معرفی
Daniel Fišer is an Associate Professor in the Department of Computer Science at Aalborg University, Denmark, within the Technical Faculty of IT and Design. He is affiliated with the Distributed and Embedded and Intelligent Systems Group and maintains active research in automated planning and artificial intelligence.
His research interests include automated planning, symbolic search, heuristic design, lifted planning, multi-agent planning, and policy learning. His work focuses on improving the efficiency and scalability of planning algorithms through novel heuristic methods, abstraction techniques, and formal analysis of planning tasks.
Daniel Fišer's recent publications span top venues such as Artificial Intelligence Journal, AAAI, ICAPS, IJCAI, and ECAI. His work shows a strong trend toward enhancing symbolic and lifted planning through operator-potential heuristics, mutex analysis, policy validation, and integration with learning-based methods like LLMs. He has also contributed to planning competitions and benchmarking efforts.
- ICAPS 2023 Best Paper Runner-Up Award
- AAAI 2022 Outstanding Paper Award: Honorable Mention
He has advised and collaborated with several researchers and has developed open-source software tools such as cpddl, maplan, and pddl-data. Daniel Fišer holds a PhD (2021) and Master’s degree (2016, Dean’s Award) in Computer Science. His former affiliation includes Saarland University, Germany. He is actively publishing, with recent and upcoming work in 2024–2025.
