Ramana M. Pidaparti
Indiana University – Purdue University Indianapolis, University of Georgia
Papers
5
Total Citations
72
H-Index
4
About
Ramana M. Pidaparti is a pioneering researcher whose work bridges mechanical engineering, materials science, and collective robotics. His early contributions include developing neural network-based material models for composites, addressing complex behaviors like anisotropy and microcracking—a foundational approach that has garnered over 50 citations and influenced constitutive modeling. More recently, Pidaparti has focused on multi-robot systems, studying how heterogeneity (e.g., symbiotic relationships like mutualism and parasitism) impacts collective behaviors in search-and-rescue missions. His innovative frameworks, such as Graded Particle Swarm Optimization (GPSO) and Knowledge Transfer through Behavior Trees (KT-BT), advance swarm intelligence by enabling efficient information sharing and adaptive learning among agents. With over 60 citations across his most-cited works, Pidaparti’s research has significant implications for autonomous systems, disaster response, and bio-inspired engineering. His work exemplifies a unique synthesis of computational modeling and biological inspiration, offering practical solutions for complex, distributed systems.
Research Focus
Key Achievements
Top Papers
- 1Material model for composites using neural networks51 citations · 1993
- 2
- 3Graded Particle Swarm Optimization (GPSO)6 citations · 2016
- 4
- 5