Selected Work
Cofounded and lead a student organization bringing together engineers, neuroscientists, and designers to explore brain-computer interfaces.
Explored deep learning techniques to classify epileptic states from the Bonn dataset, achieving 95.26% accuracy in seizure detection using a simple ANN.
Built machine learning models to classify schizophrenia from EEG data using power spectral density features.
Academic Journey
A collection of the most interesting courses I've taken thus far in my undergraduate degree.
This class covered biophysics, considerations about stimulation/ recording electrode design, and a deep dive into existing applications (pacemakers, retinal implants, DBS, etc.) .
Main takeaway: material scientists are unbelievably underappreciated.
This class primarily covered estimators and how to evaluate their quality combined an in depth revist of fundamental statistical tools such as confidence intervals and hypothesis testing.
Main Takeaway: A new perspective on inference and how to think about the quality of guesses.
This class covered the ionic basis of the action potential, synaptic plasticity, various motor pathways/ neural networks, and the neural basis for several disorders.
Main takeaway: Plasticity is an extremely powerful concept.
This class covered a wide array of topics with a focus on servant leadership and developing a personal definition of leadership.
Main takeaway: The importance of understanding who you are serving and why you are serving them before actually taking action.
Spring 2026
Spring 2026
Fall 2026