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Applying modern bioengineering approaches to aging research can revolutionize how we think about and study aging. As our worldwide population grows older, staying free of chronic illness and other aging-related diseases has never been more important. Aging is complex and presents significant challenges to healthcare, quality of life, and health equity. However, to make significant strides and optimize human health across the lifespan, we must take unconventional approaches. Bioengineering is poised to have a significant impact on aging and longevity research by developing new concepts, innovative technologies, and AI/ML strategies to improve health and resilience. This course will build on emerging concepts in aging biology, mechano-biology, immuno-engineering, and data science. Specific topics will include: a) developing conceptual frameworks for aging and a bioengineering perspective for why we age differently; b) scales of aging (i.e., groups of genes to groups of people); c) hallmarks and biomarkers of aging; d) senescence; e) mechano-biology of aging; f) cellular reprogramming for engineered resilience; and g) the applications of data science, modeling, and AI/ML strategies to predict aging trajectories, health, and aging interventions. We will also discuss new frontiers of aging and areas that could benefit from emerging bioengineering perspectives that include reproductive longevity, democratizing longevity science: ethical and societal implications of aging and longevity interventions, and perturbation science: cells as sensors of health and disease. The goal is for students to gain a deep understanding of how biomedical engineering can reshape the future of aging and longevity. Students are expected to complete class readings, weekly assignments, class presentations, and group projects. Recommended background: data science principles, cellular and tissue engineering, and fundamentals of biomedical engineering.