Professional

Work &
Education

My professional journey in AI/ML, spanning industry internships, freelance development, and academic milestones.

Experience

IT - Data and Artificial Intelligence Intern

September 2025 — March 2026

Built a geospatial data mining pipeline using Computer Vision and Google Earth Engine to extract infrastructure data from satellite maps; utilized Levenshtein distance to ensure high-accuracy data loading into BigQuery.
Developed a high-precision OCR platform powered by Tesseract.js and Docling to automate and validate data extraction from power billing statements. Implemented a bounding box annotation system to target specific document regions, integrating PyMuPDF for seamless document processing and LLM-ready data preparation.
Conducted R&D on multi-agent workflows using LangGraph, Flowise, and Pydantic AI to develop an in-house Agentic Data Analyst platform. This tool automates data extraction from Excel, CSV, and BigQuery to generate visualizations and key insights. Successfully deployed the system on GCP using Docker and Google Artifact Registry, integrating Okta authentication to ensure secure, employee-only access.

Beyond the technical tools, this experience taught me the true value of soft skills. I learned the importance of proper communication with the team and with the stakeholders and how to approach complex problems.

Freelance AI/ML Python Developer

October 2024 — August 2025

Developed YOLOv8 real-time fabric defect detection system achieving 94% accuracy with 45ms inference time using Ultralytics and ONNX optimization, deployed via Streamlit admin interface with Roboflow integration, reducing manual inspection time by 60%
Evaluated and implemented transfer learning on TensorFlow Model Garden CNNs for custom fabric dataset using TensorFlow/Keras, improving classification performance by 23% over baseline models
Built end-to-end IoT fire detection system with Supabase backend, Streamlit interface, and scikit-learn Random Forest classifier achieving 89% detection accuracy for real-time emergency response

Junior Machine Learning Engineer (Project Based)

August 2023 — November 2024

Personal Injury Claims Valuation (US): Conducted comprehensive EDA with boxplot/whisker visualizations for outlier detection and statistical analysis, contributing to ensemble ML-based legal compensation prediction model (Random Forest, XGBoost, Linear Regression) achieving 82% accuracy with RMSE optimization
Tuberculosis Analysis Platform (Nigeria): Led data preparation team, automated Excel-to-unified format processing using Pandas reducing data cleaning time by 80%, developed interactive PyGWalker/Plotly dashboard with time-series analysis deployed via Streamlit Cloud
Mango Leaf Disease Detection (Bangladesh): Spearheaded EDA and built custom CNN dataset loading pipeline using TensorFlow/Keras ImageDataGenerator for agricultural computer vision model, implementing data augmentation (rotation, flip, zoom) and transfer learning (ResNet50, MobileNetV2) enabling real-time disease classification with 91% accuracy
Climate Data Analytics (São Paulo, Brazil): Engineered weather data retrieval system for 645 regions spanning 23 years (2000-2023) using OpenStreet/Weather APIs with custom data manipulation functions (Pandas, NumPy), implementing time-series forecasting (ARIMA, Prophet) processing 15,000+ data points daily

Education

Polytechnic University of the Philippines

2023 — present

Bachelor's degree, with focus on Computer Science Research

Design and Analysis of AlgorithmsNatural Language ProcessingComputational IntelligenceArtificial Intelligence

Special Awards

Awardee of Gawad Pagkilala sa Natatanging Iskolar ng Bayan (2024)

Chose PUP for its tech community — see Impact for what that looks like in practice.

Honorato C. Perez Sr. Memorial Science High School

2017 — 2023

Class Valedictorian — Talagháy Batch Graduates

Rank 1, Overall

Rank 1, STEM