As an MD/PhD student in the lab of Nicholas Tatonetti, I study transcriptional regulation in the brain to predict and understand how these mechanisms are altered by genetic mutations in neurodegenerative disease. I use computational and network biology analysis of tissue expression and sequencing data to determine these regulatory pathways. I am also interested in applying machine learning techniques to the electronic health records to determine genetic and clinical indicators of acute disease events such as stroke.

Before Columbia, I graduated from Yale University in 2011 with a BS in physics. My undergraduate thesis project studied chromatin uncoiling by measuring the force of DNA-H1 histone interactions using magnetic tweezers. I then completed a post-baccalaureate IRTA Fellowship in theoretical neuroscience in the Laboratory of Biological Modelling at the National Institutes of Health. We implemented a basic excitatory/inhibitory neuron model used previously to model binocular rivalry to recreate the perception of a motion rivalry illusion.