About me

Hi! I am a Pittsburgh based Ph.D. student, jointly in the Machine Learning Department and the Statistics and Datascience Department at Carnegie Mellon University (CMU). I am a member of the NeuroStats Research Group, and I am supervised by Prof. Robert Kass. I conduct research in Computational Neuroscience, with the broad aim of understanding the pathways by which different brain regions communicate with each other. In addition to furthering scientific knowledge about the functioning of the brain, this research has applications in Brain-Computer Interfaces (BCI), for example, in decoding neural signals in neural prosthetics. I am also interested more broadly in building ML/AI tools that can learn in small data regimes, and from data with low signal-to-noise ratio.

In the summer of 2024, I interned at Meta reality labs, where I developed AI for neuro-motor interface technology. In 2023, I worked as a Machine Learning Engineer for Performance Photo, where I developed computer vision models to support efficient indexing and querying of large-scale image databases. I interned as an Applied Research Science at AT&T Labs in the summer of 2022, where I worked on forcasting mobile cell tower traffic from historical data relevant predictors. Prior to stating graduate school at CMU, I obtained a Bachelors degree in Applied Mathematics, and a Masters degree in Computational Neuroscience. I also worked as a Software Engineer at Intel Corporation, building tools to automate the statistical analysis of large-scale production datasets.

Outside of academic and professional pursuits, I am an avid explorer of the outdoors. I enjoy hiking, backpacking, rock climbing and snowboarding. I have also (more recently) taken to long distance running. My goal is to run at least one ultra marathon in my lifetime.