Rajiv Joshi
Papers
1
Total Citations
34
H-Index
1
About
Dr. Rajiv Joshi is a leading figure in the development of energy-efficient computing architectures, with a primary focus on memristor-based technologies for edge-AI applications. His most-cited work, "Low-Power Memristor-Based Computing for Edge-AI Applications" (2021, 34 citations), addresses the critical challenge of bringing intelligent computation to resource-constrained IoT devices. In this influential paper, Joshi pioneers novel approaches to leverage memristors—non-volatile memory devices—to perform analog computing directly at the data source, dramatically reducing the energy overhead of data movement. His contributions are pivotal for enabling applications like personalized healthcare and smart robotics, where low power consumption is paramount. By demonstrating how memristive circuits can execute neural network inference with minimal energy, Joshi has laid essential groundwork for a new generation of smart edge-devices. His work stands out for its practical focus on overcoming the fundamental energy bottleneck in distributed AI, making him a key innovator in the transition from cloud-centric to edge-based intelligence.
Research Focus
Key Achievements
Top Papers
- 1Low-Power Memristor-Based Computing for Edge-AI Applications34 citations · 2021