Ever since third grade, I have been attending science fairs, though initially conducting science projects as school assignments. This all changed when I realized how excited I was about planting my mung beans under different colored cellophane covers. Every day after school, I was filled with excitement observing the growth of the plants and drawing scientific conclusions based on my experiments.

Since then, I have relished exploring a variety of scientific subjects and have continued to participate in science fairs every year. I find great satisfaction in presenting my research results at these events, and my topics have ranged from investigating plant and salt properties to exploring the electrical conductivity of household materials, as well as using Raspberry Pi for facial recognition to improve learning efficiency with AI.

In high school, my experience during the pandemic inspired my project using AI to improve learning efficiency. As an online tutor, I found it challenging to detect my students' level of engagement through a screen, especially as many were hesitant to ask questions. Failing to identify a student’s learning bottleneck became detrimental to how I proceeded with my teachings, and I recognized this as a critical issue to solve.

This led me to ponder how effective Artificial Intelligence and Machine Learning could be when applied to learning behavior analysis and providing learning engagement results to instructors. Because of this, I embarked on my AI research journey and conducted my first project, “Computer Vision with Biometric Information for Engagement Detection in Virtual Learning,” which targets advanced personalized learning that still remains my passion.