My research and teaching interests span a wide spectrum of interdisciplinary areas, including artificial intelligence, quantum computing, VLSI design, and instrumentation, with strong applications in bioelectricity, experimental and computational biophysics, and biomedical engineering. I am particularly focused on integrating signal processing and machine learning approaches to advance understanding in neuroscience, aiming to bridge theoretical models with practical applications in health, technology, and education.