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.

    Latest news in artificial intelligence and machine learning

    Sixteen new professors join the MIT community, with research areas ranging from robotics and machine learning to health care and agriculture.

    A new technique boosts models’ ability to reduce bias, even if the dataset used to train the model is unbalanced.

    A new methodology simulates counterfactual, time-varying, and dynamic treatment strategies, allowing doctors to choose the best course of action.

    The Department of Electrical Engineering and Computer Science (EECS) is proud to announce the following promotions: Adam Belay is being promoted to Associate Professor Without Tenure, effective July

    Meta (Facebook) recently announced the winners of its highly competitive 2022 fellowships. The incoming group of Fellowship recipients includes four MIT graduate students, two of whom study within

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