Martin Kronegger

Martin Kronegger serves as a Senior Lecturer in the Department of Automation Systems at Vienna University of Technology (TU Wien), where he teaches courses including Fundamentals of Digital Systems, Computer Engineering Projects, and Scientific Projects in Computer Science for the 2025W and 2026S semesters. His academic profile demonstrates active engagement in both teaching and research within the Faculty of Electrical Engineering and Information Technology.

Dr. Kronegger's research centers on theoretical foundations of artificial intelligence with emphasis on parameterized complexity, automated planning, and answer set programming. His work bridges theoretical computer science with practical applications in knowledge representation and reasoning, as evidenced by publications in premier venues like Artificial Intelligence journal and AAAI conferences. Key research themes include:

• Backdoor techniques for planning problems
• Parameterized complexity analysis of AI problems
• QBF solving for conformant planning
• SAT-based verification methods for software models

His publication landscape reveals consistent contributions to parameterized complexity theory applied to planning and logic programming from 2011-2019, with significant work on multiparametric analysis of answer set programming and SAT-based approaches to planning problems. The research trajectory shows deepening theoretical contributions while maintaining connections to practical AI applications.

Dr. Kronegger has supervised at least one diploma thesis on planning solvers and has participated in major research projects including FAIR (2013–2018), START (2014–2022), and X-TRACT (2014–2018). His project work demonstrates sustained collaboration with research groups at TU Wien focused on computational logic and automated reasoning.

Based in the Automation Systems research group (E191-03) at TU Wien's Treitlstraße campus, he maintains active research collaborations through projects like the START program and contributes to the international answer set programming community as evidenced by involvement in the Fourth Answer Set Programming Competition.