Abstract: Recent advances in smart devices and artificial intelligence are transforming personal fitness, health awareness, and self-care. Wearable mobile computing and Artificial Intelligence of Things (AIoT) systems now provide real-time insights into body signals and health metrics, while increasingly informing medical decision-making. Yet, challenges remain in achieving accessibility, affordability, comfort, usability, responsiveness, and scalability. This talk explores how embedding intelligent systems into daily life redefines wellness, fitness, and healthcare—shifting toward pervasive, preventive, and proactive management and personalized care.

I will present my research on developing accessible wearable sensing platforms that enable continuous monitoring and interaction across emotion, fitness, and wellness in diverse communities. This work includes novel form factors leveraging commercial off-the-shelf sensors, computational fabrics, and emerging soft electronics to capture multimodal signals, paired with efficient and privacy-aware systems and algorithms. I will then highlight model-driven analysis approaches—spanning digital signal processing, machine learning, and foundation models—for biosignal analysis and emotion detection from physiological signals and speech. Finally, I will discuss how everyday smart home devices can be repurposed to screen daily functioning, assess mental health, monitor physical well-being, and deliver AI-enabled psychotherapeutic care in collaboration with licensed clinicians.

Short Bio: Jingping Nie is an Assistant Professor in the School of Data Science and Society at the University of North Carolina at Chapel Hill. She received her Ph.D. in Electrical Engineering from Columbia University in 2025, under the supervision of Prof. Fred Jiang and Prof. Matthias Preindl. She received her Master of Science degree (Honor Student) in Electrical Engineering from Columbia University in 2019 and her Bachelor of Science degree (magna cum laude with high honors) in Engineering Science from Smith College in 2017. Her research transforms everyday devices into intelligent healthcare and smart city solutions by co-designing hardware form factors and software for human-centric smart devices in Artificial Intelligence of Things (AIoT) systems. She aims to enhance personal wellness, fitness, and mental health by sensing the physical world in its many forms — and reimagining how AI and machine learning can transform the future of pervasive healthcare across the entire life cycle of data. Her work has been published in various top-tier journals and conferences and received multiple distinctions, including the Best Paper and People’s Choice Demo at ACM MobiSys’24, Best Paper at IEEE ITEC’21, Best Demo at ACM/IEEE IPSN’20, and Best Demo Runner-up at ACM SenSys ’22. She is a recipient of the 2023 Apple Scholars in AI/ML PhD Fellowship, 2023 EECS Rising Stars, 2025 CPS Rising Stars, and the Columbia University Morton B. Friedman Memorial Prize for Excellence. She has served on technical and organizing committees of leading conferences and workshops in the field and is the associate editor for ACM HEALTH and Elsevier Smart Health journals.