Estrous Phase Classification

Feb. 2025 -- Present

Taking the dataset I published in the mEPSC Dataset Project, I utilized various Python packages to import the data into google colab, make it useable, and filter it. After that I extracted experimental features to compare against the features of the mEPSC events generated by MiniAnalysis. Comparing the model accuracies of various machine learning algorithms, we determined the best features to classify Estrous cycle phase with. This more broadly represents an exploration of how best to computationally represent small scale neuromodulatory differences in cells within the brain. Next steps are in the works...

The picture to the left is from the poster I presented at the Symposium for Young Neuroscientists and Professors of the South East (SYNAPSE) at the University of North Carolina at Chapel Hill in March of this year. I was also selected to give a short talk about the project which you can listen to here if you are interested.

Interfaith Food Shuttle Farm

Aug. 2024 -- Dec. 2024

My time with the Interfaith Food Shuttle Farm taught me so much about the difficulties of growing fresh produce at scale. It gave me a new appreciation for the work that goes into growing food without pesticides, herbicides, or a large team of people. Spending hours fannning through cabbage leaves looking for worms, mulching the shallow roots of blueberry trees, and spreading wheel barrows of leaf mulch on fields (and in my shoes) has changed the way I see a fully stocked grocery store forever. Interfaith has pantries and farms across central North Carolina, I'd highly encourage anyone local to spend a day with them. Check out their website here.

Pictured on the right is the awesome service-learning team I volunteered with at Interfaith, as part of the Caldwell Fellows Program.

Schizophrenia EEG Classification

June 2024 -- Aug. 2024

This project was my introduction into the interaction of ML and neuroscience. Inspired by Talha Anwar's series on applying machine learning to EEG data, I learned how to make EEG into tabular, usable data and process signals in python. Beyond the videos, explored the use of power spectral density as a powerful feature in the classification task. This project helped me refine my data science skills and opened my mind to the possibilities of using Python for neuroscience. Check out my Github for the code!

On the left is a picture of me with my first ever EEG headset, gifted to me by a mentor. Tinkering with it taught me a great deal about the challenges of working with EEG data, the importance of signal processing, and the crazy amount of setup needed for a quality recording.

mEPSC Dataset Publication

Jan. 2024 -- Mar. 2024

As part of my first project in the Meitzen lab I used a simple Python script to automate the merging of many excel spreadsheets into a dataset with data from two papers which I manually cleaned. I gained a lot of knowledge about how to read academic papers and understand what is important amongst a lot of jargon during this time. Knowing what I do now, I am thoroughly dissapointed in the lack of laziness I incorporated into my strategy for this project. If you are interested in accessing the dataset you can do so by following this link.

On the right is a picture of me working on the computer in the patch-clamp rig room in the lab. It's pretty crazy to think that we can poke singular neurons and figure out what they are up to.

Human-Robot Autonomy Teaming

Aug. 2023 -- Nov. 2023

My first ever research experience was with the LACELab in the department of human factors psychology. I used JSON files and a git package called omrchecker to build outlines to accurately record data from paper surveys, manually QAd paper forms, and helped with literature review on topics including human-robot anthropomorphism, optimal learning conditions, and the effects of different distractions on specific tasks.

To the left is a picture of me at the State of North Carolina Undergraduate Research and Creativity Symposium (SNCURCS) 2023 meeting. It was my first time preparing and presenting research and taught me lots about the pace at which research moves and the importance of patience.