Dr. Menglu Liang | Bayesian methods | Best Researcher Award

Assistant Professor, University of Maryland, United States

Dr. Menglu Liang is an Assistant Professor of Biostatistics at the University of Maryland, with a strong background in biostatistics, epidemiology, and public health. Her journey into the field of biostatistics began during her studies at Johns Hopkins University, where she first encountered survival analysis in large cohort studies. Dr. Liang’s academic and research career has focused on developing advanced statistical models for real-world health challenges, particularly in the areas of cardiovascular disease, cancer, and public health. She has received extensive training at prestigious institutions, including Beijing University of Chinese Medicine, Peking University, Johns Hopkins University, the University of Minnesota, and Penn State University. Her work has resulted in numerous impactful publications in top-tier journals, and she is highly regarded for her interdisciplinary collaborations with clinicians, epidemiologists, and statisticians to address pressing health issues.

Profile

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Education

Dr. Menglu Liang completed her undergraduate studies in Preventive Medicine at Beijing University of Chinese Medicine, graduating in 2011. She further pursued a Master’s degree in Public Health (MPH) from Peking University, Beijing, in 2014. Her passion for applying statistical methods in public health led her to Johns Hopkins University, where she earned a Master of Science in Epidemiology in 2016. Dr. Liang’s academic path continued with a Master of Science in Statistics from the University of Minnesota in 2019, and she earned her PhD in Biostatistics from Penn State University in 2023. Her doctoral research, titled “Modeling and Dynamic Prediction for Recurrent Time-to-event Data with Competing Risks,” focused on advanced Bayesian techniques for survival analysis and statistical modeling. Dr. Liang’s education across multiple disciplines and prestigious institutions has provided her with a comprehensive foundation in biostatistics, epidemiology, and public health.

Experience

Dr. Menglu Liang has built an impressive academic and professional career, culminating in her current position as an Assistant Clinical Professor of Biostatistics at the University of Maryland. Prior to this, she gained invaluable experience as a Graduate Assistant at Penn State University (2019–2023) and the University of Minnesota (2018–2019), where she developed advanced statistical models and conducted research on cardiovascular disease and clinical epidemiology. Dr. Liang’s early career included roles at Johns Hopkins University, where she worked as a Data Analyst (2016–2017) and a Graduate Assistant (2015–2016), contributing to significant research in epidemiology and biostatistics. Throughout her career, she has demonstrated a commitment to collaborative research and statistical consulting, working closely with clinicians and researchers to tackle complex health issues. Dr. Liang has also served as a mentor to students and researchers, providing guidance in statistical modeling, data analysis, and scientific writing.

Awards and Honors

Dr. Menglu Liang has received numerous awards and honors that recognize her outstanding contributions to biostatistics and public health research. In 2022, she was awarded the prestigious Travel Award by the International Chinese Statistical Association, highlighting her commitment to advancing statistical methods in health research. She was also the recipient of the Statistical Significance Award in the JSM Statistical Significance Competition, which acknowledges innovative research in statistical methodology. Dr. Liang’s scholarly achievements have been recognized through her publications in top-tier journals, where her work on dynamic prediction models and Bayesian statistical methods has garnered significant attention. She has presented her research at various national and international conferences, demonstrating her leadership in advancing the application of statistical techniques to public health and clinical research. Her consistent recognition underscores her academic excellence and her ability to contribute to high-impact research in the field.

Research Focus

Dr. Menglu Liang’s research focuses on the application of advanced statistical methods to public health, epidemiology, and clinical research. Her primary areas of interest include survival analysis, Bayesian hierarchical modeling, and the development of dynamic prediction models for recurrent time-to-event data with competing risks. Her work often integrates complex statistical methods with real-world data to address key health challenges, particularly in cardiovascular disease, cancer, and public health policy. Dr. Liang is particularly interested in the intersection of statistical modeling and clinical research, where she collaborates with clinicians and epidemiologists to improve predictive models and decision-making processes. She has also applied Bayesian network meta-analysis techniques in dental research and developed spatial-temporal models to study the effects of extreme heat on health outcomes. Dr. Liang’s research is driven by the goal of making meaningful contributions to public health through the application of innovative statistical techniques to real-world problems.

Publication Top Notes

1. Association of a Biomarker of Glucose Peaks, 1,5-Anhydroglucitol, With Subclinical Cardiovascular Disease 🩺📊
2. Tackling Dynamic Prediction of Death in Patients with Recurrent Cardiovascular Events 💓🔍
3. Bayesian Network Meta-Analysis of Multiple Outcomes in Dental Research 🦷📈
4. A Spatial-Temporal Bayesian Model for Case-Crossover Design with Application to Extreme Heat and Claims Data 🌡️📉