The Principles, Application, Perspectives and Potential of Model-Based Diagnosis
 

2 December 2025 | Online | 11:00 | Ingo Pill (Graz University of Technology)

Abstract
Starting with its connections to verification, I will outline the basics of model-based diagnosis (MBD). We will delve into the underlying concept of reasoning from first principles, will discuss computational concepts, and will look at extensions for inspecting temporal behavior as well as multiple scenarios. In order to illustrate its application, we will look into how to diagnose formal specifications (and models) in Amir Pnueli’s temporal logic of programs (LTL) and more for infinite and finite computations. I will conclude by puting MBD into perspective, mentioning some competing concepts and a short outline of some open challenges in MBD research. 

Bio

Since 2020, DI Dr. techn Ingo Pill has been an external lecturer with the Institute of Software Engineering and AI (SAI, former Institute for Software Technology) at Graz University of Technology.  From 2020 to 2024 he was a staff scientist with the Embedded Systems division of the Silicon Austria Labs (SAL) in Graz. Before joining SAL in 2020, he was a senior scientist with the Software Engineering & Artificial Intelligence group at SAI where he completed his PhD in Formal Verification in 2008. His research interests lie in symbolic AI and formal methods, with a special focus on diagnosis and its integration with verification, control, and sub-symbolic AI techniques in order to facilitate resilient systems. Ingo is a recognized expert in model-based diagnosis and reasoning as well as verification, is a member of AAAI, ACM and ASAI/ÖGAI, reviews for top journals and conferences, and has been a regular (senior) program committee member of leading AI

venues like AAAI, IJCAI or ECAI for which he received several awards. He has been active in organizing workshops and conferences, e.g., as co-chair of the International Conference on Principles of Diagnosis and resilient systems (DX) (2014, 2017, 2023, 2024, 2025) for which he also initiated the Steering Committee in 2023 that he has been chairing since then, as co-chair of the Dagstuhl Seminar 24031 “Fusing Causality, Reasoning and Learning for Fault Management and Diagnosis) in 2024, and in several capacitites for further conferences and workshops in the area of AI. He received several awards, including the Best Paper Award at the DX conference in 2025. He co-supervised several master and PhD students and has been chair or member of MSc/PhD examination boards, e.g, at TU Graz, ANU, Ben Gurion University of the Negev, or the University of Trento. At SAL, Ingo was one of three members of the SAL doctoral college management team who governed the SAL-DC and who lead and authored the multi-million MSCA-Cofund program CRYSTALLINE with 18 PhD students (funding of 2.4M€) that started in 2024.