Topic: Deep Reinforcement Learning for Critical Decision Support
• R&D Innovation: Designed a Deep Reinforcement Learning (DRL) architecture for
dynamic resource allocation in constrained environments.
• Technical Development: Implemented advanced algorithms using PyTorch to sim-
ulate intelligent defensive strategies.
• Explainable AI (XAI): Integrated Transformer architectures and attention mecha-
nisms to analyze the explainability of autonomous decisions.
• Robustness: Validated the knowledge transfer of AI agents across unseen scenarios
to ensure adaptability.

Combinatorial Optimization and Deep RL for Infrastructure Networks
• Analysis: Analyzed existing systems and modeled the problem as a combinatorial optimization challenge.
• Implementation: Developed and trained RL agents to maximize traffic flow efficiency within an interchange network.

• Modeling: Developed a tool for generating probabilistic models (Bayesian Networks) for human genetics.
• Packaging: Conducted unit testing, wrote technical documentation, and created a reusable Python package.