Data Scientist · BS Data Science, Cum Laude
I build data-driven systems that go from raw signal to decision — UAV gas-detection ML pipelines, spatial demand models for public transport, NLP analysis, and generative AI tools. Based in Cagayan de Oro, Philippines.
I'm a Data Science graduate (Cum Laude) from the University of Science and Technology of Southern Philippines, with a scholarship under the Cagayan de Oro City Scholarship Program (Iskolar sa Dakbayan). I like working close to messy, real-world data — sensor readings, transit patterns, text — and turning it into models people can actually use.
My recent work spans a UAV-integrated gas detection platform (AEROVANT), a kernel density estimation framework for jeepney demand mapping in Cagayan de Oro, and an applied NLP and generative AI toolset for resume screening. AEROVANT was one of six teams nationwide selected for the Green Rising Fund grant, delivered in partnership with UNICEF Philippines and the Positive Development Youth Network.
Outside of modeling, I do freelance web development (WordPress, Elementor) and enjoy data visualization and storytelling — infographics on health, transport, and community topics.
The hardware behind the modeling, rendering, and multitasking.
A mix of academic research, individual coursework, and applied builds — spanning sensor ML, geospatial statistics, NLP, and generative AI.
UAV-integrated multi-sensor platform for hazardous gas detection, threat-level classification, and environmental monitoring using a two-stage ML pipeline. Green Rising Fund grantee (UNICEF Philippines × PYDN).
View project ↗ 02 · ResearchA Kernel Density Estimation framework mapping passenger demand and service imbalance for jeepneys in Cagayan de Oro City, with a GIS-based heatmap and route-optimization metric.
View project ↗ 03 · CourseworkAn end-to-end individual machine learning project covering data preparation, model building, and evaluation, submitted as the main course notebook.
View project ↗ 04 · CourseworkTwo NLP notebooks: POS tagging and NER on a literary passage, plus a focused frequency analysis of a scene from The Lord of the Rings.
View project ↗ 05 · CourseworkFinal exam notebook covering ARIMA vs. SARIMA, forecast error metrics, and applied stochastic time series methods.
View project ↗ 06 · Applied BuildA Flask app that ranks resumes against a job description using TF-IDF cosine similarity and summarizes each candidate with Gemini via LangChain.
View project ↗Open to data science, machine learning, and analytics opportunities — new grad roles, internships, or collaborations. Reach out through any of the channels below.