About
Jendrik Seipp is an Associate Professor in Artificial Intelligence at Linköping University (LiU), Sweden. He leads the 'Representation, Learning and Planning' lab within the AIICS division of the Department of Computer and Information Science (IDA). His research focuses on automated planning, particularly integrating machine learning with classical planning methods.
Education:
- Docent in Computer Science, Linköping University (2022)
- Ph.D., University of Basel, Switzerland (2018)
- M.Sc. and B.Sc., University of Freiburg, Germany (2009–2012)
Research Interests:
Seipp specializes in classical planning systems, cost partitioning algorithms, heuristic search, and abstraction methods. His work emphasizes optimizing planning efficiency through techniques like saturated cost partitioning and Cartesian abstractions. He contributes to open-source planning tools such as Scorpion and Fast Downward, aiming to make planning accessible to broader audiences.
Awards:
- IJCAI 2021 Distinguished Paper Award
- ICAPS 2020 Best Dissertation Award
- Multiple first/second places in international planning competitions (IPC, CoRe Challenge)
Advising & Grants:
Seipp leads the development of planning systems and frameworks like Scorpion, which won awards at ICAPS 2022 and IJCAI 2021. He collaborates on projects funded by the Wallenberg AI, Autonomous Systems and Software Program (WASP). His lab focuses on advancing symbolic AI methods and their applications in real-world planning tasks.
Labs & Teams:
He heads the 'Representation, Learning and Planning' lab at LiU, fostering interdisciplinary research in AI planning and optimization. The lab develops tools like Downward Lab for experiment management and contributes to open-source planning communities.
