Anushtup Nandy
Papers
2
Total Citations
8
H-Index
2
About
Anushtup Nandy is a rising star in artificial intelligence and multi-agent systems, whose work tackles the frontier of complex, real-world pathfinding. His primary research focuses on Multi-Agent Combinatorial Path Finding (MCPF), a challenging problem where multiple robots or agents must navigate collision-free routes while visiting a set of intermediate targets. This work has immediate applications in warehouse logistics, autonomous drone swarms, and automated manufacturing. In his highly cited 2024 paper, "DMS*: Towards Minimizing Makespan for Multi-Agent Combinatorial Path Finding," Nandy introduced a novel algorithm that significantly reduces the total completion time (makespan) for such systems, earning 5 citations in its first year. He has also advanced the field of pathfinding under constraints, notably in his 2025 paper on "Heuristic Search for Path Finding With Refuelling," which addresses the classic Gas Station Problem—a critical model for electric vehicle routing and long-duration drone missions where fuel or battery management is essential. With his innovative algorithmic contributions and a growing citation footprint, Nandy is establishing himself as a key figure in making multi-agent coordination both efficient and practical for the constraints of the physical world.
Research Focus
Key Achievements
Top Papers
- 1
- 2Heuristic Search for Path Finding With Refuelling3 citations · 2025