Welcome to my webpage! I am a fourth year PhD candidate in the Biostatistics Department at the Harvard TH Chan School of Public Health. I am currently working with Drs. Franziska Michor, in the Biostatistics and Computational Biology (BCB) Department at Dana Farber Cancer Institute (DFCI), and Kevin Haigis, in the Cancer Research Institute at Beth Israel Deaconess Medical Center. With Dr. Michor, I am developing mathematical models to characterize the response of various cancers to radiation, chemotherapy, novel targeted agents, immunotherapy, and combination therapies in order to predict optimal drug combinations, dosaging, and treatment scheduling. With Dr. Haigis, I am using organoids to study KRAS allele specific colorectal cancer evolution and response to drug treatment.
During the fall 2017 semester I rotated with Dr. Shirley Liu in the BCB Department at DFCI, during which I used RNAi and CRISPR knockdown screens to understand tumor progression and identify synthetic lethal gene pairs. During the fall 2016 semester I rotated in the Vidal Lab at the Center for Cancer Systems Biology at DFCI to identify mutations that affect interactions in protein-protein interaction networks.
As an undergraduate at UCLA, I worked under Dr. Yi Xing in the Microbiology, Immunology, and Molecular Genetics Department. The goal of my project was to identify hidden splicing variants by mapping personal transcripts to personalized genomes, and was published in Nucleic Acids Research in 2015. In this paper we demonstrate that a personal genome approach to RNA-seq alignment enables the discovery of previously unknown splicing variations. One issue in RNA-seq alignment is that commonly used alignment algorithms rely on the consensus splice site dinucleotide motif to identify splice junctions. Therefore, if a genetic variant creates a novel splice site motif the resulting splice junctions reads are likely to be unmappable to the reference genome, causing the splice junction to be missed. To address this issue we implemented a computational pipeline called RNA-seq Personal Genome-alignment Analyzer (rPGA), which maps personal transcriptomes to personal genomes to identify personal specific splicing variations. During this time, I was selected as an Amgen Scholar for the summer of 2014 to continue my work in Dr. Xing's lab.
During the summer of 2013, I conducted research under Dr. Zhong Wang in the Genome Analysis Group at the US Department of Energy Joint Genome Institute as part of the Science Undergraduate Laboratory Internship (SULI) program. My project involved developing a data driven scoring function to select the best RNA-seq alignment method based on a variety of parameters, including read length and genome complexity. During the summer of 2012, I conducted research under Dr. Stan Krajewski at the Sanford Burnham Medical Research Institute, and was involved in behavioral phenotyping of genetically engineered mice.