I am an accomplished academician and researcher with interdisciplinary expertise spanning Electronics, VLSI Design, Artificial Intelligence, and Machine Learning. Currently serving as an Assistant Professor in Computer Science & Artificial Intelligence, I actively teach Machine Learning and Theory of Computation while supervising three Ph.D. scholars and one Postdoctoral researcher, fostering high-impact research and innovation. My research integrates low-power VLSI design, neuromorphic computing, and intelligent systems, with contributions in hybrid memristor/CNTFET based architectures, m-GDI design techniques, and energy-efficient circuit development. I also specialize in spiking neural networks, LIF neuron models, and AI-driven healthcare applications, including non-invasive biomedical signal analysis and deep learning-based image classification. Driven by academic excellence and translational research, I aim to bridge hardware intelligence with advanced AI methodologies, contributing to cutting edge innovation, funded research, and global academic collaboration while mentoring future ready engineers and researchers.