I am an engineer and researcher specializing in machine learning, reinforcement learning, and AI. I hold a Ph.D. in Electrical Engineering and have extensive experience developing and implementing reinforcement learning systems from scratch. My work spans the full RL spectrum, including model-free methods (REINFORCE, Actor-Critic, PPO, DQN), model-based RL, offline RL (CQL, Decision Transformers), and modern RLHF approaches used in training large language models.

I focus on making reinforcement learning practical and accessible for engineers through clear explanations, clean implementations, and hands-on experimentation. My goal is to bridge the gap between theory and real-world applications, helping learners build a deep and usable understanding of RL.