Welcome to my homepage!
I am a researcher in Software Engineering. My research is aimed at the development and empirical evaluation of advanced data-driven techniques and tools to help software engineers create more secure, trustworthy and resilient systems. The focus is on creating actionable, evidence-based, insights for assessing and understanding the risks involved with the evolution and operation of complex software-intensive systems.

Currently ongoing work addresses the following areas: (1) cybersecurity, in particular, automated assessment and repair of software security vulnerabilities; (2) autonomous self-healing systems, where we investigate how bio-inspired approaches can help build more resilient systems; and (3) intelligent analytics, to benefit from the wealth of data that is produced during software development, evolution and operation to support decision-making.

My research combines several subfields of computing, such as software analytics, software reverse engineering, software repository mining, machine learning, program comprehension, and empirical software engineering.

Leon Moonen


  • 28th IEEE/ACM International Conference on Program Comprehension (ICPC 2020, co-chair of the Early Research Achievements track (ERA))
  • 27th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2020, co-chair of the Reproducibility Studies and Negative Results track (RENE))
Consider submitting a paper and/or attending!

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  • I’ll be a panelist in the panel on ``Antifragile systems and chaos engineering’’ organized on Nov 6, 2019 by KTH and HiQ in Stockholm, SE
  • We have (fully funded) open PhD and PostDoc positions in the cureIT project on adaptive bio-inspired techniques for creating autonomous self-healing systems, funded by the Norwegian Research Council
  • I’ll be attending the SEREN4 Horizon 2020 Secure Societies Info Day, Workshop and Brokerage Event on 9 April 2019 in Riga, Latvia. Let’s meet and talk about collaboration opportunities.
  • We have (fully funded) open PhD and PostDoc positions in the secureIT project on applications of machine learning for secure software engineering, funded by the Norwegian Research Council

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