My journey began in pure computer science, but the end goal was always robotics. Before writing my first line of code, I knew I wanted to build machines that interact with the physical world. When deciding whether to approach this through hardware like mechanical engineering, electrical engineering, or software, my fascination with AI ultimately made the choice clear.
I chose the software path because of a specific vision: combining robotics with machine learning to create systems that feel genuinely "alive." Inspired by sci-fi like Iron Man, Big Hero 6, and Chappie, I realized that while pure hardware builds the body, AI builds the mind. Even computer engineering felt too focused on low-level constraints rather than pushing the boundaries of intelligent autonomy.
Currently, I'm focusing on machine learning and AI while continuously expanding my knowledge in classical robotics. My trajectory is laser-focused on merging these domains by using modern learned autonomy to bring complex physical systems to life.
RL Missile Guidance System
A PPO agent trained to intercept a moving, evasive target in a custom-built 2D physics environment.
Jen & JJ Tint Shop
Languages
Frameworks & Libraries
Tools
Core Domains
Reinforcement Learning
Proximal Policy Optimization, Curriculum Learning, Reward Shaping, Sim-to-Real Transfer.
Classical Controls
PID, Model Predictive Control (MPC), Proportional Navigation.
Simulation & Modeling
Custom Gymnasium Environments, Rigid Body Physics, TVC Dynamics, Curriculum Design.
AI Systems & Pipelines
Vision-Language Models, Perception-Reasoning Separation, Prompt Engineering, Local LLM Deployment.