I Build Things.
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I enjoy tackling interdiciplinary problems. Thriving at the intersection of mechanical systems, electronics, software development and system design, I always try to approach problems holistically.
Whether it’s iterating on aerodynamic designs, building AI agents, or crafting intuitive user experiences, I leverage my diverse skills to build efficient, impactful, and scalable solutions.
What I've Done!
DJI RoboMaster DART team
Collaborated with NUS Calibur Robotics to develop a high accuracy projectile launching robot to iterations on.
Building Agentic AI systems
Spent a summer fighting AI frameworks, pipelines and endless documentation. As unpredictable and frustrating they can be, engineering a reliable system from the ground up was a fun experience, so... here's a concoction of my thoughts from building an agentic orchestration system.
Autonomous Heat-Seeking Bot
Built a fully autonomous robot using ROS2, capable of navigating a maze, detecting thermal sources, and launching projectiles. The system integrated pathfinding and heatsensing together with mechanical flywheels.
A Reinforcement Learning Journey: From First Principles to Robotic Control
Self-taught progression through reinforcement learning, breaking down the key insights from foundational papers on policy gradients, actor-critic methods, and their application to complex control tasks.
Implementation of Fundemental ML Concepts
Built increasingly complex ML models ranging from simple bigram models to a basic transformer model. During which, implemented concepts from the following papers; Wavenet a generative model for raw audio, Attention is all you need, Deep residual learning for image recognition, Improving neural networks by preventing co-adaptation of feature detectors ML Paper (Dropout Technique)
Soybean Decision Support System: Leveraging NASA Satellite Data
NASA SpaceApps 2024, My team developed a data-driven approach towards optimizing decision making in selecting appropriate Soy Beans by regions
