Clay Crews

MS in Computer Engineering @ UofSC | Graduating August, 2025

My interests / involvements include research in ML architecture, the development of digital twins (DTs), and real-time hardware deployment. I am currently working on my MS thesis on creating specialized solvers for accelerating the simulation of power electronic converters using physics-informed neural networks and real-time deployment on FPGA hardware. This research is in line with my work on Digital Twins for Naval Power and Energy Systems (NPES).

I am seeking a position that is in need of research/development regarding Digital Twin systems and/or implementation of machine learning on real-time systems.

Projects Skills Contact Me
john doe headshot
More About Me

Projects

Simulation of DC-DC Power Converter using Physics-Informed Neural Networks image

Simulation of DC-DC Power Converter using Physics-Informed Neural Networks

Machine Learning PyTorch NumPy ODEs MLP Physics-Informed ML SPICE FPGA MATLAB

The real-time simulation of power converters is necessary for the health monitoring and preventative maintenance to avoid critical failures. Developed a digital twin of a buck converter for simulation and health monitoring to be deployed on FPGA with a 1ns time-step.
Distributed Wireless Sensor Network for Risk Assessment of Levee Breach image

Distributed Wireless Sensor Network for Risk Assessment of Levee Breach

Arduino RaspberryPi Electrical Design PCB Design KiCad nRF24 Module Python C

Developed wireless sensor packages with conductivity probes for distributed real-time soil saturation assessment in levees.
ML Brain Tumor Segmentation image

ML Brain Tumor Segmentation

Machine Learning Image Segmentation PyTorch NumPy Mamba CNN Transformers U-Net

Developed an ML model for image segmentation of brain tumors in MRI images using a Mamba model, a competitor to Transformers boasting a faster throughput. Additional approaches using transformers and CNNs were also implemented.

Skills