Centre for Analytics & AI Engineering (CARTE)

carte.utoronto.ca

As the hub for collaborations and partnerships in analytics and artificial intelligence at The University of Toronto's Faculty of Applied Science and Engineering, our mission is to conduct state-of-the-art research while nurturing the next generation of engineering talent. We seek to translate and commercialize effective solutions in engineering and be a catalyst for our partners to make a significant and lasting impact in the global marketplace. We partner with industry and government to drive collaborative research between technical analytics and artificial intelligence experts and those with domain-specific knowledge. Through these partnerships, we also cultivate new experiential learning opportunities for students, including internships, professional experience year co-op placements, capstone projects and MEng projects. We have 102 faculty affiliates from eight different departments and units within the University of Toronto's Faculty of Applied Science and Engineering, namely: Chemical Engineering, Civil and Mineral Engineering, Electrical and Computer Engineering, Institute for Biomedical Engineering, Mechanical and Industrial Engineering, Materials Science Engineering, University of Toronto Institute for Aerospace Studies, and Institute for Studies in Transdisciplinary Engineering Education & Practice (ISTEP). Our faculty affiliates apply analytics, artificial intelligence, and machine learning techniques to tackle issues in a variety of sectors, including health care, urban planning and transportation, robotic systems, social networks, the energy sector, materials sciences, mining, the financial industry, the sport industry, and the education sector. We facilitate research partnerships and provide support to match funds from government sources. We also provide technical and executive level training in the field. To discuss collaboration opportunities with us, please contact: [email protected]

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As the hub for collaborations and partnerships in analytics and artificial intelligence at The University of Toronto's Faculty of Applied Science and Engineering, our mission is to conduct state-of-the-art research while nurturing the next generation of engineering talent. We seek to translate and commercialize effective solutions in engineering and be a catalyst for our partners to make a significant and lasting impact in the global marketplace. We partner with industry and government to drive collaborative research between technical analytics and artificial intelligence experts and those with domain-specific knowledge. Through these partnerships, we also cultivate new experiential learning opportunities for students, including internships, professional experience year co-op placements, capstone projects and MEng projects. We have 102 faculty affiliates from eight different departments and units within the University of Toronto's Faculty of Applied Science and Engineering, namely: Chemical Engineering, Civil and Mineral Engineering, Electrical and Computer Engineering, Institute for Biomedical Engineering, Mechanical and Industrial Engineering, Materials Science Engineering, University of Toronto Institute for Aerospace Studies, and Institute for Studies in Transdisciplinary Engineering Education & Practice (ISTEP). Our faculty affiliates apply analytics, artificial intelligence, and machine learning techniques to tackle issues in a variety of sectors, including health care, urban planning and transportation, robotic systems, social networks, the energy sector, materials sciences, mining, the financial industry, the sport industry, and the education sector. We facilitate research partnerships and provide support to match funds from government sources. We also provide technical and executive level training in the field. To discuss collaboration opportunities with us, please contact: [email protected]

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Potential Decision Makers

  • Research and Education Director

    Email ****** @****.com
    Phone (***) ****-****
  • Assistant Director

    Email ****** @****.com
    Phone (***) ****-****

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