About
Ryan Hechenberger is a Research Fellow in the Department of Data Science & AI at Monash University. His research focuses on pathfinding algorithms, computational geometry, and combinatorial search. He has contributed to advancements in Euclidean shortest path computation, multi-target search strategies, and benchmarking frameworks for game AI applications.
His work bridges theoretical algorithm development with practical implementations in robotics and automated planning. Recent collaborations include studies on ray shooting techniques for Euclidean space and online path computation methods.
Ryan has published at major conferences such as the International Symposium on Combinatorial Search (SoCS) and the International Conference on Automated Planning and Scheduling (ICAPS). His research emphasizes optimizing search algorithms for efficiency and scalability in dynamic environments.
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