I am a Project Scientist at Toronto Metropolitan University, holding a Ph.D. in Electrical and Computer Engineering from Ryerson University and an M. Tech. from the National Institute of Technology, Jalandhar, India. My research specializes in signal processing, machine learning, and deep learning, with a focus on healthcare applications. Specifically, I work on low-power and tinyML techniques that enable real-time data processing and decision-making on resource-constrained hardware and wearables.

During my Ph.D. studies, I developed computationally efficient signal processing and machine learning algorithms for real-time brain-computer interfaces, as well as low-power approaches for fetal ECG monitoring. I am particularly focused on the need for explainability in AI systems, and I currently lead a team developing AI/ML frameworks for use on edge devices in healthcare projects.

Beyond my academic and research work, I have 3 years of experience addressing the IT needs of the lumber industry, including eCommerce systems development. My diverse background in both healthcare and industrial applications allows me to deliver tailored solutions that drive innovation across multiple fields.

I am an active member of the IEEE, a TC affiliate member of the IEEE Machine Learning for Signal Processing Society, and the founder of the charity "We for Help," which I started in 2015 to support those in need.