I am a first-year Engineering Science student at the University of Toronto with a passion for machine learning, computer science, robotics, and control systems. I use technology to solve real-world challenges and explore innovative solutions.
My technical interests span machine learning, AI, robotics, and control systems. I love leveraging software and emerging technologies to enhance system performance and solve practical problems.
Developed a real-time emotion detection system using CNNs and Eigenface algorithms to track user reactions during video interactions, enhancing user engagement.
Created a high-performance Pong bot using NeuroEvolution of Augmenting Topologies (NEAT), exploring deep learning techniques like CNNs and Q-learning for improved decision-making.
Designed an AWS-based algorithm to analyze roommate descriptions and compute compatibility through semantic embeddings, efficiently matching roommates with similar habits.
Developed an object detection system using OpenCV to analyze pendulum motion with center origin detection and dynamic graph generation for detailed analysis.
Developed a reinforcement learning agent for a Smash Bros.-style platformer game using rPPO, NEAT, and Stable-Baselines3. Integrated recurrent networks with RecurrentPPO to improve decision-making and evolve optimal network topologies.
Developed a Django app that generates machine learning scripts based on user-defined pipelines. Includes builders for PyTorch and statistical models to streamline custom model development.
Awarded a $3,500 scholarship for a research position in Thailand at KMUTT, where I focus on machine intelligence, neural networks, and robotics.
For more details on my experience, education, and skills, please view my full resume.