Work
Projects
From-scratch implementations exploring reinforcement learning, graph neural networks, and deep learning foundations.
Reinforcement Learning
RL From Scratch
Practical reinforcement learning implementations with reproducible experiments. Covers value-based methods, policy gradients, and actor-critic architectures.
View project → Graph Neural NetworksGNN Concepts From Scratch
From-scratch graph neural network work focused on foundations — message passing, spectral methods, and graph attention.
View project →