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

    The prize is the top honor within the field of communications technology.

    Seven researchers, along with 14 additional MIT alumni, are honored for significant contributions to engineering research, practice, and education.

    Department of EECS Assistant Professors Connor Coley and Dylan Hadfield-Menell have been named to the inaugural cohort of AI2050 Early Career Fellows by Schmidt Futures, a philanthropic initiative from Eric and Wendy Schmidt aimed at helping to solve hard problems in AI.

    Six distinguished scientists with ties to MIT were recognized “for significant contributions in areas including cybersecurity, human-computer interaction, mobile computing, and recommender systems among many other areas.”

    As the pioneers of a developing field, data scientists often have to deal with a frustratingly slippery question: what is data science, precisely, and what is it good

    Upcoming events