معرفی
Daniel Harabor is an Associate Professor in the Department of Data Science & AI at Monash University, Australia. He holds a PhD and BSc (Honours) in Computer Science from the Australian National University (ANU). His research focuses on pathfinding algorithms, multi-agent systems, and optimization, with notable contributions to multi-agent pathfinding (MAPF), transportation routing, and constraint-based reasoning. He leads or collaborates in projects like the 2023 MAPF Competition and the Future of Urban Routing initiative.
Education:
- PhD in Computer Science, ANU (2014)
- BSc (Honours) in Computer Science, ANU (2007)
Research Interests: His work emphasizes practical and efficient solutions for combinatorial search problems, including real-time pathfinding, public transport optimization, and large-scale multi-agent coordination. He develops algorithms for dynamic environments with applications in robotics, urban planning, and logistics.
Awards:
- DECRA Research Fellowship (Australian Research Council)
Projects & Grants: He has secured funding for projects such as 'Personalised Public Transport' (2019–2025) and 'Improved Constraint Reasoning for Robust Multi-agent Path Planning' (2021–2024). His work often involves collaboration with global experts in AI and robotics.
Labs & Teams: Active in the Data Science & AI research group at Monash, contributing to MAPF competitions and open-source pathfinding tools like JPS (Jump Point Search).
