Department: Princeton Neuroscience Institute Faculty Adviser: Fenna Krienen & Jonathan Pillow Year of Study: G3 Undergraduate School: University of California, Los Angeles (UCLA) Undergraduate Major: Computer Science
I studied computer science at the University of California, Los Angeles (UCLA) with a minor in bioinformatics. During this time, I learned how to analyze single-cell RNA sequencing data and develop bioinformatics methods for gene regulatory network inference at the Xia Yang Lab. I also interned with the Allen Institute for Brain Science, focusing on machine learning approaches to multi-omics data integration. At the Princeton Neuroscience Institute, I am working on cross-species comparisons between human and mammalian brains. I am also studying animal behavior using pose-tracking and latent state inference. In general, my research involves developing novel probabilistic and statistical machine learning algorithms for large multi-modal datasets. In my free time, I enjoy performing piano, playing the flute, and wildlife photography.
My favorite concerto is "Rach 2" Rachmaninoff's 2nd Piano Concerto in C minor, Op. 18 No. 1
My research combines computer science, neuroscience, and statistics to develop powerful new computational tools for analyzing biological data. I work with a wide variety of data, including molecular biology data from single cell RNA sequencing and behavioral data such as videos of live animals from multiple species (e.g. mice and monkeys). My projects include investigating what makes human brains unique compared to other species using multi-modal data (e.g. RNA/gene expression, DNA/chromatin accessibility, spatial transcriptomics), studying neuropsychiatric disorders using model organisms, and learning latent representations of animal behavior. The ultimate goals of my research include uncovering new information about what makes human brains unique while developing robust computational tools to analyze future datasets. I have multiple ongoing projects that include aspects of computer science, computational biology, neuroscience, computer vision, and probabilistic/statistical machine learning.
Interested in participating in Summer 2027 ReMatch+ program.
