My research has focused on building computational tools to quantify animal behavior with the goal of better understanding the brain.
PhD in Neuroscience, 2021 (Expected)
MS in Neuroscience, 2017
BS in Bioinformatics and Computational Biology, 2015
University of Maryland, Baltimore County
Using fruit flies (Drosophila melanogaster) to study how the brain integrates sensory information to pattern behavioral sequences. Developed hardware and software for acquisition and processing of high resolution video, audio and realtime instrument control. Developed computational methods that leverage computer vision, deep learning, signal processing and unsupervised machine learning for quantifying behavior through few shot pose estimation and manifold embedding. Working on mapping the substrates and function of biological neural circuits involved in patterning the structure of complex motor behaviors.
Advisors: Mala Murthy, Joshua Shaevitz
Worked on computational analysis of aggressive behaviors in fruit flies using methods in computer vision for animal tracking and supervised machine learning for timeseries segmentation.
Advisor: David J. Anderson
Worked on image processing algorithms for large scale (100-1000s GiB) electron microscopy image alignment/registration for connectomic reconstruction.
Advisor: Sebastian Seung
Developed computational algorithm for GPU-accelerated transcription factor DNA binding site prediction in large scale (10-100s GiB) metagenomic sequencing data. to characterize transcriptional regulatory networks.
Advisor: Ivan Erill
Worked on characterizing interactions between proteins associated with psychiatric disease in the axon initial segment via immunochemical assays.
Advisor: Jon Madison
Characterized the learning and memory impairment induced by knockout of a type-1 diabetes-associated neuroendocrine transport gene in mice.
Advisor: Abner L. Notkins