International Summer School on Health Medical Big Data and Intelligent Statistics
Sun Yat-sen University
Shenzhen campus, 2026

Prof. Siyang Liu received her M.Sc. and Ph.D. in Bioinformatics from the University of Copenhagen. Before joining Sun Yat-sen University in 2021, she was a Senior Bioinformatics Engineer and Research Scientist at BGI. Her research focuses on developing and applying big data analytics, statistical genetics, and bioinformatics techniques to elucidate disease mechanisms and advance therapeutic discovery. She has led several research projects funded by the National Natural Science Foundation of China (NSFC) and the Danish Innovation Fund (Innovationsfonden). As a (co-)first or corresponding author, her work has been published in prestigious journals such as Cell, Nature, Blood, Journal of Hepatology and Nature Communications.
Further details about her recent research can be found in https://liusylab.org/ .

Professor at the University of Copenhagen, specializing in statistical models for applied population and medical genetics. I have a highly interdisciplinary background, holding a Ph.D. from the Department of Biostatistics, a master's degree from the Bioinformatics Center, and a bachelor's degree in Molecular Biology. In addition, I spent two years studying mathematics and over a year working on disease mapping at the Steno Diabetes Center. During my Ph.D. and postdoctoral research, I spent a couple of years at UC Berkeley in the United States and a few months at deCODE Genetics in Iceland.
My primary research focus in recent years has been the development of methods for high-throughput sequencing (HTS) data, particularly for low-depth sequencing, as well as large-scale association mapping studies using both microarrays and HTS data.

Prof. Miguel Rentería leads the Computational Neurogenomics Laboratory in the Brain and Mental Health Program at QIMR Berghofer Medical Research Institute. He also holds appointments as an Honorary Associate Professor at the University of Queensland and as an Adjunct Associate Professor at the Queensland University of Technology. He completed a PhD in Human Genetics at the University of Queensland and undertook postdoctoral training in the Department of Neurology at Brigham and Women's Hospital and Harvard Medical School. He has authored more than 135 peer-reviewed publications in leading journals—including Nature, Cell, Nature Genetics, Nature Communications, BRAIN, SLEEP, and NeuroImage—which have accumulated approximately 13,000 citations, resulting in an h-index of 42. This impactful output has placed him in the Stanford–Elsevier ranking of the world's top 2% most-cited scientists. In recent years, his lab works at the intersection of human genetics, computational biology, and digital health to understand what makes individuals susceptible to neuropsychiatric and neurodegenerative diseases — particularly Parkinson's disease, sleep disorders, depression, dementia, and self-harm behaviours.

Dr Jue-Sheng Ong is a disease-agnostic genetic data scientist and research entrepreneur, and Team Head of the newly established Global Precision Health Lab at QIMR Berghofer Medical Research Institute. He earned his PhD in Statistical Genetics from the University of Queensland in 2019 and built his career at QIMR Berghofer, joining in 2015 and serving as a postdoctoral researcher until 2024. His early potential was recognised through an NHMRC Investigator Grant (EL1) and the QIMR Berghofer Postdoctoral Prize in 2023. He also holds an Executive MBA from Quantic School of Business and Technology, which he pursued specifically to strengthen his work in research commercialisation. Beyond his academic research, Dr Ong works actively at the interface of science, industry, and policy across Australia and Southeast Asia: he holds advisory roles with genomics ventures in Malaysia, collaborates with partners including the Sarawak Infectious Disease Centre (SIDC), builds capacity-building programs with public and private universities in Malaysia, and has hands-on experience designing and scaling biobank data infrastructure for diverse and under-represented populations. His work integrates deep technical expertise, translational and commercial acumen, and a mission-driven approach to advancing precision health and global health equity.
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