Hello!
I'm Manuel Olalo Jr., a graduating CS student at Mapúa University, passionate about building practical software solutions that combines software development, automation, and AI integration. My experience spans web systems, enterprise applications, and process automation, focusing on writing efficient, maintainable code while delivering real-world impact in academic and corporate environments.
Education
Bachelor of Science in Computer Science, Mapua University (2026) - Specialized in Artificial Intelligence
Professional Experience
Procurement Operations Intern
Accenture
October 2025 - January 2026
Supported enterprise procurement operations by validating financial data and developing automation scripts to reduce manual workload and improve processing accuracy.
- Reconciled SAP & Ariba invoice data
- Automated Excel workflows using Python
- Developed Selenium browser automation
- Increased operational efficiency through scripting
Global Engineering Intern
Universal Robina Corporation
May 2025 - September 2025
Developed enterprise applications and automation solutions to streamline engineering project tracking and payment management processes using Microsoft Power Platform and data-driven dashboards.
- Built Project & Payment Management Apps
- Designed Power BI operational dashboards
- Automated workflows with Power Automate
- Improved internal process efficiency
Freelance Software Developer
Self-Employed
August 2023 - March 2024
Provided technical guidance and development support to university students on academic software projects, primarily using Java, C++, and Python.
- Developed and assisted with Java, C++, and Python projects
- Provided debugging support and code reviews to improve functionality and structure
- Collaborated with peers to meet project requirements
- Explained core programming concepts and best practices
Selected Projects
Click on any project to expand and see more details and images
Research Papers
Selected Academic Research and Publications
Fish Disease Classification using Transfer Learning with ResNet50
Miggy Olalo, Andrew Canlas, Jodd Villegas
Mapua University • 2026
Developed an image-based classification system for detecting common Tilapia diseases using a ResNet50 transfer learning approach, achieving improved accuracy through image preprocessing, data augmentation, and comparative model evaluation against a baseline CNN.
A Study on the Proposed Prototype of WikaSaya using Design Thinking Apporach Introduction
Miggy Olalo, Daphnie Abano, John Lam, Kacey Vidal
Mapua University • 2025
Presented WikaSaya, a gamified mobile learning app for children aged 2–8, designed to enhance Filipino language literacy and cultural awareness. Using the Design Thinking Approach and feedback from parents and teachers via the Six Thinking Hats method, the study highlights the app’s potential while addressing UX and screen-time considerations.
Analysis of Global Video Game Sales
Miggy Olalo, Raymond Cruz, Dylan Magana, Paul Tuason
Mapua University • 2024
Analyzed global video game sales using a 16,000+ row Kaggle dataset to uncover sales patterns across regions and key factors influencing success. The study provides actionable insights for publishers on market strategies, game development, and product release planning, highlighting the economic, social, and cognitive significance of video games in today’s world.
AI-Driven Analysis of Poverty Indicators
Miggy Olalo, Paul Tuason, Andrew Canlas, Arjun Bali
Mapua University • 2024
Applied AI and machine learning models, including Random Forest, Logistic Regression, and deep learning, to analyze socioeconomic indicators from the APIS dataset and predict poverty status among Filipino households. Findings highlight critical factors like food consumption and household demographics, demonstrating AI’s potential to inform targeted policy and resource allocation for poverty alleviation.
Skills & Technologies
A comprehensive overview of my technical expertise across multiple domains