About me

I am an Applied Scientist at Amazon AGI. I have obtained my PhD degree from the Ming Hsieh Department of Electrical and Computer Engineering (ECE) at University of Southern California in 2023. I was advised by Prof. Peter A. Beerel. My research interests include energy and latency efficient algorithm-hardware co-design for machine learning at the edge.

During my PhD tenure, I was fortunate to be a finalist of the Qualcomm Innovation fellowship 2022 (North America), a Ming Hsieh Ph.D. scholar, and a DAC 2021 PhD fellow. I was a recipient of the IEEE Graduate Fellowship on Applied Superconductivity 2022, the best Research Assistant (RA) award from USC ECE, and the Annenberg fellowship. I have published more than 25 peer-reviewed papers in top-tier venues including Nature Scientific Reports, Frontiers in Neuroscience, ECCV, TCAS-I, DATE, WACV, among others, and received a best paper award nomination at VLSI-SoC 2022. Lastly, my research on in-sensor computing have been highlighted multiple times here and here by Edge Impulse, a leading semiconductor IP company for TinyML, and USC Viterbi School of Engineering here.

Prior to joining USC, I attended IIT Kharagpur where I obtained my B.Tech. degree in Instrumentation Engineering with a minor in Electronics and Communication Engineering in 2018. I was adjudged the academically best outgoing student in my programme at IIT Kharagpur.

In my spare time, I like learning Mathematical Analysis, Modern Finance, Economics and Philosophy. I also like playing and watching soccer, and driving along the Pacific highway.