Bernhard Aichernig

Bernhard Aichernig is an Associate Professor at the Institute of Software Engineering and Artificial Intelligence. His work bridges formal methods, model-based testing, and artificial intelligence, with a focus on automata learning, digital twins, and AI-assisted programming.

• Institution: Institute of Software Engineering and Artificial Intelligence
• Key Research Areas: Model-Based Testing, Automata Learning, AI-Driven Verification

His research explores the integration of machine learning into formal verification, enabling scalable testing of complex systems like IoT devices and reinforcement learning agents. Recent projects include AI-Augmented DevOps frameworks (AIDOaRT) and digital twin validation (LearnTwins).

Notable scientific awards include multiple best paper recognitions at SEFM (2020, 2021) and the TAYSIR Competition first place (2023). His publications emphasize hybrid approaches combining genetic programming, SMT solving, and neural networks for system modeling.

• 2025: AI-assisted programming, timed automata via domain knowledge
• 2024: Stochastic environment modeling, Git system learning
• 2023: Reinforcement learning under partial observability, digital twins for VPN servers

He actively contributes to testing frameworks like AALpy and investigates explainable AI for fault diagnosis in cyber-physical systems.