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I am a full-stack developer building AI-integrated systems using machine learning models such as regression, classification, CNNs, and forecasting.
I focus on clean architecture, purposeful intelligence, and scalable applications.
I am a Full-Stack Developer with a strong foundation in UI/UX design, frontend development, and web technologies, currently expanding my work into AI-integrated systems through machine learning. My background allows me to approach problems from both a design and engineering perspective, ensuring that solutions are not only functional, but also intuitive and well-structured.
I hold a Bachelor of Science in Information Technology, graduating Cum Laude, and I am currently pursuing a Master of Science in Data Science. I actively build and integrate machine learning models—including regression, classification, convolutional neural networks (CNNs), and time-series forecasting—to enhance applications with intelligent, data-driven capabilities.
My professional experience spans web development, IT support, and digital design, complemented by leadership roles in academic and professional organizations. I have participated in and placed in innovation challenges and national IT competitions, reflecting my commitment to problem-solving, collaboration, and continuous growth.
I value clean system architecture, thoughtful design patterns, and purposeful AI integration. Whether building applications, designing interfaces, or developing intelligent features, my focus is always on creating systems that are reliable, scalable, and meaningful.
HTML
CSS
JavaScript
TAILWIND
REACT
LARAVEL
NODE.JS
GITHUB
GIT
C
CSharp
PHOTOSHOP
FIGMA
ILLUSTRATOR
CANVA
PYTHON
R
JUPYTER
LOOKER STUDIO
PANDAS
NUMPY
SCIKIT-LEARN
Active member of the organization, contributing to research and innovation initiatives in the field of education and technology.
Certified in artificial intelligence and machine learning concepts, demonstrating proficiency in AI technologies and their applications.
Certified in technopreneurship education and innovation.
Gaining foundational knowledge of AWS cloud concepts, services, and best practices for cloud computing.
Pursuing graduate studies focused on data science, machine learning, analytics, and intelligent systems.
Managing financial operations and ensuring compliance for the regional chapter.
Teaching and mentoring students in information technology, software development, and research.
Graduated with honors and awarded as Academice achievers and Best in Multi-Media Arts, demonstrating academic excellence and dedication to the field of information technology.
Recognized for developing an innovative technology solution addressing a real-world problem.
Presented and defended an innovative technology solution in a regional-level competition.
Placed among the 100+ competitors in a national information technology skills programming competition, showcasing proficiency in coding and problem-solving.
Placed among the top competitors in a national information technology skills competition.
This project implements a water-quality detection and short-term forecasting prototype for Penaeus vannamei aquaculture.It combines a Random Forest classification model with parameter-specific ARIMA forecasting models and exposes the trained models through a Streamlit web application.
This repository combines data engineering, model training, and forecasting to provide both real-time and short-term predictions for fish kill events in aquaculture ponds. The project includes: Real-time fish kill risk detection using classification models Short-term dissolved oxygen forecasting using ARIMA The result is a practical workflow for early warning and pond management.
A web-based application that allows event organizers to efficiently manage attendee check-ins and validate their attendance using QR codes. The system streamlines the registration process, enhances security, and provides real-time data on attendee participation.
This repository provides beginner-friendly, step-by-step machine learning walkthroughs with runnable notebooks.
