Papers
1
Total Citations
3
H-Index
1
About
Jaya Dofe is a researcher at the forefront of energy-efficient computing for the Internet of Things (IoT). Her work centers on the critical challenge of power consumption in artificial intelligence hardware, particularly for resource-constrained IoT devices. Her most-cited paper, "Machine Learning–Enabled Techniques for Reducing Energy Consumption of IoT Devices" (2021, 3 citations), introduces a novel AI hardware architecture designed to dramatically lower energy demands. This contribution addresses a fundamental bottleneck in IoT deployment, where battery life and thermal constraints often limit functionality. By proposing a design rooted in standard machine learning principles, Dofe’s work offers a practical path toward more sustainable and scalable AI at the edge. Her research is essential reading for engineers and students seeking to bridge the gap between high-performance AI and ultra-low-power hardware, making her a rising voice in the push for greener, smarter IoT ecosystems.
Research Focus
Key Achievements
Top Papers
- 1