A 2018 exploration of evolutionary algorithms applied to Atari games, forking Dennis Wilson’s d9w/CGP.jl, where my contribution was the Atari reinforcement-learning experiment layer (experiment variants, fitness functions, hyperparameter tuning) on top of the upstream Cartesian Genetic Programming framework and its NEAT-inspired speciation.
An in-depth guide to GANs: how two neural networks compete to generate realistic data, the math behind it, and the evolution of objective functions that stabilize training.
A sophomore year deep dive into functional metaprogramming, replicating FFTW’s genfft metaprogram logic in Haskell to generate straight-line optimized C kernels for FFTs, using symbolic DAG representation and algebraic simplification to understand how abstract algebra translates into efficient machine code.
A freshman-year automation tool solving the university scheduling constraint satisfaction problem through web scraping Drexel’s Term Master Schedule and implementing recursive backtracking algorithm to generate every valid schedule permutation satisfying user-defined hard and soft constraints, used throughout undergrad 2016-2020.