Abhijeet Saraha
Papers
1
Total Citations
9
H-Index
1
About
Abhijeet Saraha is a researcher at the forefront of edge AI and collaborative robotics, specializing in the efficient deployment of deep neural networks (DNNs) on resource-constrained platforms. His seminal work, "Characterizing the Execution of Deep Neural Networks on Collaborative Robots and Edge Devices" (2019, 9 citations), provides a critical framework for understanding the performance bottlenecks that arise when running complex DNNs on edge hardware. By systematically analyzing latency, energy consumption, and memory constraints, Saraha’s research bridges the gap between high-accuracy AI models and the real-time demands of autonomous systems. His contributions are pivotal for enabling collaborative robots to process sensor data locally, reducing reliance on cloud infrastructure and improving response times in dynamic environments. This work has laid the groundwork for more efficient edge inference, directly impacting applications in industrial automation, smart manufacturing, and autonomous navigation. Saraha’s insights continue to guide engineers and researchers seeking to optimize AI workloads for the next generation of intelligent, decentralized systems.
Research Focus
Key Achievements
Top Papers
- 1