As an aspiring computer scientist and computational biologist, my work is primarily focused on these two disciplines.
In computer science, my primary areas of interest are algorithms, machine learning, sketching cryptography and computer security. In addition to my work in theoretical computer science, I have significant programming experience in Python, Java and R, and have worked with C, Go and Matlab before.
As a computational biologist, I am interested in the intersections of biology and computer science. My areas of interest are in algorithms (especially those pertaining to the problems we encounter computational biology), computational genomics, genomic privacy, big data analysis, cryptography and computer security.
I'm currently working with Dr. Mike Schatz at Johns Hopkins, as I pursue a PhD in Computer Science with a focus on Computational Genomics. My first project was "Sapling: Accelerating Suffix Array Queries with Learned Data Models", which focused on learned index structures/data models for genomics. It was published in Bioinformatics, and can be found here.
My latest work is "Sketching and sampling approaches for fast and accurate long read classification", which focuses on sketching and sampling approaches to speed up read classification compared to existing high-overhead index and alignment based methods. This work has been published in BMC Bioinformatics, and can be found here.
My current work focuses on investigating and improving the representation of South Asian genomes in existing genomic datasets, as well as evaluating the improvements offered by new linear and pangenome references. This work has been presented at Biology of Genomes 2023, and will be presented at ASHG 2023. Stay tuned for more exciting updates in the new future!
My Google Scholar page can be found here.