Developed a customized open-source static website powered by Jekyll and Minimal Mistakes
Automatically enable dark/light themes based on the user’s OS/browser preferences with the prefers-color-scheme CSS media feature
Created custom containers for a grid view publications page using Liquid, HTML, and CSS
Distributional Deep Q-learning
Implemented Google’s C51 algorithm in PyTorch, and trained it on various Atari games such as Pong and Breakout
Exploited high performance GPU computing to run highly parallelized, batch jobs on the Blue Waters supercomputer
Programmed single-layer networks from scratch and tuned hyperparameters for CNN, RL, and NLP deep neural networks
Modeling and Evolutionary Optimization
Simulated slithering snake and elastocapillary fins using 1D Cosserat rods and position-Verlet time integration in Python
Modeled muscular activations, elastocapillary forces, friction and self-contact boundary conditions
Implemented covariance matrix adaptation evolution strategy (CMA-ES) in Python to minimize generic loss functions
Employed CMA-ES for 40 generations to maximize the snake’s forward velocity and achieve desired fin mechanics
Turbulence Compensation Table - University of Arizona Senior Design
Devised a two axis, active suspension table system for use in a super first-class airplane suite with five colleagues from various engineering disciplines. Awarded the Excellence in Aerospace Electronic System Design prize
Utilized GD&T and manually machined over twenty moving parts for final table assembly
Conducted rigorous trade studies and communicated limitations with sponsor to adjust design requirements
