Pranav Agrawal

My research focuses on vibroacoustics, advancing signal processing and optimization to address critical challenges in water distribution networks (WDNs) and structural dynamics. I develop innovative acoustic-based methods for leak detection and localization in complex WDNs, integrating graph theory, maximum likelihood estimation, and AI-driven approaches to enhance accuracy and sensitivity. My research also includes optimal sensor placement strategies using genetic algorithms and pioneering active transducer techniques for proactive leak detection. Beyond WDNs, I apply my knowledge to battery health estimation, developing robust CNN-LSTM models to predict State of Health and Remaining Useful Life for lithium-ion batteries, supporting sustainable energy systems. Additionally, my PhD research on cable-harnessed structures has led to novel analytical models and damping mechanisms, validated through experimental modal analysis, with applications in aerospace engineering.

​Currently, I am a postdoctoral researcher in Sriram Narasimhan's group at University of California Los Angeles (UCLA). Previously, I was a doctoral researcher at University of Waterloo (UW) in Vibration and Energy harvesting lab led by Armaghan Salehian. Also, I held a sessional instructor position at UW, developing a graduate course curriculum on Engineering Acoustics, and using a new teaching and learning methods for teaching junior-level Dynamics course. Before my PhD, I worked as a Noise Vibration and Harshness (NVH) engineer in research division of Tata Motors Limited. I obtained a Master's-Bachelor's dual degree from Indian Institute of Technology (IIT) Kanpur specializing in engineering design, vibrations and nanomechanics, and supervised by Shakti Gupta.