TU Wien Informatics

ASAI Master Thesis Award for Michael Bernreiter and Tobias Geibinger

  • 2023-07-05
  • Research
  • Students

The Austrian Society for Artificial Intelligence (ASAI) honors two TU Wien Informatics graduates for their outstanding master theses.

Tobias Geibinger (l) and Michael Bernreiter (r).
Tobias Geibinger (l) and Michael Bernreiter (r).
Picture: Nadja Meister, Michael Bernreiter / Design: TU Wien Informatics

On June 5, 2023, the Austrian Society for Artificial Intelligence (ASAI) honored two exceptional researchers for their work in AI with the ASAI Master Thesis Award: Michael Bernreiter and Tobias Geibinger are both PreDoc Researchers at TU Wien Informatics and have made significant contributions to their field early in their academic career. They are both awarded the ASAI Master Thesis Award 2023, endowed with a prize of € 2000.

In his thesis, A General Framework for Choice Logics Michael Bernreiter focuses on developing a general framework for choice logics, a topic applicable in various domains. Choice logics enable us to express preferences, allowing for more precise and systematic AI decision-making. Bernreiter’s novel framework extends the capabilities of existing logics, providing greater flexibility and expressiveness in handling preferences. This advancement opens doors to more personalized and tailored decision support systems, recommender systems, user interfaces, and more – making AI more effective and thus empowering individuals and organizations to make choices that align with their preferences and priorities. Michael Bernreiter was supervised by Stefan Woltran, Head of the Research Unit for Databases and AI and Co-Head of CAIML; and Jan Maly.

Tobias Geibinger’s thesis Investigating Constraint Programming and Hybrid Answer-Set Solving for Industrial Test Laboratory Scheduling revolves around solving the complex scheduling problem faced by industrial test laboratories. These laboratories perform a vast number of tests using specialized equipment and qualified personnel, all while adhering to strict deadlines and numerous constraints. Geibinger’s research introduces novel approaches to optimize the scheduling process, improving efficiency and solution quality. By leveraging constraint programming and hybrid answer-set solving, Geibinger’s work provides innovative techniques to enhance resource allocation and streamline operations. These advancements can potentially revolutionize the laboratory workflow, resulting in timely results, cost reduction, and improved customer satisfaction. Tobias Geibinger was supervised by Nysret Musliu, Professor at our Research Unit for Databases and AI.

About the Awardees

Michael Bernreiter

Michael Bernreiter is a PreDoc Researcher at the Research Unit for Databases and AI, working under the supervision of Stefan Woltran and Wolfgang Dvořák. His research focuses on preferences in artificial intelligence. Specifically, Bernreiter investigates preferences in abstract argumentation and logic-based formalisms with respect to their impact on computational properties. His educational background is in computer science. He obtained his bachelor’s degree at FH Technikum Wien and his master’s in Logic and Computation at TU Wien Informatics. At COMMA 2022 (9th International Conference on Computational Models of Argument) Bernreiter received the Best Student Paper Award for his paper with Wolfgang Dvořák and Stefan Woltran titled “Abstract Argumentation with Conditional Preferences”.

Tobias Geibinger

Tobias Geibinger is a PreDoc Researcher at the Institute of Logic and Computation under the supervision of Thomas Eiter and Agata Ciabattoni. He is a recipient of a DOC Fellowship of the Austrian Academy of Sciences (ÖAW). Geibinger works on notions of explainability in Answer-set Programming (ASP), especially for advanced language features and hybrid forms of ASP. Further research interests include logic in general and particularly in the context of AI. Before his DOC Fellowship, Tobias was a Master’s student and a Project Assistant at the TU Wien Informatics, working with Nysret Musliu on discrete optimization for scheduling and related topics like optimization in Knowledge Representation (KR) paradigms or hybrid systems.

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