Machine Learning
Adam Cannon is part of the first cohort of professors being honored for excellence and innovation in teaching.
Richard Zemel and Toniann Pitassi were recognized for their paper, "Learning Fair Representations," which established the subfield of machine learning–machine learning and fairness.
Teaching AI to distinguish between causation and correlation would be a game changer— well, the game may be about to change.
About
The group does research on foundational aspects of machine learning — including causal inference, probabilistic modeling, and sequential decision making — as well as on applications in computational biology, computer vision, natural language and spoken language processing, and robotics.
It is part of a broader machine learning community at Columbia that spans multiple departments, schools, and institutes. Activities include seminars on statistical machine learning, several student-led reading groups and social hours, and participation in local events such as the New York Academy of Sciences Machine Learning Symposium.
Causal Artificial Intelligence Lab 
Machine Learning @ Columbia 
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