The Healthy Aging Data Science Group @ CityUDG

Our group leverages digital health data to better understand and promote healthy aging. We are led by Dr. SAKAL Collin (Collin Sakal) and located at the City University of Hong Kong (Dongguan), 香港城市大学(东莞). We have openings for PhDs and RAs. For more information, please see the “Recruitment” page.

Research Areas

  • The bulk of our current research involves analyzing health data derived from wearables. In our work, we examine how wearable-derived sleep, walking patterns, physical activity, and circadian rhythms associate with adverse health outcomes in older adult populations.

  • Our research is centered around understanding and promoting longevity among older adults through the use of digital health technologies.

  • We are also interested in identifying how wearables could be used for personal health monitoring. More specifically, we explore how wearable device data can be used to train machine learning models for tasks like forecasting sleep quality, monitoring cognitive function, and predicting risk of adverse health outcomes.

  • Functional Data Analysis is an emerging area of statistical methodology that has direct applications to wearable device data analysis. In our lab we leverage functional data analytic methods in digital health research.

Selected Publications

  • Zhang W, Xu W, Chen T, Sakal C, Li X. Integrating images and genomics for multi-modal cancer survival analysis via mixture of experts. Information Fusion (2025). https://doi.org/10.1016/j.inffus.2025.103521

  • Sakal C, Chen T, Xu W, Zhang W, Yang Y, Li X. Towards proactively improving sleep: machine learning and wearable device data forecast sleep efficiency 4-8 hours before sleep onset. SLEEP (2025). https://doi.org/10.1093/sleep/zsaf113

  • Sakal C, Li T, Li J, Li X. Predicting poor performance on cognitive tests among older adults using wearable device data and machine learning: a feasibility study. npj Aging (2024). https://doi.org/10.1038/s41514-024-00177-x

  • Sakal C, Zhao W, Xu W, Li X. Effects of caffeine on accelerometer measured sleep and physical activity among older adults under free-living conditions. BMC Public Health (2024). https://doi.org/10.1186/s12889-024-20115-6

  • Sakal C, Li T, Li J, Yang C, Li X. Association Between Sleep Efficiency Variability and Cognition Among Older Adults: Cross-Sectional Accelerometer Study. JMIR Aging (2024). 10.2196/54353

  • Sakal C, Li T, Li J, Li X. Identifying Predictive Risk Factors for Future Cognitive Impairment Among Chinese Older Adults: Longitudinal Prediction Study. JMIR Aging (2024). 10.2196/53240

  • Sakal C, Li J, Xiang YT, Li X. Development and validation of the Chinese Geriatric Depression Risk calculator (CGD-risk): A screening tool to identify elderly Chinese with depression. Journal of Affective Disorders (2022). https://doi.org/10.1016/j.jad.2022.09.034

Location

The City University of Hong Kong (Dongguan, CityUDG) is located in the Songshan Lake, Guangdong Province, China. Songshan Lake is home to tech giants like Huawei and within commuting distance of Dongguan’s city center, Shenzhen, Guangzhou, and Hong Kong. The CityUDG campus is brand new, having opened in 2024, and is currently expanding.