Artificial Intelligence and Machine Learning

    Our research covers a wide range of topics of this fast-evolving field, advancing how machines learn, predict, and control, while also making them secure, robust and trustworthy. Research covers both the theory and applications of ML. This broad area studies ML theory (algorithms, optimization, etc.); statistical learning (inference, graphical models, causal analysis, etc.); deep learning; reinforcement learning; symbolic reasoning ML systems; as well as diverse hardware implementations of ML.

    Faculty

    Latest news in artificial intelligence and machine learning

    Ranking at the top for the 13th year in a row, the Institute also places first in 11 subject areas.

    The Institute of Mathematical Statistics (IMS) fosters the development and dissemination of the theory and applications of statistics and probability.

    Associate Professor Jonathan Ragan-Kelley optimizes how computer graphics and images are processed for the hardware of today and tomorrow.

    The Institute also ranks second in five subject areas.

    MIT professors Roger Levy, Tracy Slatyer, and Martin Wainwright appointed to the 2024 class of “trail-blazing fellows.”

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