Asil Andrei Acasio

About

As a fourth year Electronics Engineering student at the University of the Philippines Diliman, I'm honing my skills to become a versatile and adaptable full-stack software engineer. My background in electronics has equipped me with a strong foundation in technical problem-solving and communication systems (ex. the internet).

I'm interested in machine learning and IoT, and I've built projects in these areas. I love exploring how technology can solve real-world problems. I use Arch btw.

Outside of school and coding, I am a casual 🎸, a regular 🎮, a binge 📺 show watcher, and an 💪 active person.

Experience

May 2024 — October 2024

Web and Mobile App Developer Intern

Symph

Contributed to two projects involving frontend development using NextJs, backend API development with NestJS, and cloud configuration on Google Cloud Platform. This experience enhanced my technical skills and understanding of the web development lifecycle.

June 2019 — July 2019

Digital Signal Processing Lab Intern

UP EEEI

Assisted in collecting data from various signal sources such as audio from Philippine native instruments and human vital signs sensor data for research by using Python and MATLAB.

Projects

Automatic Smoke Observer

A remote monitoring and alerting system for forest fires mitigation, which was built with a Raspberry Pi equipped with smoke sensors and a camera. Trained and integrated a YOLOv5 model for fire and smoke detection through images. Gold awardee at the Malaysia Technology Expo 2021.
Python
Raspberry Pi
Arduino
YOLOv5
OpenCV

Personal Portfolio

My personal portfolio website built with Next.js, Tailwind CSS, and animated with Framer Motion.
ReactJs
NextJs
Tailwind

Hayahay

An IoT-based home automation system for controlling lights, fans, and other appliances. Interfaced sensor components with ESP32 microcontrollers and controlled them through a Flutter app. Built backend services with Firebase and Python.
Flutter
Python
Firebase
IoT

Buoywatch

A buoy-based system that detects and reports illegal fishing. Trained and integrated a YOLOv5 model for fishing vessel image detection. Built as an entry for the 2021 Karagatan Hackathon.
Python
OpenCV
Tensorflow
YOLOv5

© 2025 Asil Andrei Acasio. Built with Next.js and Tailwind CSS. Layout inspired from Brittany Chiang.