The human gut metagenome was recently discovered to encode vast collections of biosynthetic gene clusters with diverse chemical potential, almost none of which are yet functionally validated. Recent work elucidates common microbiome-derived biosynthetic gene clusters encoding peptide aldehydes that inhibit human proteases.
My webpage has moved! I am currently an assistant professor in the department of computer science and engineering at the University of Texas at Arlington. I am also a faculty member in the multi-interprofessional center for health informatics. My group focuses on 1) developing deep learning accelerated search tools for petabytes of cancer imaging data, 2) building algorithmic piplines to determine how the microbiome augments cancer immunotherapy, and 3) building analysis tools for high dimensional `omics data that provide utility at the bench and in the clinic.
I am currently recruiting postdoctoral research fellows, software engineers, staff scientists, PhD students, masters students, and undergraduate students. If you are an interested in doing a PhD with me, please apply through the UTA CSE department, specify interest in the bioinformatics track, and mention my name in your application. If you are interested in joining my lab as a postdoc, software engineer, or staff scientist please email me directly. I currently only recruit undergrad and masters students who are already in the CSE department at UTA.
I defended my PhD in August of 2020 and and was a postdoctoral researcher at the NCI Cancer Data Science Laboratory at The National Institutes of Health working with Peng Jiang and Eytan Ruppin from 2020 through 2021.
I was formerly a NSF Graduate Research Fellow and PhD Candidate in the Bioinformatics and Integrative Genomics (BIG) Program at Harvard Medical School in The Division of Medical Sciences under the aegis of The Graduate School of Arts and Sciences. My research interests are biomedical informatics, spatial 'omics, computer vision, functional genomics, machine learning, and personalized genomic medicine. My Erdős number is 4. My research was previously funded by a NSF GRFP Fellowship (September 2018-August 2021) and was previously funded by a NIH T32 grant (August 2016-August 2018) and Amazon (March 2017-March 2018).
In 2016 I graduated cum laude with special departmental honors in computer science from Trinity University. My undergraduate thesis research was conducted under Matt Hibbs on osteoblast development and bone maintenance in Mus musculus where I focused on methods to consider tissue context specificity properly when using machine learning to make gene-gene functional relationship predictions. Additionally, from 2015 to 2016 I worked in Carol Bult’s group on the Patient Derived Xenograft (PDX) project at The Jackson Laboratory where I built a data-mining pipeline that aims to better subtype Triple Negative Breast Cancer tumors and computationally predict chemotherapy drug response in them.
Featured examples of my past work are available on this site; full details about my previous scholarship can be found in my CV.