Ashik Abrar
Naeem

I am a researcher, engineer and currently working as an adjunct lecturer in the department of EEE, BUET. My research interests arises from a fundamental question: "How can we synthesize intelligent behaviors in complex, uncertain systems while maintaining absolute, mathematical guarantees of safety and stability?". To answer this, I seek to scrutinize the modern tools (e.g. deep learning, reinforcement learning) and establish rigorous proofs of safety and stability. I am working to bridge the empirical success of deep and reinforcement learning with the formal rigor of control theory and leveraging stochastic control, optimal transport, and Schrödinger bridges to extend deterministic safety boundaries into highly probabilistic environments. Recognizing that advancing this frontier requires a profound theoretical baseline, I am aggressively deepening my mathematical toolkit in real analysis and abstract linear algebra. I am directing this trajectory toward a Ph.D. in Fall 2028, seeking an academic environment that champions both deep mathematical rigor and the real-world deployment of autonomous architectures. Ultimately, my ambition is to push the frontiers of information and decision systems, developing foundational theories that render the next generation of autonomous systems structurally verified and intrinsically safe.