I am a computer scientist with a background in bioinformatics and computational biology. Holding a Ph.D. in Computer Science from the University of Maryland, I specialize in developing efficient data structures and algorithms for analyzing complex biological datasets.
My experience encompasses a wide range of projects, from designing and implementing efficient classification methods for nanopore reads to contributing to the development of tools like Alevin-fry and Puffaligner for pre-processing single and bulk RNA-seq short reads. My passion lies in creating solutions that bridge the gap between computational challenges and biological insights.
I am excited about the intersection of computer science and biology, and I look forward to contributing to advancements in the field.
Find my CV here.
that I have contributed to
A suite of tools for the rapid, accurate and memory-frugal processing single-cell and single-nucleus sequencing data.
I contributed to the development of the pseudo-alignment with structural constraints algorithm for mapping short reads to the transcriptome.
[November 2023] We posted a pre-print about implementing move data stucture for cache-efficient string matching. Find it on BioRxv
[Fall 2023] I instructed a HEART course for incoming undergraduate students. The course was about an introduction to common exact and approximate string matching algorithms that are widely used for searching sequencing data. Find my slides for the course here.