I am a PhD candidate in Computational Biology at Brown University, currently studying at Princeton University with advisor Ben Raphael. My research is focused on developing algorithms for understanding tumor heterogeneity. Recent projects include developing a probabilistic method to identify structural variants from whole-genome linked-read sequencing data and using machine learning to cluster cells from high-throughput single-cell RNA-seq data.
I work with advisor Ben Raphael to develop algorithms for understanding tumor heterogeneity. Recent projects include developing a probabilistic method to identify structural variants from whole-genome linked-read sequencing data and using machine learning to cluster cells from high-throughput single-cell RNA-seq data.
I am collaborating with ecologists to assemble a high-quality genome and transcriptome for the barnacle species S. balanoides and to characterize allele frequencies and microbiome composition differences across the upper and lower extremes of the intertidal zone.
I developed software to synthesize neuron morphologies of different cell types for the Blue Brain Project. The software uses diffusive particle dynamics to “grow” a population of neurons in parallel, allowing growing neurons to interact with each other and create realistic neuronal arbors.
I worked under Dr. Robert Murphy to develop algorithms to create generative models of neuron shape as part of the CellOrganizer tool.
I teach Elementary Algebra to inmates at Garden State Youth Correctional Facility. The course is accredited through Raritan Valley Community College.
I designed a research project and supervised a high school intern as part of the Laboratory Learning Program.
I mentored junior independent work for COS397
I mentored Princeton undergraduates in website and app development as part of Princeton Summer Programming Experiences
Text-book chapter describing genome assembly approaches using pooled-sequencing data. I contributed computational bioinformatics approaches as part of the IGERT fellowship in reverse ecology.
Method for identifying structural variants, accepted to RECOMB-CCB 2017.
Princeton Citizen Scientists is a graduate organization aimed at promoting effective science communication and evidence-based policy making. I am one of four executive board members.
Co-organized a series of talks and teach-ins with Princeton Citizen Scientists, taking an intersectional look at the relation of the sciences to society in the form of advocacy, science culture, and inclusivity.
netNMF is a network regularization algorithm for dimensionality reduction and imputation of single-cell expression data.View Project
I was partnered with the Billion Oyster Project through the Bloomberg Data for Good Exchange Immersion Fellowship. I created a web application for generating plots and figures for visualization of oyster measurement data on the digital platform.View Project
NAIBR (Novel Adjacency Identifying with Barcoded Reads) is a probabilistic method for identifying novel adjacencies created by structural variants. NAIBR utilizes barcoded reads produced by 10X Genomics' whole genome sequencing pipeline to probabalistically model and rank candidate novel adjacencies.View Project
Software to simulate single cell count matrices from several canonical geometries. Created with members of the Cell Types working group at the Chan Zuckerberg Initiative (CZI) investigator meeting Collaborative Computational Tools for the Human Cell Atlas.View Project
The Octduino is an octopus plush that has 12 programmable buttons sewn to its tentacles with conductive thread. We have programmed the buttons to play the 12 notes of an octave so that the Octduino can be played like a piano. The user can also program the Octduino to be a general purpose USB controller, allowing the user use the Octduino to control all types of video games. Octduino placed 3rd at HackPrinceton as well as winning 'Best Hardware' and 'Made My Day'.View Project