Xi Yang

Xi (Cecilia) Yang is a Staff Research Scientist at IBM, with research interest spanning machine learning, reinforcement learning, and LLM-based agentic systems. Her work focuses on developing intelligent, adaptive, and scalable AI methods for real-world applications, with impact across healthcare, education, and IT automation.

Cecilia received her Ph.D. in Computer Science from North Carolina State University, where her research centered on designing and advancing machine learning and reinforcement learning approaches for healthcare and education. Since joining IBM, she has focused on applying AI to IT automation, developing solutions that improve the efficiency, reliability, and autonomy of enterprise IT operations. Since 2025, her research has increasingly focused on LLM-based agentic systems for IT operations. Her recent work explores reinforcement learning-guided agent decision-making, automated knowledge distillation, and self-evolving LLM agents, with the goal of enabling more capable, trustworthy, and autonomous AI systems.

She actively contributes to the AI research community and has served as a program committee member and reviewer for leading conferences in artificial intelligence and machine learning, including ICML, ICLR, NeurIPS, KDD, and AAAI.