I am an assistant professor in the Computer Science and Engineering Department at the University of Connecticut. I graduated from the University of Rhode Island with B.S. degrees in Computer Engineering and Computer Science, received my Ph.D. in Computer Science from Brown University, advised by Professor Sorin Istrail, and completed my postdoctoral work at Princeton University with Professor Barbara Engelhardt. My research aims to develop probabilistic machine learning models, combinatorial algorithms, and scalable inference methods to better understand high-dimensional data, particularly genomics and genetics data applied to complex disease.
I am currently looking for motivated PhD students interested in research at the intersection of probabilistic machine learning and combinatorial algorithms and applying this work to application areas including genomics, transcriptomics, population genetics, sociology, and law.
HapCompass haplotype assembler
HapCompass is a state-of-the-art haplotype assembler presented at ISMB 2013 and published in Bioinformatics and the Journal of Computational Biology. It is extremely accurate and efficient and the first haplotype assembly algorithm capable of polyploid haplotype assembly. more on HapCompass
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Most human protein-coding genes can be transcribed into multiple distinct mRNA isoforms. Isoforms are difficult to characterize from short-read RNA-seq data because they share identical subsequences and occur in different frequencies across tissues and samples. BIISQ is a Bayesian nonparametric model for isoform discovery and individual specific quantification from short-read RNA-seq data.