Data + QA-focused developer
Undergraduate at Georgia Gwinnett College. Working with Python, data workflows, and system validation. Especially interested in how this applies to healthcare and neurotechnology.
Undergraduate at Georgia Gwinnett College. Working with Python, data workflows, and system validation. Especially interested in how this applies to healthcare and neurotechnology.
I work with Python (pandas, NumPy), MATLAB, and EEG/biosignal processing tools. Experience with data cleaning, signal analysis, and building processing pipelines.
QA testing lead and documentation lead on multiple projects. Did QA testing during my internship at ThinkSuite and on projects like Lyra. I write tests, review code, and document processes.
My work on biosignal systems (EEG, cognitive load monitoring) and teaching experience in anatomy & physiology labs has made me comfortable with clinical terminology and research workflows.
Long-term, I'm planning to pursue a PhD in biomedical engineering, so I'm intentionally looking for work that connects data, systems, and clinical applications.
Built a Python tool for EEG analysis/visualization. A lot of the work was cleaning noisy sensor data, checking signal quality, and making outputs consistent enough to analyze.
View on GitHubWorked through messy transactional data (missing values, inconsistent formats, outliers) and documented the cleaning steps so the analysis was reproducible.
View on GitHubBuilt data pipelines for wearable force sensors and added checks for completeness/consistency across synced streams. Also documented data formats and system flow.
View on GitHubContributed to BrainFlow (EEG/EMG/ECG data tooling), mainly around docs and biosignal workflow support.
View on GitHubLive coding environment for D2L with automated grading via Gradescope. QA testing lead and documentation lead. Wrote 20+ unit tests using Jest/Supertest. Private client project for Georgia Gwinnett College.
Fitness analytics platform with privacy-by-design architecture. Built Flask API for predictions, TensorFlow model with differential privacy optimizer, and Streamlit dashboard. Tested with synthetic data and validated privacy budget calculations.
View on GitHubOutside of building, I'm pretty involved in neurotech spaces. I'm part of NeurotechX, where I help manage student clubs and work on initiatives across the community, and NeuroNYC, where I'm involved in neuroethics and fundraising.
I like being around people who are actually working on things in this space and thinking through how this all translates into real-world systems. A lot of that has come from being in these communities, hackathons, and just putting myself in environments where these conversations are happening.
