I am a fourth year graduate student at Princeton University pursuing a Ph.D. in Neuroscience, with a particular interest in quantitative and computational approaches to neuroscience. I am also pursuing a supplemental graduate Certificate in Statistics and Machine Learning (CSML) and am a member of the Quantitative Neuroscience Training Program (QNTP).
My PhD advisors are Jonathan Pillow and Ilana Witten. Broadly speaking, I am interested in using statistical modeling and machine learning to quantify animal behaviors and their associated neural dynamics. My current work involves using latent variable models to identify the discrete structures underlying complex cognitive processes ranging from decision-making to exploration and social interaction in mice.
I earned my B.S. in Physics from George Mason University in December 2017. While there, I worked as a research assistant in the Vora Lab, studying the optoelectronic properties of a range of organic and nano-materials. During the summer of 2017, I participated in an NSF REU (Research Experience for Undergraduates) at UCLA, where I spent 10 weeks working in the W.M Keck Center for Neurophysics.
- Statistical neuroscience
- Generative models
- Machine learning
- Systems neuroscience
- Decision making
- Social behavior
- PhD in Neuroscience, Princeton University (2018-Present)
- MS in Neuroscience, Princeton University (2020)
- BS in Physics, George Mason University (2017)