Alexander Egyed

Alexander Egyed serves as a full Professor at the Institute of Software Systems Engineering, Johannes Kepler University Linz, where he directs the LIT Secure and Correct Systems Lab. His leadership spans 350+ research outputs and 50+ projects, with current active grants securing research through 2029 in critical software engineering domains.

His research focuses on advancing model-driven engineering practices through innovations in software evolution, variability management, and process guidance. Key contributions include reactive link propagation for model consistency, AI-driven refactoring of legacy systems, and industrial-strength process compliance solutions. His work bridges formal methods with practical industrial applications, particularly in secure system development and software modernization.

Recent publications (2024-2025) reveal a pronounced shift toward AI-integrated solutions for legacy system transformation, with consistent emphasis on scalable techniques for model consistency and variability control. This trajectory demonstrates increasing industrial collaboration in developing actionable engineering guidance tools.

His scientific excellence is recognized through:

• ACM Best Paper Award (2015)
• ACM Recognition of Service Award (2024)
• ACM SIGSOFT Distinguished Paper Awards (2021, 2023)
• Best Paper Award (2014)

Professor Egyed currently leads major funded initiatives including the FWF-sponsored 'Co-Existence of Modeling Language Versions and Co-Evolution' (2025-2029) and dual 'RefactorAI' projects for legacy system modernization (FFG 2025-2028). His supervision of 12 graduate students reflects commitment to academic mentorship alongside his extensive editorial and program committee service across 147 recorded academic activities.

He directs the LIT Secure and Correct Systems Lab, a nexus for interdisciplinary research in formal verification, model-driven security, and AI-assisted software engineering, maintaining strong industry partnerships for real-world validation of research outputs.