Ruhai Bai, PhD, is a Professor at Nanjing University of Science and Technology, China. His research focuses on population health measurement and social statistical methodology, with particular interests in population ageing, disease burden, health inequality, and health-system planning. He uses large-scale epidemiological, demographic, and social data to examine changes in population health and to provide evidence that may inform public health research, policy discussion, and health-system decision-making. Dr Bai has published more than 50 peer-reviewed academic articles in journals including *The Lancet Public Health*, *The Lancet Regional Health – Western Pacific*, and other international journals. His publications have received 25,019 citations, with an H-index of 32. Several of his studies have addressed important issues related to life expectancy, non-communicable diseases, disability, population ageing, and inequalities in health. He has also received several academic recognitions, including inclusion among the world’s top 2% scientists. In addition to his research work, Dr Bai contributes to the academic community and scientific publishing. He serves as a member of a World Health Organization technical advisory group, Associate Editor of *Population Health Metrics*, and Editorial Board Member of *BMC Medicine*. He has also served as a reviewer for academic journals in public health, medicine, epidemiology, and population studies, contributing to the assessment and improvement of scholarly manuscripts. His long-term research interests include population health measurement, disease burden assessment, healthy ageing, health inequality, and health-system planning, particularly in the context of demographic transition and the increasing burden of chronic diseases. Through his research, he aims to develop and apply quantitative methods that can help describe population health patterns, identify vulnerable groups, and support evidence-informed planning. Dr Bai has expertise in epidemiological analysis, statistical modelling, disease burden estimation, health inequality assessment, scientific writing, and interdisciplinary collaboration. He also values active listening, clear communication, mentoring, teamwork, leadership, management, and problem-solving in academic and professional settings. Outside his professional work, he enjoys reading, academic exchange, and exploring new ideas across public health, social science, and technology.