About Me
I am a PhD Candidate in the School of Computing at Clemson University. A member of the PERSIST Research Lab, where I build and deploy new low-power wireless protocols, on-device ML models, software and hardware technologies that enable embedded networked sensor systems to operate for decades without maintenance.
Research Interests
My research lies at the intersection of embedded networked sensor systems, intermittent computing, and embedded machine learning. It explores new low-power wireless network solutions that are resilient to frequent and erratic power failures; common in emerging batteryless systems that operate entirely on harvested energy. My research interests span the following areas:
Education
Ph.D. Computer Science
Clemson University, Clemson, SC, USA. 2023M.S. Computer Science
Clemson University, Clemson, SC, USA. 2019B.Sc. Computer Engineering
Obafemi Awolowo University, Ile-Ife, Nigeria. 2014News
(08/2021) Received the Tapia 2021 Scholarship.
(03/2020) Attended the Computing Research Association (CRA) Grad Cohort Workshop in Austin, March 2020.
(09/2019) Awarded the 2019 ACM-UPE Academic Achievement Award.
(08/2019) Presented a session on “tips for doing great research” at the National Society of Blacks in Computing (NSBC) Conference 2019, Atlanta.
(03/2019) I was selected to participate in the Computing Research Association (CRA) Grad Cohort Workshop in Hawaii, March 2019.
(08/2018) Visited Northwestern University, Evanston for the Cross-layer Computing Summer School: Circuits to System 2018 workshop.
(03/2018) Attended the Computing Research Association Grad Cohort Workshop in San Diego, California.
Recent Projects
Embedded ML with TF Lite
This project leverages TensorFlow Lite to create optimized linear and DNN models for realtime inferencing on Raspberry Pi and On-board Unit (OBU) of Connected Autonomous Vehicles.
UV Risk Detection/Prevention
This is a wearable device prototype that inform users about their UV exposure rate. One device senses UV radiation and the other displays the UV radiation levels. The display device shows the UV index.