Hardware Project | Jan 2025 – Present
Building a custom AI system that classifies physical object characteristics—like material type, hollowness, and surface texture—based on reflected ultrasonic sound waves. Using an emitter and high-frequency microphone setup, collecting raw ultrasonic echo data from controlled object interactions. The signals are processed into frequency-domain features (e.g. FFT, spectrograms), which are then fed into machine learning models to predict properties of the target objects. The hardware stack includes a Raspberry Pi to control pulse emission and timing, and audio interfaces capable of high-resolution sampling for clean waveform capture. This fusion of custom acoustics and AI opens up applications in smart inspection systems, security, and embedded sensing where visual data is limited or impractical.
Software Project | Jan 2025 – Present
GradLinkR is a map-first directory to find PhD programs, labs, and PIs. We scrape via Scrapy + Playwright + Trafilatura, then normalize into a geo-indexed dataset. Users get faceted search, rich profiles, saves/collections, and outreach templates. Premium adds advanced filters, unlimited collections, CSV export, alerts, and lab-dossier PDFs. Built with Expo (React Native + Web), Supabase (Postgres + PostGIS + FTS), Stripe; shipped with Claude Code + Taskmaster.
Cook Children's Hospital | Aug 2023 – May 2025
Developed a deep learning multiclass image classification model using Confocal Laser Endomicroscopic images. Applied the Watson Score to assist in identifying gastrointestinal health from a cellular level.
UT Arlington | May 2023 – Mar 2025
Created a Python-based pipeline for statistical analysis of caregiver–patient interaction data. Resulted in models that improved patient success rates by over 80%.
UT Arlington | May 2023 – Feb 2025
Built a scraping and NLP pipeline to extract skills from job postings. Used results to support job market forecasting and enhance university curricula alignment with industry demands.
UT Arlington | Jun 2023 – Jul 2025
Developed a deep learning transfer learning model to classify pollen grain species. Built a GAN to generate synthetic training images, increasing data diversity for training.
UT Arlington | Sep 2023 – May 2025
Performed statistical and machine learning modeling on medical datasets to forecast survival probabilities. Manuscript submitted for publication.
UT Arlington | Aug 2022 – May 2023
Programmed a solution using data from Atomic Force Microscopy (AFM) scans via Gwyddion software to extract cross-sectional data and calculate growth rates with 94% accuracy.
UT Arlington | Aug 2022 – May 2023
Designed and executed Python web scraping scripts to gather geospatial mineral data (e.g., Lithium, Nickel, Magnesium, Calcium). Mapped results using QGIS to visualize global abundances and localities.