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Computer scientists employ AI to help address COVID-19 challenges
  1. Computer scientists employ AI to help address COVID-19 challenges

    Five multidisciplinary research teams are working on projects to assist with the coronavirus outbreak and to help find solutions to pressing problems.

  2. Emily Mower Provost named Toyota Faculty Scholar

    Her work uses machine learning to measure mood, emotion, and other aspects of human behavior for purposes of providing early or real-time interventions for people in managing their health.

  3. CSE researchers present 9 papers at leading AI conference

    The students and faculty submitted projects spanning several key application areas for AI.

  4. Alumnus Peter Wurman inducted into National Inventors Hall of Fame

    Wurman and his cofounders were recognized for their invention of the Kiva system, a revolutionary warehouse order fulfillment system that uses mobile robots and control software to bring inventory shelves to workers.

  5. Michigan AI celebrates second annual symposium

    The goal of the symposium is to facilitate conversations between AI practitioners from Michigan and beyond.

  6. New attack on autonomous vehicle sensors creates fake obstacles

    Up to this point, no attacks had been discovered targeting a car’s LiDAR system—but a major new finding from researchers at the University of Michigan has demonstrated what that might look like.

  7. Taking machine-learning models in health care from concept to bedside

    The authors provide an overview of common challenges to implementing ML in a health-care setting, and describe the necessity of breaking down the silos in ML.

  8. Year of growth, experiments for May Mobility

    May Mobility intends to gradually acclimate the public to the experience of autonomous driving.

  9. DARPA Award for more responsive AI that combines human and machine

    The goal of Lasecki’s proposal is to create methods for making AI systems more robust and flexible.

  10. Paper recognized for lasting contributions to AI decision making

    Baveja’s paper tackled the difficult problem of giving artificial intelligence a way to understand and represent knowledge collected over time.