Four ECE graduate students recognized by NSF Graduate Research Fellowship Program

Demba’s research is focused on developing robust low powered localization technology for Artificial Intelligence enabled Internet of Things in locations where GPS is limited or blocked. He relies on trained neural networks and machine learning models to improve localization accuracy and enhance performance. This work could improve the safety of activities such as driving, firefighting rescue operations, remote surgery, and traversing harsh environments. He is co-advised by Mingyan Liu, the Peter and Evelyn Fuss Chair of ECE, and Prof. Hun-Seok Kim.

Demba earned his bachelor’s degree in Electrical Engineering from the University of Mississippi. He is an active member of the ECE Graduate Student Council where he runs BuddEEs, an ECE PhD Peer Mentoring program. He also serves as Treasurer of the Graduate Society of Black Engineers and Scientists. He was recently awarded the 2021 Ada Lovelace Fellowship by Microsoft Research.

Yixin is working on semiconductors for artificial photosynthesis, in which solar energy is captured by the semiconductor and stored in the form of chemical fuels, the generation and use of which are carbon neutral or even carbon negative. In particular, he grows and characterizes crystalline nanostructured III-nitrides via molecular beam epitaxy with the ultimate goal of achieving high efficiency and stability as required for commercial viability. He is advised by Prof. Zetian Mi.

Yixin grew up in Shenzhen, a vibrant immigrant city on the southern coast of mainland China. He attended Amherst College in Massachusetts for bachelor’s degree, where he found himself to have gathered enough intellectual tools to try research in a technical engineering field for which he sensed social urgency.

Sunny is currently researching wind farm aerodynamic models and how they can be adapted to control and optimize a wind farm’s power output. Control algorithms often need models that are both reasonably accurate and fast to run. While there exist high-fidelity models of wind farms, they are too complex to be computed in real-time. Thus, wind farms need models specifically developed for control. Through such work, Sunny ultimately hopes to make wind farms more efficient, less intermittent, and easier to maintain. He is advised by Professors Johanna Mathieu and Peter Seiler.

Sunny graduated from the University of California, Berkeley, with a B.S. in Mechanical Engineering in 2020. During the summer of 2020, he worked with the Commercial Buildings Group at the National Renewable Energy Laboratory on using data science to assess the health of solar panels. He also enjoys listening to and playing music.

Hannah is a first year PhD in the Power Systems research area. Her research is focused on optimization and control strategies for reducing the cost and environmental impacts of power systems. She is particularly interested in exploring integration of distributed flexible resources such as energy storage, electric loads, and distributed renewable resources in power system operation. She is advised by Professor Johanna Mathieu.

Hannah received her B.S. in Mechanical Engineering from the University of Florida in 2020. Outside of classes and research, she is an avid runner and cyclist.