Academia
As a visiting researcher at the faculty of Technology, Policy & Management, I advise MSc and PhD students and participate in academic research within the cybersecurity, education, and data analytics domains.
Paper highlight
EvilEDR: Repurposing EDR as an offensive tool (2025):
in the proceedings of the 34th USENIX Security Symposium
Paper highlight
IAM role diet: A scalable approach to detecting RBAC inefficiencies (2025):
in the proceedings of the 55th Annual IEEE/IFIP International Conference on Dependable Systems and Networks
— UNIVERSITIES
TUDelft
Radboud Nijmegen
Vrij University
WUR
Theses supervision
2024-ongoing: PhD advisor of Kotaiba Alachkar, TUDelft – Cybersecurity
2025: MsC advisor of Tamara Tataru, TUDelft – Cybersecurity.
Thesis: A Data-Driven Approach to Dependency Risk Prioritization
2025: MSc advisor of Chrysanthos Kindynis, TUDelft – Cybersecurity.
Thesis: Breaking the Trade-Off: Adaptive Optimization for Scalable, Minimal RBAC
2024: MSc advisor of Stefani Slavova, TUDelft – Artificial Intelligence, Education.
Thesis: Bridging the gap between innovation and application (cum laude)
2024: MSc advisor of Ignjat Pejic, TUDelft – Artificial Intelligence, Cybersecurity.
Thesis: Adding context to cybersecurity alerts
2024: MSc advisor of Mohamed Ramdan, TUDelft – Artificial Intelligence, Cybersecurity.
Thesis: Evaluating DeepCASE in a Multi-Detection Systems Setting
2024: MSc advisor of Samuel Haeck, Radboud University Nijmegen – AI, Cybersecurity.
Thesis: Reputational Swarm Learning in Cybersecurity
2023: MSc advisor of Anne-Kee Doing, TUDelft – Artificial Intelligence, Education.
Thesis: New metrics to measure the effect of anti-phishing training
2023: MSc advisor of Daan Hofman, TUDelft – Artificial Intelligence.
Thesis: Unstable Log Sequence Anomaly Detection: Introducing VoBERT
2023: MSc advisor of Erik Sennema, TUDelft – Artificial Intelligence, Cybersecurity.
Thesis: Elastic gradient boosting: limited labels and epistemic uncertainty quantification
2017: MSc advisor of Ruben Sikkes, Vrij University – Artificial Intelligence.
Thesis: Quantifying the role of personalisation in different recommender systems
2017: BSc advisor of Marcoen Beeks, Amsterdam Univ. of Applied Sciences
Thesis: Employing personalisation to augment online conversion rates
2016: MSc advisor of Jeroen van den Hoven, Vrij University – AI, Buss. Analytics.
Thesis: Clustering with optimised weights for Gower’s metric: Using hierarchical clustering and quasi-Newton methods to maximise the cophenetic correlation coefficient.
2014: MSc advisor of Dimitra Kalosynaki, Wageningen University – Physics, Chemistry
Thesis: Model simulation of the morning transition effect on boundary-layer dynamics and chemistry during the PEGASOS campaign in the Netherlands.
See a list of my academic publications here.
Support Vector Machines: Employing a Lagrange multiplier to maximise the margin between the positive and negative samples