Our research explores both biological and digital markers of aging to better understand the complex processes that shape how individuals age. Engineering faculty, working closely with medical colleagues, apply advanced mathematical approaches such as control theory to study how cells behave and move—with the goal of preventing harmful cells from spreading.
Another interdisciplinary team is creating non-invasive, AI-driven technologies to detect, monitor, and assess functional and cognitive decline in older adults, with a focus on conditions such as Alzheimer’s disease, Parkinson’s disease, and frailty. By integrating human language technologies with physiological signals—including speech, eye movement, handwriting, and gait—we aim to develop novel methods for identifying neurological disorders and frailty syndromes.
