Bin Huang, PhD

Biostatistician, Division of Biostatistics and Epidemiology

Academic Affiliations

Professor, UC Department of Pediatrics

Affiliated Assistant Professor, Department of Mathematical Sciences, University of Cincinnati A&S College

Phone 513-636-7612

Email bin.huang@cchmc.org

Research

Statistics Causal Inference; Comparative Effectiveness Research (CER); causal mediational analyses; statistics modeling of electronic medical records and clinical registry data

Bin Huang has had more than 15 years research as a biostatistician researcher. Her research has been focused on applying and devising better statistics methodologies for: a) searching for better treatment/preventive strategies; and b) evaluating to what extent health disparities exists, and how the different exposures to biological, social and physical environments may interact with each other leading to the gap. Currently, she is working on evaluating casual inference methods and devising improved methods for conducting comparative effectiveness research (CER) using data collected from electronic health record and multi-center patient registry. Her other research interests include causal mediational and causal mechanisms analyses, and analyses of large observational data.

Dr. Huang has authored and co-authored more than 100 peer-reviewed publications in the health and pediatric care research area. She has been funded as principal investigator, co-investigator and biostatistician on a number of NIH/PCORI and other extramural grants. Dr. Huang is an elected member of International Statistical Association (ISI). She serves on multiple federal governments public advisory committees. She over sees a graduate internship program at the Division of Biostatistics and Epidemiology.

BS: Shanghai Jiao Tong University, Shanghai, China, 1991.

MS: University of Cincinnati, Cincinnati, OH, 1995.

PhD: Environmental Health, University of Cincinnati, Cincinnati, OH, 2000.

View PubMed Publications

Sivaganesan S, Müller P, Huang B. Subgroup finding via Bayesian additive regression trees. Statistics in Medicine. 2017.

Beck AF*, Huang B*, Auger KA, Ryan PH, Chen C, Kahn RS. Explaining Racial Disparities in Child Asthma Readmission Using a Causal Inference Approach. JAMA pediatrics. 2016. (*shared 1st author.) 

Huang B, Giannini EH, Lovell DJ, Ding L, Liu Y, Hashkes PJ. Enhancing crossover trial design for rare disease: limiting ineffective exposure and increasing study power by enabling patient choice to escape early. Contemporary Clinical Trials. 2014 Jul;38(2): 204-212.

Hashkes PJ, Spalding SJ, Giannini EH, Huang B, et al. Rilonacept for Colchicine Resistant for Intolerant Familial Mediterranean Fever: A Randomized Controlled Trial. Annals of Internal Medicine. 2012;157:533-41.

Huang J, Huang B*. Proportion of Treatment Effects Explained by a Continuous Surrogate Marker in Randomized Clinical Trial. Statistics in Pharmaceutical Research. 2010;2(2): 229-238. (*corresponding author).

Huang B, Sivaganasen S, Succop P, Goodman E. Statistical assessment of mediational effects for logistic mediational models. Statistics in Medicine. 2004;23(17):2713-28.

Patient Centered Adaptive Treatment Strategies (PCATS) using Bayesian Causal Inference. Principal Investigator. PCORI / Improving Methods for Conducting Patient-Centered Outcome Research. Sep 2015–Sep 2019.

Assessing Personal Exposure to Ultrafine PM Number and Respiratory Health. Co-investigator. National Institutes of Health/National Institute of Environmental Health Science. Mar 2015-Feb 2020.

Real-time Optimized Biofeedback Utilizing Sport Techniques (ROBUST). Co-investigator. National Institutes of Health/National Institute of Arthritis and Musculoskeletal and Skin Diseases. Apr 2016-Mar 2019.

Epidemiologic Impact of HPV Vaccination. Co-investigator (PI, J Kahn). Jan 2013–Dec 2017.

Inpatient Asthma Care for Children: Adding a Place-Based Community-Focused Approach. Statistics Advisor (PI, Beck). National Institutes of Health. July 2014–June 2019.