معرفی
Jarkko Peltomäki is a researcher in the Faculty of Science and Engineering, Department of Information Technology, specializing in cyber-physical systems verification and testing. His work focuses on developing advanced falsification techniques using generative models and adaptive testing strategies.
His primary research interests include:
- Cyber Physical Systems (100% fingerprint weight)
- Generative Models and GANs (33%)
- Adaptive Testing methodologies (33%)
- Falsification algorithms (33%)
- Tool Competitions like ARCH-COMP (33%)
- Requirements Engineering for complex systems (33%)
- Unmanned Aerial Vehicle validation (33%)
- Multi-arm Bandit optimization (33%)
Analysis of his 2022-2025 publications reveals increasing integration of generative adversarial networks (GANs) into cyber-physical system testing, with significant contributions to the ARCH-COMP benchmarking framework. His work demonstrates a clear evolution from traditional falsification methods toward adaptive, model-driven approaches that leverage machine learning for test generation and coverage optimization, particularly in UAV and hybrid system contexts.
Scientific awards: None documented in provided sources.
Grant activity includes participation as Co-Investigator in the European Commission-funded ADOaRT project (2021-2024), focusing on adaptive testing for cyber-physical systems. No student advising information is available. His research outputs include multiple datasets (OGAN/WOGAN Experimental Results) supporting reproducibility in falsification studies.
He actively contributes to the ARCH-COMP international research network, coordinating falsification category evaluations and developing standardized validation methodologies for hybrid system verification tools.
