Daniel Gnad

Daniel Gnad is an Assistant Professor at Linköping University's Department of Computer Science (IDA), working within the Artificial Intelligence and Integrated Computing Systems (AIICS) division. He specializes in "Planning and model checking" within artificial intelligence, focusing on theoretical foundations and algorithmic approaches to complex planning problems.

Dr. Gnad completed his Computer Science studies at Saarland University, earning his MSc before continuing as a PhD student under Prof. Jörg Hoffmann. In 2022, he joined the RLPLab at Linköping University as a postdoctoral researcher, becoming an assistant professor in 2023. His research primarily centers on AI planning, model checking, and decoupled state-space search methodologies.

His recent publications demonstrate significant advancements in planning algorithms, pattern databases, and numeric planning techniques. Gnad's work bridges theoretical computer science with practical applications in artificial intelligence, particularly in developing more efficient search algorithms for complex planning problems. His research often involves transforming planning problems into more tractable forms through abstraction techniques and novel search topologies.

Dr. Gnad has received numerous prestigious awards recognizing his contributions to the field:

• ICAPS 2022 Best Dissertation Award for "Star-Topology Decoupled State-Space Search in AI Planning and Model Checking"
• SoCS 2022 Best Paper Award for "Additive Pattern Databases for Decoupled Search"
• SPIN 2018 Best Paper Award for "Star-Topology Decoupling in SPIN"
• Dr.-Eduard-Martin-Preis for the best dissertation of the Faculty for Mathematics and Computer Science in 2021
• Multiple recognitions at the International Planning Competition (IPC) 2018 for the "Saarplan" planning system

As a researcher at AIICS, Dr. Gnad contributes to Linköping University's strong position in artificial intelligence research. His work is part of the broader research activities within the Wallenberg Autonomous Systems Program (WASP), one of Sweden's largest research initiatives. While specific details about his advisees aren't provided in the available information, his research group likely contributes to the department's doctoral programs in computer science.

Dr. Gnad's laboratory work focuses on developing and analyzing planning algorithms, with applications ranging from theoretical computer science to practical AI systems. His recent integration of techniques like pattern databases with numeric planning represents an important direction in making planning algorithms more versatile for real-world applications.