Papers
2
Total Citations
42
H-Index
2
About
Ruimin Cao is a researcher whose work bridges the critical intersection of cyber-physical systems (CPS) and advanced optical sensing technologies. His primary research areas include the modeling and decision-making of complex CPS, as well as the development of innovative tactile sensors. In his most cited work, "Modeling and Decision-Making Methods for a Class of Cyber–Physical Systems Based on Modified Hybrid Stochastic Timed Petri Net" (2020, 26 citations), Cao introduced a novel framework to address the intricate challenges of CPS that integrate discrete events, continuous processes, stochastic phenomena, and time delays—a foundational contribution to the field. Additionally, his paper "A liquid lens-based optical sensor for tactile sensing" (2022, 16 citations) showcases his ingenuity in designing high-sensitivity, simple-structured optical sensors for applications in robot manipulation and health monitoring. With a growing citation impact, Cao’s work is recognized for its practical relevance and theoretical depth, offering valuable tools for engineers and researchers tackling real-world CPS and sensing challenges. His achievements highlight a promising trajectory in advancing both computational models and hardware innovations.
Research Focus
Key Achievements
Top Papers
- 1
- 2A liquid lens-based optical sensor for tactile sensing16 citations · 2022