
From Raw Data to Cloud Insights
Built a cloud data pipeline with members, from S3 through Lambda, EventBridge and Redshift to Looker Studio, then taught how to design dashboards people can read at a glance.
Each star in orbit is a project. Pick a skill to light up the projects built with it.
I work across data analytics, AI engineering and cloud development. Across two internships I have built automated dashboards, Python data pipelines, backend services and cloud-deployed models, and I validate them on held-out data and with real users.
I'm studying BS Information Technology at the Polytechnic University of the Philippines (expected June 2028, GPA 1.42) and lead the Data Science and Analytics Department of the AWS Student Builder Group PUP Manila.
Projects
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A star, galaxy, and quasar classifier built on five brightness measurements that stays accurate on noisy or incomplete data and says “not sure” when it can’t be trusted.

A daily-updated, open-data pipeline that turns ~2,900 Department of Agriculture price-report PDFs into a clean table of ~890,000 Metro Manila palengke prices, published as a BigQuery dataset and Looker Studio dashboard.

A matched-control follow-up to Data 001 that tests whether Gaussian Copula augmentation beats simply duplicating scarce real rows. It never did, and it was practically harmful in 10 of 18 settings.

A benchmark testing whether Gaussian Copula synthetic data can make up for scarce real healthcare training data. It couldn’t: augmentation helped 0 of 18 conditions and hurt 14.

Built an automated, cloud-native weather data pipeline on AWS (EC2, Lambda, EventBridge) that loads curated data into Redshift for a Looker Studio dashboard, and taught the build to 40+ members in a hands-on workshop.
An automated Looker Studio dashboard that brought four years of event data (80+ events, 1,000+ attendees) into one view.

An air pollution exposure simulator that won 1st place out of 25 teams at the Solar Power Hackathon.
Open one to check the credential.
Blog
Events I've hosted, attended and volunteered at, newest first.

Built a cloud data pipeline with members, from S3 through Lambda, EventBridge and Redshift to Looker Studio, then taught how to design dashboards people can read at a glance.

Learned how data science is done in practice from data scientists at EY GDS, the Asian Development Bank and Smart Communications at the launch of the PyTorch Philippines community.
AWS Office, BGC, Taguig

Taught students to handle data with pandas, Python's go-to library for tables, from importing CSV files to merging datasets.

Taught students their first steps in Python, from doing arithmetic to joining text together (string concatenation).

Attended SONAI 2026, the Global AI Council Philippines' yearly summit on where AI stands in the country, and heard lawmakers lay out plans for AI policy.
GSIS Building, Pasay City

The AWS Student Builder Group PUP's yearly community night, where members gathered to hear from established speakers in the tech community.

Helped elementary students understand how AI works, using simple ideas like how a computer tells cats from dogs by their features.

Introduced 45 members of our Data Science and Analytics Department to what data science and analytics are, starting with the Vs that describe data.
PUP Manila

Started my term as Co-Lead of the Data Science and Analytics Department, met my fellow leads, and learned the 5 buckets of knowledge we use to plan our teaching.

Led the backend team for AeroC, an air pollution exposure simulator that placed 1st out of 25 teams.