Advancing Reasoning Capabilities in Agentic AI Systems

This project aims to push the boundaries of agentic AI by addressing three critical challenges: long-horizon memory, safe and aligned tool usage, and adaptive reasoning. Current language models excel at text generation but lack agency—the ability to plan, act, and adapt in dynamic environments. The research focuses on designing structured memory modules for scalable multi-step reasoning, developing mechanisms to ensure safety and trust in tool interactions, and creating models that dynamically balance underthinking and overthinking for efficient problem-solving. These innovations will enable AI systems to perform complex, real-world tasks with greater reliability, transparency, and autonomy.