The 13th Conference of the IASC-ARS

Keynote speakers

1. Prof. Chun-houh Chen, Academia Sinica, Taiwan

Chun-houh Chen earned his Ph.D. in Mathematics in 1992 from the University of California, Los Angeles (UCLA). His expertise spans multivariate statistical methods, exploratory data analysis (EDA), data/information/matrix visualization, dimension reduction, machine/deep learning, biobanking,bioinformatics, and precision/smart health.

Dr. Chen has held various academic positions, including assistant professor in the Department of Statistics/Computer and Information Systems at George Washington University (1992-1993), Assistant Research Fellow (1993-2002), Associate Research Fellow (2002-2011), and Research Fellow (2011-) at the Institute of Statistical Science, Academia Sinica, Taiwan. He served as Chairperson of the Asian Regional Section (ARS) of the International Association for Statistical computation (IASC) (2013-2015),was a Council member of the International Statistical Institute (ISI) (2015-2019), and is the current president of the IASC (2023-2025). One of Dr. Chen's significant contributions is the development of the Generalized Association Plots (GAP) series of matrix visualization methods and software. These tools are crucial for visualizing continuous, binary, ordinal, categorical, symbolic, and cartographic data with high-dimensional/large sample structures in the field of EDA. Recently, Dr. Chen has focused on precision and smart health-related research, leading related research and application programs at Academia Sinica in collaboration with academic and medical communities.

Dr. Chen is also actively involved in academic administrative services in Taiwan. He served as president of the Chinese Institute of Probability and Statistics (2013-2016), director of the Academic Affairs and Instrument Services, Academia Sinica (2016-2017), director of the Institute of Statistical Science (2017- 2023), and co-convener of the Data Science Degree Program jointly organized by Academia Sinica and National Taiwan University (2017-2023). Additionally, he has been a co-PI responsible for Informatics in the Taiwan Biobank (2018-2022) and a co-PI of the Taiwan Precision Medicine Initiative (TPMI) (2019-). Currently, he holds the positions of Deputy Secretary-General of Academia Sinica (2023-) and President of the Chinese Statistical Association, Taiwan (2023-2026).
https://gap.stat.sinica.edu.tw/Chunhouh/index.htm

2. Prof. Jianqing Fan, Princeton University, USA

Jianqing Fan, Academician of Academia Sinica and Foreign member of the Royal Flemish Academy of Science, is Frederick L. Moore '18 Professor of Finance, Professor of Statistics and Machine Learning, and former Chairman of the Department of Operations Research and Financial Engineering at Princeton University, where he directs both the financial econometrics lab and statistics lab. He previously held professorships at UNC-Chapel Hill, and UCLA. He has authored or co-authored over 300 articles on financial econometrics, statistical machine learning, analysis of Big Data, and various aspects of theoretical and methodological statistics and machine learning. His finance work focuses on the analysis of high-frequency data, empirical asset pricing, option pricing, portfolio theory, risk assessment, high-dimensional data, and time series. He is a joint-editor of Journal of American Statistical Association, and was the joint-editor of Journal of Business and Economics Statistics, Journal of Econometrics, and Annals of Statistics, and has served as associate editor of Econometrica, Management Science, and Journal of Financial Econometrics. His published work has been recognized by the 2000 COPSS Presidents’ Award, the 2007 Morningside Gold Medal of Applied Mathematics, Guggenheim Fellowship in 2009, P.L. Hsu prize in 2013, Guy Medal in Silver in 2014, Noether Distinguished Scholar Award in 2018, and IMS Le Cam Award and Lecture in 2021. He is an Elected Fellow of the American Association for Advancement of Science, the Society of Financial Econometrics, the Institute of Mathematical Statistics, and the American Statistical Association, and a past President of the Institute of Mathematical Statistics.

3. Assoc. Prof. Tran Minh Ngoc, University of Sydney Business School, Australia

Minh-Ngoc is an Associate Professor in the Discipline of Business Analytics at the University of Sydney Business School and a Chief Investigator at the ARC Centre for Data Analytics for Resources and Environment. He earned his BSc and MSc in Mathematics from Vietnam National University, Hanoi, and completed his PhD in Statistics at the National University of Singapore in 2012.
In 2021, Minh-Ngoc was recognized by The Australian newspaper as Australia’s top researcher in "Probability and Statistics with applications”. His expertise lies in statistical methodologies, with a primary research focus on Bayesian computation and statistical machine learning, particularly Variational Bayes inference. He is also pioneering the integration of state-of-the-art quantum computation techniques into data analysis. Additionally, he applies modern Bayesian computation techniques to Cognitive Science, Consumer Behaviour, and Financial Econometrics.
Minh-Ngoc’s research has received significant national and international recognition, with publications in leading statistical journals, psychology and AI conferences. His work has secured over $1 million in research funding, including three highly competitive Australian Research Council grants. He is frequently invited to speak at national and international conferences.
As an educator, Minh-Ngoc is passionate about teaching. His research-led and student-focused approach has resulted in a positive learning experience for students and consistently strong teaching feedback. He has played a key role in developing the Business Analytics and Data Science for Business curricula at the University of Sydney Business School.
https://sites.google.com/site/mntran26/home