Zack Woodel

Zack Woodel is an Electrical Engineering student and undergraduate researcher at Texas Tech University. His academic and research interests lie at the intersection of quantitative finance, electrical engineering, national defense, and biophysics. Within the Soft Condensed Matter & Biophysics group, Zack assists in investigating lipid membranes as memory-bearing systems, utilizing X-ray/neutron scattering and electrophysiology to study their potential for neuromorphic like materials.

In the field of national defense and power systems, Zack contributes to DOD-funded research developing high-reliability power electronics and nanostructured sensing devices designed for extreme environments. His engineering background includes the development of AI algorithms for the semiconductor industry and quantitative finance, such as a Heston-Merton pricing engine optimized through FPGA hardware to handle market complexity with high-speed performance.

Zack also explores industrial efficiency, having implemented data-driven controls that utilize machine learning to optimize power consumption in real time. By identifying maximum efficiency zones rather than relying on fixed setpoints, his work has demonstrated a 38% reduction in power loss for industrial units. Currently pursuing his degree, Zack remains focused on how advanced semiconductors and data analytics can enhance system reliability across both biological and mechanical infrastructure.