Skip to Content

Expertise: Machine Learning / Data Analytics / Deep Learning / AI

SAM3 Expertise Areas: Machine Learning / Data Analytics / Deep Learning / Artificial Intelligence

SAM3 researchers have expertise in many advanced analytics methods that allow for the processing of large data sets or complex sensor data.  Through these methods, vast arrays of sensor and other data are analyzed to determine knowledge and information that can be communicated to the older adult leading to action.

Analytics Expertise Areas

Randomly generated thumbnail

K. Van Benthem, B. Wallace, L. McCauley, J. Keillor, S. Marshall, F. Knoefel, T. Friedman, and C. Herdman, “Profiles of Mature Drivers and Their Trust in Telematics‑Based Safety Technologies”, ISG 2026

Randomly generated thumbnail

B. Chimehi, J. Larivière-Chartier, B. Wallace, L. Ault, F. Knoefel, J. Kaye, Z. Beattie, J. Steele, L. Anderson, N.Thomas, “Digital Signatures of Caregiver Burden: Machine Learning Classification Using Multimodal In-Home Sensor Data”, ISG 2026

Randomly generated thumbnail

S. Shafiyan, K. Fraser, F. Knoefel, N. Thomas, M. Kunz, B. Wallace, R. Goubran, A.a Zumbansen, “Revisiting the Cookie Theft Picture for Cognitive Impairment: Assessing Its Relevance for Discourse Analysis After Four Decades”, accepted at Alzheimer’s Association International Conference (AAIC), 2025.

Randomly generated thumbnail

McCauley, L., Benthem, K. V., Herdman, C., Wallace, B., Keillor, J., Goubran, R., Knoefel, F., & Marshall, SM, “Communicating increased driving risk: A study of mature driver expectations”, accepted at Alzheimer’s Association International Conference (AAIC), 2025.

Randomly generated thumbnail

Nasr, M. S. E., Masson, P., Wallace, B., A., Benthem, K. V., Herdman, C., Keillor, J., Goubran, R., Knoefel, F., & Marshall, SM. “Identifying Mature Driver Risk from Naturalistic Driving”, accepted at Alzheimer’s Association International Conference (AAIC), 2025.

Randomly generated thumbnail

W. Sloan, B. Wallace, R. Goubran, H. Sveistrup, “Improved Activity Recognition Through Fusion of Earable Pairs” accepted at IEEE Medical Measurement and Applications Symposium (MeMeA 2025), 2025