John Langford

John Langford is a researcher at Microsoft Research, USA. His work focuses on foundational areas in machine learning, including reinforcement learning, contextual bandits, and optimization. He has contributed to advancements in scalable and efficient learning systems, with applications in human-computer interaction, robotics, and AI policy learning.

Research Interests: Langford's research spans reinforcement learning (e.g., belief state estimation, latent state discovery), contextual bandits (e.g., decision-making under uncertainty), and model efficiency (e.g., inference-time scaling for complex tasks). His recent work emphasizes developing robust frameworks for AI systems that generalize across diverse tasks and environments.

Publications: His articles address cutting-edge topics like gaze-tracking interfaces, belief state transformers, and ensemble methods for large language models. These contributions highlight his interest in bridging theory and practical applications in AI.

Labs/Teams: His primary affiliation is with Microsoft Research, where he collaborates on projects advancing machine learning and its interdisciplinary applications.