Publications

Sparsh Gupta, Kamalavasan Kamalakkannan, Maxim Moraru, Galen Shipman, and Patrick Diehl,
"From Legacy Fortran to Portable Kokkos: An Autonomous Agentic AI Workflow", Sep. 2025
(under review at the IEEE Transactions on Artificial Intelligence)

Sparsh Gupta, Kamalavasan Kamalakkannan, Maxim Moraru, Galen Shipman, and Patrick Diehl,
"From Legacy to Portable: An Agentic AI Workflow for Fortran Code Translation and Cross-Architecture Optimization",
Research Poster, Supercomputing '25, Nov. 2025

Sparsh Gupta, Debanjan Konar, and Vaneet Aggarwal, "A Scalable Quantum Non-local Neural Network for Image Classification",
https://arxiv.org/abs/2407.18906, July 2024 (presented at the AAAI QC+AI Workshop 2025)

Sparsh Gupta, "The Arrival of DNA Data Storage", 2021, Medium Article Link

Research Projects

Quantum Machine Learning, September 2023 - Present
Developing novel algorithms in the maChine Learning and quANtum computing research lab (CLAN). Supervised by Prof. Vaneet Aggarwal.

Brain fMRI Task-decoding, May 2023 - Present
Worked on graph signal processing and brain fMRI fingerprinting utilizing MATLAB, Python & ML. Implemented feature selection techniques to identify regions of the brain important in task-decoding and classification. Supervised by Prof. David Shuman.

DNA Methylation Age Predictor, August 2021 - January 2022
Developed an LSTM-based DNA Methylation Age Predictor with mean errors of 6 years (train) and 11 years (test), using p-value significance testing and Pearson correlation for validation and feature selection.
(with Prof. Vaneet Aggarwal at Purdue University)

DNA Classifier, May 2021 - January 2022
Developed an LSTM model for determining the population group of a person from the genome sequence with efficient .fastq genome data parsing and compression algorithms.
(with Prof. Vaneet Aggarwal at Purdue University)