Patricia Nava

Patricia Nava is a Professor in the Department of Electrical and Computer Engineering at the University of Texas at El Paso (UTEP), with affiliations in Computational Science. Her work bridges theoretical and applied domains across Artificial Intelligence, Deep Learning, Digital Design, and Computer Architecture.

• Primary Research Areas: AI, Deep Learning, Computer Architecture, STEM Education
• Key Collaborations: UTEP Distributed Computing Lab, H-PIPE (High-Performance Computing Pipeline) project

Her research explores Deep Learning Networks through analogies to biological systems, focusing on their implementation via programmable hardware. She has pioneered educational strategies in engineering pedagogy, particularly for Signals and Systems instruction, while maintaining a strong technical focus on neural network algorithms and hardware acceleration.

Recent publications highlight her dual emphasis on STEM student success (e.g., graduate transition pathways) and technical innovations such as GPU clusters, quantized neural networks, and multi-core architectures. Her work spans biomedical applications like asthma classification and respiratory impedance modeling, demonstrating interdisciplinary breadth.

• Featured Scientific Support: $1M grant to increase graduate engineering participation

She contributes to distributed computing infrastructure through projects like the Virgo 3-GPU upgrade and has developed fuzzy logic systems for sleep-stage and asthma classification. Her educational initiatives focus on transfer student integration and diversity in engineering.