Machine Learning
Kaffes was selected as part of the inaugural cohort in recognition of the impact and potential of his work on tail-latency scheduling.
Richard Zemel and Toniann Pitassi were recognized for their paper, "Learning Fair Representations," which established the subfield of machine learning–machine learning and fairness.
Professor David Blei, with co-authors Matthew Hoffman and Francis Bach, is recognized with a Test of Time Award at NeurIPS, the world’s top machine learning conference, for scaling his topic modeling algorithm to billions of documents.
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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