Nesreen Ahmed

As a Senior Principal Scientist at Cisco AI Research, I lead research and system development in agentic AI, large language models (LLMs), graph intelligence, and intelligent AI systems, advancing both foundational methods and enterprise-scale applications. My work focuses on multi-agent reasoning, personalization, and autonomous workflows, developing scalable architectures that integrate LLM-driven planning, reasoning, and graph-based knowledge into deployable enterprise AI systems. Previously, I spent nine years at Intel Labs, where I led research programs at the intersection of machine learning and programming systems, advancing AI-driven compiler optimization, code generation, and generative code intelligence for high-performance computing. My work helped bridge algorithmic research with systems-level performance and developer productivity. More broadly, my research spans multi-agent systems, graph foundation models, personalization, and code intelligence, reflecting a cross-disciplinary approach that unites learning, reasoning, and systems architecture. I am particularly interested in building trustworthy, adaptive, and scalable AI systems that can reason, collaborate, and act autonomously in complex environments. Author of 100+ publications and patents in machine learning, graph learning, and AI systems, with work appearing at venues such as NeurIPS, ICML, ICLR, EMNLP, ACL, KDD, Super Computing, CGO