I am a second year master’s student in Computer Science at the University of Southern California. MLOps, Edge-GPU Performance Characterization, Statistical Machine Learning, Deep Learning Theory, Natural Language Processing, Federated Learning, and Operating Systems are of interest to me. I have been awarded the prestigious J N Tata Endowment scholarship for the higher education of Indians.
I currently work as a Course Producer for CSCI 567: Machine Learning, offered by the Department of Computer Science at USC in Spring 2024, and for CSCI 699: Theory of Machine Learning, a doctoral-level course offered in Fall 2023, taught by Prof. Vatsal Sharan. During Summer 2023, I worked as a Machine Learning Software Intern at DeGirum Corp., Santa Clara, where I developed an ONNX OCR pipeline with pre and post-processor modules compatible with edge-hardware, and worked on a NumPy-only implementation of some vision-based PyTorch operators. During Spring and Summer 2023, I was a Research Assistant in the Department of Computer Science at USC Viterbi, advised by Prof. Vatsal Sharan, where I contributed to an open source project on tensor decomposition methods, and worked on a faster C++ implementation of a random forest based anomaly-detection algorithm.
Previously, I was Project Associate - I at DREAM:Lab, Indian Institute of Science (IISc), advised by Prof. Yogesh Simmhan, where I worked on performance characterization of Nvidia Jetson edge-accelerators on deep learning workloads, a review of systems research into training deep learning models on the edge hardware, and also on a Federated Learning project.
Prior to that, I graduated with a Bachelor of Technology in Computer Science and Engineering from Indian Institute of Technology (IIT) Dharwad. I worked on Federated Algorithms with Bayesian and Exponential Weighted Average approaches for my B.Tech. Project, as a member of LIaN research group, advised by Prof. B. N. Bharath.
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