Polypilot product mascot

Introducing PolyPilot:

Our AI-Powered Mentorship Program

Start your trial today

Learn More
profile picture

Andrew B

- Research Program Mentor

PhD candidate at University of California San Diego (UCSD)


computational neuroscience, cognitive neuroscience, signal processing, human neuroscience, machine learning, theoretical neuroscience, cognitive science


I am a graduate student in Dr. Brad Voytek's lab at UC San Diego. I am broadly interested in the computational mechanisms and information processing underlying cognitive processes such as decision making and working memory. I pursue this interest through the use of computational modeling and machine learning techniques in tandem with analysis of electrophysiological recordings. I love to spend my time outside of the lab both playing and watching sports (primarily soccer, basketball, and recently beach volleyball), watching movies, and playing board games. I enjoy mentoring because it challenges me to grow and learn along with students and broadens my horizons beyond the specific domain of research I do on a day-to-day basis.

Project ideas

Project ideas are meant to help inspire student thinking about their own project. Students are in the driver seat of their research and are free to use any or none of the ideas shared by their mentors.

The Dynamics of Rhythmic Brain Activity in (you choose!)

Measures of human brain activity are often composed of activity from millions of neurons. Neural oscillations, which are rhythmic features of this large-scale brain activity, have been shown to change both in neuropsychiatric disease states and dynamically during cognitive functions. In this project, you will perform a literature review to understand what research has already been done to elucidate oscillatory changes in a neuropsychiatric disease or cognitive function of your choosing. Then, you will use one of the many openly available datasets to pursue research questions of your own that the literature review inspired, allowing you to learn and apply state-of-the-art techniques for the analysis of neural oscillations.

Machine Learning for Brain-Machine Interfaces

Brain-Machine Interfaces (BMIs) are an important and promising area of medical neuroscience research that have the potential to dramatically improve the quality of life for many patients. One of the most difficult technical problems for BMIs is reading out the movement intentions of an individual from their brain activity. In this project, you will use an open dataset of motor cortical activity and machine learning techniques to determine how a prosthetic arm should be moved based on a person's brain activity, allowing you to gain valuable experience in applying machine learning to neuroscientific data.

Coding skills

Python, MATLAB

Teaching experience

I have served as a Teaching Assistant for undergraduate and graduate courses in Computational Neuroscience and Neural Data Analysis. In the summer of 2021, I also worked as a Research Project Teaching Assistant for the Computational Neuroscience NeuroMatch Academy.


Work experience

Vanderbilt University Advanced Computing Center for Research and Education (2018 - 2018)
Summer Scholar
Mayo Clinic (2017 - 2017)
Summer Undergraduate Research Fellow


Vanderbilt University
BA Bachelor of Arts (2019)
University of California San Diego (UCSD)
PhD Doctor of Philosophy candidate

Interested in working with expert mentors like Andrew?

Apply now