Designing AI with purpose and people in mind.
At Cornell, we approach artificial intelligence with curiosity, conscience, and collaboration. Since the early 1990s, our department has been building one of the world’s most respected AI research communities — recognized globally for its innovations, integrity, and impact. Unlike larger programs, we’ve intentionally fostered a close-knit culture where cooperation and diverse perspectives accelerate progress.
From robotics and ethics to computational sustainability, our work spans disciplines and domains — grounded in the belief that AI must be understood not only as a tool, but as a force that is shaping society. We ask not just what AI can do, but what it should do — for people, for the planet, and for the future.
Cornell AI Initiative
The Cornell AI Initiative advances our reputation as a leader in AI research. This university-wide initiative encompasses AI development, education, and ethics by leveraging the broad, interdisciplinary collaborations for which we’re known.

Faculty exploring AI.
Our faculty bring an unparalleled level of understanding and experience in AI to researching and solving today’s emerging challenges.





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- Research + Innovation
Core Areas of Artificial Intelligence Research
Cornell’s AIPP initiative brings together experts from computing, law, philosophy, and sociology to study AI as a socio-technical system, aiming to guide its development and impact through interdisciplinary research and policy engagement.
To learn more about this initiative, visit the Artificial Intelligence, Policy, and Practice (AIPP) research group.
This research group explores discrete solution spaces to solve optimization or decision problems, often using algorithms like backtracking or heuristic search. It connects to operations research through optimization methods and to statistical physics via models of system behavior and complexity.
To learn more about this research, visit the research group.
The Institute for Computational Sustainability applies advanced computing methods to address environmental, economic, and societal challenges, fostering interdisciplinary research for a sustainable future.
To learn more about this research, visit the Computational Sustainability research group.
This research group studies strategic decision-making and game-theoretic models to understand interactions among rational agents. Their work bridges computer science and economics, focusing on topics like market design, auctions, and incentive-compatible algorithms.
To learn more about this research, visit the research group.
This research group studies how to encode and reason about knowledge in ways machines can use, developing logical frameworks, ontologies, and algorithms for tasks like planning, diagnosis, and natural language understanding.
To learn more about this research, visit the research group.
Machine Learning at Cornell is an interdisciplinary learning and research group made up of Cornell University faculty and hundreds of involved students and alumni. The group comes together from different departments to celebrate and promote the history of machine learning at the university.
To learn more about this research, visit Machine Learning at Cornell.
The Cornell Computational Linguistics Lab and NLP Group collaborate on research in computational models of language, covering areas like syntax, semantics, psycholinguistics, and machine learning, with applications in natural language understanding, social science, and the humanities.
To learn more about this research, visit the research groups:
Natural Language Processing (NLP) Group and Computational Linguistics Lab.
Robotics@Cornell is an interdisciplinary research initiative exploring areas like autonomy, perception, control, and human-robot interaction, utilizing various robotic platforms including aerial, assistive, and humanoid robots.
To learn more about this research, visit Robotics@Cornell.

