Assoc Prof Tai Bee Choo
Assoc Prof Tai Bee Choo
Biostatistician and Clinical Trials ExpertNUS Saw Swee Hock School of Public Health
NUS Yong Loo Lin School of Medicine
Associate Professor Tai is a distinguished biostatistician and clinical trials expert at the National University of Singapore, holding joint appointments at the NUS Saw Swee Hock School of Public Health and the NUS Yong Loo Lin School of Medicine.
With over two decades of experience in medical statistics, Associate Professor Tai has established herself as a leading authority in the design, conduct, and analysis of clinical trials.
Associate Professor Tai's research expertise encompasses critical areas of clinical research methodology, including non-compliance in randomised clinical trials, meta-analysis with trial sequential analysis, and advanced statistical approaches for handling competing risks and non-proportional hazards. Her work has significantly contributed to improving the rigour and reliability of clinical trial evidence.
Academically, Associate Professor Tai brings exceptional credentials to her role, having earned her PhD in Medical Statistics from the prestigious London School of Hygiene & Tropical Medicine, University of London, where she also completed her MSc Medical Statistics with distinction. She holds the distinguished status of Chartered Statistician of the Royal Statistical Society (UK), a recognition she has maintained since 1997.
As an educator, Associate Professor Tai has demonstrated outstanding commitment to training the next generation of biostatisticians and clinical researchers. She teaches both basic and advanced biostatistics as well as clinical trial methodology, and her excellence in education has been recognised with Teaching Excellence Awards from the Saw Swee Hock School of Public Health in both 2015/16 and 2021/22.
Associate Professor Tai’s combination of rigorous academic training, extensive research experience, and proven teaching excellence makes her a highly sought-after speaker on topics related to clinical trials, biostatistics, and evidence-based medicine.