Carte supports collaborative research designed for real-world impact — bridging AI with civil engineering, healthcare, sustainability, and beyond. We help partners navigate funding and connect with faculty who can solve their specific challenges.
Carte-supported research solving real engineering challenges — from building science to healthcare to sustainability.
Olson, A.W. & Saxe, S.
A simplified, scalable approach to estimating building heights from single street-level images using deep learning, enabling rapid urban infrastructure assessment.
Huang, W., Olson, A.W., Khalil, E.B. & Saxe, S.
Leveraging deep learning to predict residential building characteristics from imagery, supporting sustainable housing analysis and urban planning decisions.
Park, S., Bae, Y., Han, G. & Olson, A.W.
A novel approach using vision-language models to detect and assess deepfake media, advancing AI safety and digital content authenticity.
Collaborative research across 8 engineering departments — with a focus on practical applications and real-world impact.
Guven, G., Arceo, A., Bennett, A., Tham, M., Olanrewaju, B., McGrail, M., Isin, K., Olson, A.W. & Saxe, S.
A comprehensive database enabling researchers to analyze resource consumption patterns in construction.
Raju, S., Roche-Nagle, G., Olson, A., Eisenberg, N. & Chan, T.
Applying ML algorithms to identify sex-based differences in surgical thresholds for improved patient outcomes.
Mendell, A.Y., Olson, A.W. & Siegel, J.A.
Research on optimizing air filtration systems through adaptive threshold algorithms for better indoor air quality.
Huang, W., Olson, A., Khalil, E.B. & Saxe, S.
A conference note demonstrating how deep learning models can infer key residential house attributes directly from imagery, laying the groundwork for scalable, data-driven housing and sustainability analysis.
Kim, J., Seo, M., Choi, E. & Olson, A.
Machine learning models for predicting candidate interview engagement on a real-time recruitment platform under extreme class imbalance, highlighting the importance of behavioral and temporal features alongside algorithmic match scores.
Whether you're a faculty member seeking AI expertise, an industry partner looking to sponsor research, or a student interested in applied AI projects—we're here to help.