Research

Energy-aware Autonomous Systems Lab (EAS-Lab)

The computing resources of autonomous systems and mobile devices can exploit locally and remotely connected smart sensors to execute advanced applications. For example, autonomous mobile robots must be able to manage their edge computing devices and sensors (e.g.,cameras, Lidar) to handle heavy workloads such as navigation and object recognition for balancing the application performance and the robot’s battery life; smart farms that locally generate green energy can manipulate the energy consumption of edge-computing and distributed sensors to help improve the crop quality while achieving 100% sustainability; smartphones and other smart devices such as smart watches and smart glasses can share their computing/sensing resources with each other to improve their energy efficiency. In the EAS-Lab we are interested in finding new ways to coordinate and manage these distributed autonomous computing and sensing resources to achieve high energy-efficiency, performance, and reliability. In summary, our main research interests are:

• Cyber-physical systems
• Energy-aware systems
• Internet-of-Things
• Edge Computing
• Embedded and real time systems

To conduct research with us in this area, it is very important for a student to have solid skills in algorithm development, software development (e.g., C/C++, Java, Python), software implementation, and a strong foundation in mathematics. If you are interested in joining my research group, contact me!

Leading Sponsored Research

Convergence Accelerator Track H: Leveraging Human-Centered AI Microtransit to Ameliorate Spatiotemporal Mismatch between Housing and Employment for Persons with Disabilities.

• Role: Lead PI
• Amount Awarded: $613,621.00
• Period: 12/2022 – 11/2024
• Official NSF Page: NSF