I am a fifth-year Ph.D. student in the Electrical and Computer Engineering department at the University of California, San Diego. I am currently working with Prof. Yatish Turakhia on developing scalable phylogenetic-based algorithms for pathogen detection from mixed-genome samples, and machine learning models that can predict the Evolution of these pathogens. My current research interests lie at the intersection of bioinformatics, computer architecture, and machine learning.
Wastewater-based epidemiology (WBE) involves analyzing sewage data to identify the genome sequences of disease-causing pathogens. A UCSD team demonstrated that WBE can even detect emerging variants up to two weeks earlier than traditional clinical genomic surveillance.
Today, WBE is being rapidly adopted worldwide to monitor a broad spectrum of pathogens, including SARS-CoV-2, RSV, Monkeypox, influenza, and Polio. However, the vast amount of WBE data presents significant computational and algorithmic challenges.
I am building novel algorithms and software tools that aim to enhance the accuracy, resolution, and timeliness of current WBE tools.