About Me

I am a Control and Automation Engineering student at ITU specializing in the intersection of high-performance software engineering and Machine Learning. To understand the limits of modern AI, I engineered forgeNN, a functional alternative to PyTorch built from the ground up. Currently, I am applying this low-level expertise to rigidRL, a physics based Reinforcement Learning environment I am building in C++. Unlike standard wrappers, rigidRL integrates the neural network and the physics solver into a single, optimized pipeline, minimizing latency to solve complex control problems in real time.

Link to my project forgeNN, a deep learning framework built from scratch in Python/NumPy and available on PyPI.

Link to my project rigidRL, a physics based Reinforcement Learning environment I am building in C++ with forgeNN.