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About

Peter Henderson is a versatile researcher whose work spans artificial intelligence, deep reinforcement learning, and responsible AI development. He is perhaps best known as a co-author of the landmark 2021 report "On the Opportunities and Risks of Foundation Models," which introduced the now widely-adopted term "foundation models" to describe large-scale systems like GPT-3 and DALL-E — a paper that has garnered over 2,177 citations and helped shape how the research community thinks about modern AI. Henderson has also made significant contributions to the pedagogy of deep reinforcement learning, co-authoring an influential introductory text that has collectively accumulated nearly 1,800 citations, making it a go-to resource for students and practitioners entering the field. His earlier work reflects a broad technical curiosity, touching on multi-robot coordination in underwater environments and variance reduction techniques in RL training. Even his undergraduate-era exploration of neural interfaces demonstrates a longstanding interest in the intersection of AI and real-world systems. Across his career, Henderson has proven adept at both advancing technical frontiers and communicating complex ideas accessibly — a rare and valuable combination in modern AI research.