Machine Learning
Teaching AI to distinguish between causation and correlation would be a game changer— well, the game may be about to change.
Blei is recognized for his groundbreaking work in machine learning, in particular his field-defining contributions in the areas of topic models and stochastic variational inference.
Five papers from CS researchers were accepted to the 41st International Conference on Machine Learning (ICML 2024).
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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