Key Achievements
- Published Estrous phase dataset on Dryad digital repository (link below)
- Presented findings on early stages of project at SYNAPSE alongside lightning talk
- Leveraged model interpretability to uncover more about the impact of hormones at the single cell level
Meitzen Lab - NC State
Jan. 2024 - Present
Using single-cell neuron recordings to classify animals across phases of the estrous cycle, a study of both ML model and single cell interpretability.
Key Achievements
- Conducted extensive research into optimal use of high-powered computing resources for reinforcement learning training
- Wrote several RL environments, comparing efficiency of computationally intensive tasks
- Researched optimal reward function configurations for several RL policies
Neuro Rehabilitation Engineering Lab (NREL)
Aug. 2025 - Present
Working on reinforcement learning decoding applications for EMG-based upper-limb prosthetics.
Key Achievements
- Designed functional concepts of modification at 50 micron scale
- Researched manufacturing capabilities for small scale modifications
- Studied medical device/ regulatory development lifecycle
CINT Fellowship - WashU
May 2025 - Aug. 2025
Prototyped modifications to stereotactic depth electrodes for enhanced diagnostic fidelity in epilepsy patients.
Key Achievements
- Developed data processing pipelines for HRI experiments
- Conducted literature reviews optimal learning conditions
- Presented findings on autonomy and trust in robotics
- Conducted manual QAing of surveys from various experiments
LACELab - NC State
Aug. 2023 - Dec. 2023
First research experience in undergrad, assisting in projects dealing with optimal learning conditions and trust in human-robot interaction.
Experience Descriptions
Machine Learning and Neural Classification
NC State University
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. A variety of biological signal types (spiking, mEPSC, and passive membrane potential) each of
which capture different aspects of neuronal function were explored. I then tested the model accuracies of various machine learning algorithms
across features extracted from the different signal types, indicating which signal type encodes the state of estrous cycle phase best. This more broadly
represents an exploration of how best to computationally represent small scale neuromodulatory differences in cells within the brain. More on this coming soon...
On the right is a picture of my poster presentation at SYNAPSE 2025, alongside this,
I was selected to give a lightning talk which you can listen to using the link below.
mEPSC Dataset Publication
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.
Me in the rig room scouring the old laptops for abf files.
Reinforcement Learning for Prosthetic Control
NC State University/ University of North Carolina at Chapel Hill
I work on optimizing the algorithms behind upper-limb prosthetics under Dr. Helen Huang. Thus far my work has involved
developing custom RL environments using Gymnasium to assess efficiency of multithreading/ vectorizing computationally intensive tasks. Beyond this,
I have also done extensive reserach into use of my university's high-performance computing cluster for training RL agents, ultimately reducing
the training times of the upper-limb agents by up to 70% compared to before. I've also helped with data collection and cleaning for a 3 degree of freedom
prosthetic control study, working with motion capture and wireless EMG sensors.
Other tasks I've helped with include configuring the eye tracking glasses pictured to the right, volunteering at the lab's outreach events, and
helping with tricky threading issues.
Innovation in Neurotech Fellowship
Washington University in St. Louis Medical School
During my time with the Center for Innovation in Neuroscience and Technology (CINT) another undergraduate student and I drafted and prototyped substantial modifications to stereotactic depth electrodes to enhance their functionality while retaining their core purpose under Dr. Eric Leuthardt.
I learned so much about FDA regulations and pathways for medical devices, the differences in how neurosurgeons and engineers communicate, and the importance of observing before you build. I had the exciting opportunity to watch neurosurgery, work with very fancy 3D printers, and speak with experts from so many different domains. The project involved designing functional concepts at the 50 micron scale and researching manufacturing capabilities for implementing these small-scale modifications in a clinically viable way.
Human-Factors and Human-Robot Interaction
NC State University
I worked under Dr. Anne McLaughlin, assisting in multiple projects involving human-robot interaction, optimal learning conditions, and focus in stressful environments. I did a lot of work in setting up the infrastructure for code sharing via Github, wrote code
for Unity environments, and used Python/ JSON files to configure an automated survey system.
I also had the opportunity to present findings on autonomy and trust in robotics at the SNCURCS 2023, pictured to the right. This was a great experience that taught me a lot about how to prepare and present research findings.
