CARTE Research

On this page

    Research Support

    Facilitating collaborative applied research in Artificial Intelligence (AI) involving external partners, faculty members and students

    CARTE capitalizes on Toronto's position as a world-class research powerhouse in analytics and artificial intelligence (A/AI) and its close proximity to a wide range of industry clusters, from biomedical technology to advanced manufacturing.

    We support basic research in analytics and artificial intelligence (A/AI) methodologies that may have broad applications, by driving collaborative research between technical A/AI experts and those in other domains. We catalyze the launch of large-scale multi-investigator research partnerships and provide support to match funds from government sources.

    Learn more about our research support services for:


    CARTE Affiliate Faculty Research Portfolio

    Professor Chandra Veer Singh uses high throughput simulations, machine learning, and available experimental data to enable design of high entropy alloys for structural applications

    Professors Yu Zou and Chi-Guhn Lee are integrating Additive Manufacturing and AI to develop a “self-driving 3D printing system” that senses/predicts defects and corrects processing parameters adaptively

    Professor Deepa Kundur is developing an Integrated Co-Simulation and AI-based data analytics platform for smart grid modeling and cybersecurity analysis

    Professor Ben Liang applies machine learning to categorize the network traffic and optimally balance the trade-off between accuracy, privacy, cost, and delay

    Professors Babak Taati and Andrea Laboni work on ambient monitoring of gait in long-term care facilities to automatically identify residents who are at a high risk of falling

    External Partners

    Are you currently working in industry, government or the non-profit sector and want to sponsor applied research in your field? We facilitate research collaborations with our faculty affiliates and research staff. We also provide support to leverage funds through government sources such as NSERC Alliance and MITACS . Contact us to learn more. If you have an applied AI research project but don’t have the funding to sponsor research, contact us to learn about opportunities to have upper-year undergraduate students work on these projects as capstone design projects.

    Faculty Members

    Are you a faculty member conducting research in a specific domain and are looking for AI experts to lead the technical aspects of a research project and provide guidance to your students? Contact us to learn more about our research support services on a cost-recovery basis. Looking for a student research assistant, too? Make sure you ask about our CV bank of Master of Engineering students looking for research project opportunities.

    Past collaborations have produced high-quality publications and presentations, including:

    • Mendell, A. Y., Olson, A. W., & Siegel, J. A. (2022). Evaluation of fixed and adaptive concentration thresholds for particle filter systems. Indoor air, 32(10), e13134.
    • Huang, W., Olson, A., Khalil, E. B., & Saxe, S. (2022, June). Note: Image-based Prediction of House Attributes with Deep Learning. In ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies (COMPASS) (pp. 693-695).
    • Guven, G., Arceo, A., Bennett, A., Tham, M., Olanrewaju, B., McGrail, M., Isin, K., Olson, A.W. and Saxe, S., 2022. A construction classification system database for understanding resource use in building construction. Scientific Data, 9(1), pp.1-12.
    • Huang, W., Olson, A., Khalil, E., & Saxe, S. (2022, June 29–July 1). Image-based Prediction of House Attributes with Deep Learning [Poster]. ACM SIGCAS Conference on Computing and Sustainable Societies, Seattle, WA.
    • Raju, S., Olson, A., Deghan, S., Eisenberg, N., Chan, T.C.Y., and Roche-Nagle, G. (2022, August 18-21). Utilizing machine learning algorithms to evaluate sex-based differences in preoperative hemoglobin thresholds in open vascular surgery [Poster]. SVS 2021 Annual Vascular Meeting, San Diego, CA.

    University of Toronto Students

    Are you a University of Toronto engineering student looking for technical guidance on your AI research projects? Book a free AI research drop-in clinic with a CARTE senior research associate using your University of Toronto email address.

    Are you a University of Toronto engineering student looking to work on applied AI research projects in industry settings? Look no further than current MITACS opportunities for internships in Analytics/AI/Machine Learning (updated frequently).

    Are you a University of Toronto Master of Engineering student looking for research project opportunities in Analytic, AI, and Machine Learning? Send us your CV to be added to our CV bank.

    CARTE Seed Research Funding

    In 2020 and 2021, CARTE funded multi-disciplinary, high-impact projects that connected pairs of faculty researchers with complementary expertise.