Email lwei65@nus.edu.sg

Insufficient physical activity contributes to more than 5 million deaths each year, yet around one in three adults worldwide remain insufficiently active. Understanding how different patterns of physical activity are associated with health outcomes can inform sustainable health promotion strategies that help overcome barriers to physical activity. Wei Le and his colleagues work with large-scale datasets to explore these patterns and identify findings that could inform more sustainable and effective approaches to promoting physical activity.

Outside of work, he enjoys playing soccer and go travelling, and exploring different cultures. He has a cute cat he would love to take everywhere he goes, but the cat prefers staying at home.

• NUS Saw Swee Hock School of Public Health

• Physical Activity Epidemiology
• Chronic disease

• B.Sc., Kansas University. 2012
• M.Sc., Hofstra University. 2015
• Ph.D. Sydney University. 2025

• Statistician, 2017-2021, Zhengzhou University
• Research Officer, 2025, Sydney University
• Research Fellow, 2026-Present, National University of Singapore

• Wei L., Ahmadi M. N., Koemel N. A., et al. (2026). Combinations of stepping intensity and daily step counts against all-cause and cardiovascular disease mortality: insights from a device-based prospective study. Br J Sports Med, 60, 1401–1408. DOI: 10.1136/bjsports-2025-111173
• Speirs, C., Wei, L., Ahmadi, M. N., Hamer, M., Stamatakis, E., Granat, M. (2026). Ambulatory Tasks and Journeys: A Framework for Free-Living Behaviour. Sensors, 26(6), 1754. DOI: 10.3390/s26061754
• Wei L., Ahmadi M.N., Blodgett, J. M., Aguiar, E. J., Biswas, R. K., Koemel, N. A., del Pozo Cruz, Borja., & Stamatakis, E. (2025). Does the choice of stepping intensity metric influence dose–response associations with mortality? A UK population cohort study of 65,253 adults. Med Sci Sports Exerc, 58(3), 506-516. DOI: 10.1249/MSS.0000000000003887
• Wei, L., Ahmadi, M. N., Hamer, M., Blodgett, J. M., Small, S., Trost, S., & Stamatakis, E. (2024). Comparing cadence-based and machine learning based estimates for physical activity intensity classification: The UK Biobank. Journal of Science and Medicine in Sport, 27(8), 551-556. DOI: 10.1016/j.jsams.2024.05.002
• Wei, L., Ahmadi, M. N., Biswas, R. K., Trost, S. G., & Stamatakis, E. (2024). Comparing Cadence vs. Machine Learning Based Physical Activity Intensity Classifications: Variations in the Associations of Physical Activity with Mortality. Scandinavian Journal of Medicine & Science in Sports, 34(9), e14719. DOI:10.1111/sms.14719
• Ahmadi, M. N., Holtermann, A., Tudor-Locke, C., Koster, A., Johnson, N., Chau, J., Wei, L., … & Stamatakis, E. (2024). Time to elicit physiological and exertional vigorous responses from daily living activities: setting Foundations of an Empirical Definition of VILPA. Medicine and Science in Sports and Exercise, 56(12), 2413-2420. DOI: 10.1249/MSS.0000000000003521
• Wei, L., Ahmadi, M. N., Chan, H. W., Chastin, S., Hamer, M., Mishra, G. D., & Stamatakis, E. (2023). Association between device‐measured stepping behaviors and cardiometabolic health markers in middle‐aged women: The Australian Longitudinal Study on Women’s Health. Scandinavian Journal of Medicine & Science in Sports, 33(8), 1384-1398. DOI: 10.1111/sms.14363
• Pulsford, R. M., Brocklebank, L., Fenton, S. A., Bakker, E., Mielke, G. I., Tsai, L. T., Wei, L., … & Stamatakis, E. (2023). The impact of selected methodological factors on data collection outcomes in observational studies of device-measured physical behaviour in adults: A systematic review. International Journal of Behavioral Nutrition and Physical Activity, 20(1), 26. DOI:10.1186/s12966-022-01388-9