About Me
“Bridging data, health, and equity through science and innovation.”
I’m Isabelle Gatmaitan, a Filipino-American undergraduate at the University of Florida majoring in Data Science with a minor in Computer Science. I build and apply computational tools — including machine learning, signal processing, computer vision, and geospatial analytics — to questions in public health, medicine, and accessibility.
My long-term goal is to integrate clinical impact with computational research: developing methods that help clinicians interpret complex data, improve diagnosis and treatment pathways, and make healthcare more personalized and equitable. I’m especially motivated by accessibility and disability-inclusive design, and I enjoy working at the intersection of rigorous quantitative modeling and human-centered problem solving.
Current Research
- Mapping Mobility Barriers on Campus (USP) — Using sensor-equipped wheelchair data (GPS, accelerometer, gyroscope) to identify “high-friction” zones and build dynamic accessibility maps. Work includes data cleaning/alignment, feature engineering, hotspot analysis, and visualization for infrastructure planning.
- Unpacking Hoarding Speech (UF Linguistics) — Applying NLP methods and linguistic annotation to characterize language patterns in hoarding disorder, with the aim of supporting clinical insights and interventions.
- PFAS Exposure & Educational Outcomes — Analyzing relationships between environmental exposures and FCAT performance with demographic covariates; building regression and exploratory models.
- Mobile ECG Study — Prior work organizing data, basic statistical analysis, and device evaluation in a clinical setting.
Academic Foundation
My coursework blends mathematics, statistics, and computing with health applications. Highlights include:
- Programming 1 & 2 (C++/Java fundamentals), Data Structures & Algorithms
- Probability, Statistical Theory, Regression Analysis
- Computational Linear Algebra, Numerical Analysis, Differential Equations
- Computer Vision, Foundations of Digital Signal Processing
- Programming with Data in R; Advanced Computational Techniques
Values & Approach
I care about reliability, reproducibility, and real-world impact. I like building systems that are transparent and actionable for practitioners, and I’m committed to ethical, privacy-respecting AI practices in healthcare and public sector contexts.
What’s Next
I’m continuing my USP research on dynamic accessibility mapping and advancing the NLP study on hoarding disorder. I’m also exploring graduate pathways at the intersection of AI/ML, epidemiology, and accessibility, with a focus on translational impact.