logistics interoperability.
- Advisers: Prof. Yao-Hua Tan and Dr. Wout Hofman.
- Thesis: Information-theoretic learning approaches to high-dimensional unsupervised data analysis.
- Adviser: Prof. G. A. Hodtani.
- Coursework emphasized software engineering fundamentals, programming, and systems design.
Professional Experience
- Develop foundation models for mass spectrometry analysis using advanced state-space approaches.
- Study analytical explanations for kernel-based models and distributional discrepancy measures such as MMD and HSIC.
- Designed explainable AI techniques for clinical decision support and interlinked guidelines (e.g., WebOfGuidelines.nl).
- Collaborated with industry partners including myTomorrows and Thuisarts.nl to integrate AI into medical workflows.
- Investigated explainable AI techniques for fake news detection systems.
- Researched deep learning, cybersecurity, and interpretable AI while supervising multiple M.Sc. theses.
- Delivered web and desktop applications with complex data backends using ASP.NET and ASP.NET MVC for regional clients.
- Collaborated with international teams (Omnia, Prototype) to build and maintain scalable ASP.NET/MVC platforms.
- Led end-to-end development: requirements gathering, architecture, data modeling, deployment, and maintenance.
