Viraj Parimi
Papers
1
Total Citations
2
H-Index
1
About
Viraj Parimi is a rising researcher at the intersection of robotics, artificial intelligence, and autonomous systems, with a core focus on multi-agent coordination and adaptive sampling. His most-cited work, "Multi-Agent Vulcan: An Information-Driven Multi-Agent Path Finding Approach" (2024), tackles the critical challenge of deploying autonomous vehicles to explore hazardous or inaccessible environments where human operation is impractical or dangerous. Parimi’s major contribution lies in developing online control algorithms that enable teams of robots to intelligently gather information—a process known as adaptive sampling—while simultaneously solving complex multi-agent pathfinding problems. By fusing information-theoretic objectives with path planning, his approach allows autonomous fleets to dynamically seek out phenomena of interest without prior knowledge of the environment. Though early in his career, his work has already garnered attention (2 citations in its first year), signaling its relevance to pressing applications in environmental monitoring, disaster response, and planetary exploration. Parimi’s research promises to make autonomous exploration more efficient, scalable, and responsive, positioning him as a promising voice in the next generation of multi-robot systems engineering.
Research Focus
Key Achievements
Top Papers
- 1