Bonnie Ferri
Papers
3
Total Citations
11
H-Index
2
About
Bonnie Ferri is a leading researcher in the intersection of control systems and power-aware computing, with a focus on developing intelligent, resource-efficient software frameworks for embedded and real-time applications. Her major contributions center on the design of compute-aware control systems—controllers that dynamically adapt to the power and performance constraints of the underlying hardware. Ferri pioneered the 2QoSM framework, a Q-learning-based quality-of-service manager that enables application-guided, platform-agnostic power management. This work, detailed in her most-cited paper (2020, 6 citations), introduces a software architecture that allows control systems to proactively modify low-level power managers in response to physical system demands. Her subsequent research (2022, 3 citations; 2021, 2 citations) demonstrates the effectiveness of reinforcement learning for dynamic power management, reducing overhead while maintaining performance. Ferri’s work is notable for bridging control theory and machine learning, offering practical solutions for energy-constrained devices. Her achievements include advancing the field of power-aware embedded systems, with her frameworks providing a foundation for next-generation, adaptive control applications in IoT and autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Low-Overhead Reinforcement Learning-Based Power Management Using 2QoSM3 citations · 2022
- 3