Some research areas I like working on include Machine Learning, Quantum Computing, Algorithms,
DNA computing, Generative AI, Synthetic Biology, and Financial Tech.
Publications
Sparsh Gupta, Debanjan Konar, and Vaneet Aggarwal, "A Scalable Quantum Non-local Neural Network for Image Classification,"
(draft completed - 10 typed pages, to be submitted for publication)
Sparsh Gupta, "The Arrival of DNA Data Storage," Medium Article Link
Research Projects
Quantum Machine Learning, September 2023 - Present
Working in the maChine Learning and quANtum computing research lab (CLAN) on developing novel quantum algorithms.
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)