BIO Asia–Taiwan 2021 亞洲生技大會

BIO Asia–Taiwan 2021 亞洲生技大會


Kung-Yee Liang

Session 4 – Data-driven Precision Health

Date:21 July (Wednesday)
Time:  15:40 – 17:10 (GMT+8)

Kung-Yee Liang

National Health Research Institutes


Kung-Yee Liang received his Ph.D. in Biostatistics from University of Washington in 1982 and has been a faculty member at the Department of Biostatistics, Johns Hopkins University since then for 28 years.  He served as the Graduate Program Director for the department from 1996 to 2003.
Liang has served as the Vice President, National Health Research Institutes (NHRI), Taiwan from July, 2003 to August, 2006 and was the Acting President for six months beginning in January, 2006.
In August, 2010, Liang became the sixth President of the National Yang-Ming University, the first medical university in Taiwan. In December, 2017, Liang stepped down from the post to become the sixth President of NHRI and his primary appointment is with the Institute of Population Health Science.
Among the honors and awards, Liang received the Snedecor Award (with Scott Zeger) in 1987 by the American Statistical Association for best publication in biometry for 1986, the Spiegelman Award by the American Public Health Association in 1990 for outstanding accomplishments in the field of health statistics, the Rema Lapouse Award by the American Public Health Association in 2010 for significant contributions to the scientific understanding of the epidemiology and control of mental disorders, the Karl Pearson Prize (with Scott Zeger) in 2015 by the International Statistical Institute for contemporary research contribution that has had profound influence on statistical theory, methodology, practice, and/or applications, and the Heritage Award in 2016 by the Johns Hopkins Alumni Association for outstanding service to the progress of the University over an extended period of time. Liang is an Elected Fellow of the American Statistical Association in 1995, an Elected Academician, Academia Sinica, Taiwan in 2002, an Elected Member, Academy of Sciences for the Developing World (TWAS) in 2012, an Elected Member, the National Academy of Medicine, USA in 2015 and an Elected Member, Johns Hopkins Society of Scholars in 2016.  In 2020, Liang was one of the 50 alumni from around the world recognized as changemakers for their distinguished service and achievement across public health disciplines and settings in celebration of University of Washington School of Public Health’s 50th anniversary.
Liang’s research interest has primarily been on developing new statistical methods for analyzing correlated data derived from longitudinal and genetic epidemiological studies, and on developing statistical theory for inference in the presence of nuisance parameters. Liang is a co-author of the book on “Analysis of Longitudinal Data”, published by the Oxford University Press in 1994 and in 2002 (2nd edition). He is also the author of the monography on “Generalized Linear Models, Estimating Equations and Multivariate Extensions”, published by the Institute of Statistical Science, Academia Sinica in 1999, as a part of the Invited Lecture Series in Statistical Science.  

Speech title & Synopsis

Current Advances in Precision Health in Taiwan

By 2025, Taiwan will be facing serious health crises including becoming super aging society, increasing health expenditure due to rise in chronic diseases and disparity in rural areas. In this talk, we first examine some global trends leading to the current interest in precision health of all ages, which we will elaborate. We then focus on some recent developments in Taiwan pertained to precision health: (1) constructing of conceptual framework in precision health and welfare, (2) Establishing the National Biobank Consortium, (3) Initiating the multi-governmental “Health Big Data Platform Program” and (4) Building the “Service Window” for health big data. These components serve as the fundamental infra-structures for the implementation of precision health in Taiwan. We end with a brief discussion concerning the challenges to face with.