Max van Haastrecht
PhD candidate
- Name
- M.A.N. van Haastrecht MSc
- Telephone
- +31 71 527 4799
- m.a.n.van.haastrecht@liacs.leidenuniv.nl
- ORCID iD
- 0000-0002-4195-0585
Max van Haastrecht is a PhD Candidate in Cybersecurity at the Leiden Institute for Advanced Computer Science (LIACS). He studied Econometrics at the Rijksuniversiteit Groningen (RUG), where he specialised in Operations Research. He subsequently spent 1.5 years in industry as a data analyst for fraud detection. Before his current spell at LIACS, he spent the first period of his PhD at Utrecht University.
His research focuses on making cybersecurity measurable at small- and medium-sized enterprises (SMEs). Improving SME cybersecurity is the core goal of the European Horizon 2020 project GEIGER in which he is actively involved. He currently leads the validation work package of the project.
Besides his research, he thoroughly enjoys teaching and supervising students, and is always looking to improve his skills in this domain. Outside of work, he enjoys playing/coaching hockey, and helping at his community centre by teaching a computer course for beginners.
PhD candidate
- Science
- Leiden Inst of Advanced Computer Science
- Ferguson R., Khosravi H., Kovanović V., Viberg O., Aggarwal A., Brinkhuis M.J.S., Buckingham Shum S., Chen L., Drachsler H., Guerrero V.A., Hanses M., Hayward C., Hicks B., Jivet I., Kitto K, Kizilcec R., Lodge J.M., Manly C.A., Matz R.L., Meaney M.J., Ochoa X., Schuetze B.A., Spruit M.R., Haastrecht M.A.N. van, Leeuwen A. van, Rijn L. van, Tsai Y.S., Weidlich J., Williamson K. & Yan V.X. (2023), Aligning the goals of learning analytics with its research scholarship: an open peer commentary approach, Journal of Learning Analytics 10(2): 14-50.
- Haastrecht M.A.N. van, Brinkhuis M.J.S., Wools S. & Spruit M.R. (2023), VAST: a practical validation framework for e-assessment solutions, Information Systems and E-Business Management 21: 603-627.
- Haastrecht M.A.N. van, Brinkhuis M.J.S., Peichl J., Remmele B. & Spruit M. (2023), Embracing trustworthiness and authenticity in the validation of learning analytics systems, Proceedings of the 13th International Learning Analytics and Knowledge Conference. 13th International Learning Analytics and Knowledge Conference 13 March 2023 - 17 March 2023. New York, NY, USA: Association for Computing Machinery (ACM). 552-558.
- Haastrecht M.A.N. van, Golpur G., Tzismadia G., Kab R., Priboi C, David D., Răcătăian A., Baumgartner L., Fricker S., Ruiz J.F., Armas E., Brinkhuis M. & Spruit M.R. (2021), A shared cyber threat intelligence solution for SMEs, Electronics 10(23): 2913.
- Smit T., Haastrecht M.A.N. van & Spruit M.R. (2021), The effect of countermeasure readability on security intentions, Journal of Cybersecurity and Privacy 1(4): 675-704.
- Haastrecht M. van, Ozkan B.Y., Brinkhuis M. & Spruit M. (2021), Respite for SMEs: A systematic review of socio-technical cybersecurity metrics, Applied Sciences 11(15): 6909.
- Haastrecht M. van, Sarhan I., Yigit Ozkan B., Brinkhuis M. & Spruit M. (2021), SYMBALS: A Systematic Review Methodology Blending Active Learning and Snowballing, Frontiers in Research Metrics and Analytics 6: 685591.
- Haastrecht M., Sarhan I., Shojaifar A., Baumgartner L., Mallouli W. & Spruit M. (2021), A threat-based cybersecurity risk assessment approach addressing SME needs. In: ARES 2021: The 16th International Conference on Availability, Reliability and Security.: Association for Computing Machinery (ACM). 158.
No relevant ancillary activities