A photo of Bin Huang.

Bin Huang, PhD


  • Biostatistician, Division of Biostatistics and Epidemiology
  • Professor, UC Department of Pediatrics
  • UC Department of Environmental Health; UC Department of Mathematical Sciences

About

Biography

I’m a biostatistician and researcher focused on patient-centered comparative effectiveness research. I apply and develop principled and advanced causal inference methodology centered around Patient-Centered Adaptive Treatment Strategies (PCATS). I aim to find better treatment and preventive approaches by learning from existing data. Our PCATS lab has been improving treatment strategies for patients with chronic and prolonged conditions, for whom treatment strategies need to be adaptively managed. We have also been working on validating and improving data analytical methodologies to understand the effectiveness of PCATS by utilizing existing data.

My career journey started as a biostatistician participating in research programs at Cincinnati Children’s. From there, culture influenced me to pursue excellence at Cincinnati Children’s and the passion for improving health outcomes and providing equitable healthcare with those with whom I collaborate. I’m driven and passionate about discovering what works and doesn’t work for patients by providing robust and reliable evidence to inform better approaches to improve health outcomes and reduce health disparity in children. This has been the driving force behind the evolution of my research program.

With colleagues and team members, we have contributed to the methodological literature by improving the robust Bayesian Gaussian Process and Bayesian Additive Regression Tree for causal inference to handle time-varying adaptive treatment strategies, missing data and heterogeneous treatment effects. With the PCATS team, we have publicly made advanced Bayesian causal inference methods available and provided an application program interface (API) callable from R and Python.

With clinician-researchers, we have advanced the field by providing comparative effectiveness evidence in treating children with newly diagnosed juvenile idiopathic arthritis (JIA), in caring for children in need of heart transplantation, in helping young athletes recovering after anterior cruciate ligament (ACL) reconstructive surgery, in understanding mechanisms underlying health inequality, and in advancing equitable healthcare by providing novel intervention programs to those in needs.

I was honored to have authored a Wiley Top Cited Article (2023) in Pediatric Transplantation and to be named Top Reviewer for the Journal of Hospital Medicine (2023). I’m also an elected member (2016) of the International Statistics Institute (ISI). I have been a researcher for more than 30 years and began working at Cincinnati Children’s in 1999. I’m passionate about fostering the next generation of data scientists and interdisciplinary researchers.

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

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

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

Interests

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

Research Areas

Biostatistics and Epidemiology

Publications

Selected

Bayesian causal inference for observational studies with missingness in covariates and outcomes. Zang, H; Kim, HJ; Huang, B; Szczesniak, R. Biometrics. 2023; 79:3624-3636.

Selected

Garnering effective telehealth to help optimize multidisciplinary team engagement (GET2HOME) for children with medical complexity: Protocol for a pragmatic randomized control trial. Warniment, A; Sauers-Ford, H; Brady, PW; Beck, AF; Callahan, SR; Giambra, BK; Herzog, D; Huang, B; Loechtenfeldt, A; Loechtenfeldt, L; Sucharew, HJ; Tegtmeyer, K; Thomson, JE; Auger, KA. Journal of hospital medicine (Online). 2023; 18:877-887.

Selected

An application programming interface implementing Bayesian approaches for evaluating effect of time-varying treatment with R and Python. Chen, C; Huang, B; Kouril, M; Liu, J; Kim, H; Sivaganisan, S; Welge, JA; DelBello, MP. Frontiers in Computer Science. 2023; 5:1183380.

Selected

Metformin for Overweight and Obese Children With Bipolar Spectrum Disorders Treated With Second-Generation Antipsychotics (MOBILITY): Protocol and Methodological Considerations for a Large Pragmatic Randomized Clinical Trial. Welge, JA; Correll, CU; Sorter, MT; Fornari, VM; Blom, TJ; Carle, AC; Huang, B; Klein, CC; DelBello, MP. 2023; 1:60-73.

Selected

GPMatch: A Bayesian causal inference approach using Gaussian process covariance function as a matching tool. Huang, B; Chen, C; Liu, J; Sivaganisan, S. Frontiers in Applied Mathematics and Statistics. 2023; 9:1122114.

Selected

Effect of ischemic time on pediatric heart transplantation outcomes: is it the same for all allografts?. Dani, A; Vu, Q; Thangappan, K; Huang, B; Wittekind, S; Lorts, A; Chin, C; Morales, DL S; Zafar, F. Pediatric Transplantation. 2022; 26:e14259.

Selected

Dexamethasone Versus Prednisone in Children Hospitalized With Asthma Exacerbation. Hoefgen, ER; Huang, B; Schuler, CL; Kercsmar, CM; Murtagh-Kurowski, E; Forton, M; Auger, KA. Hospital Pediatrics. 2022; 12:325-335.

Selected

Reductions In Hospitalizations Among Children Referred To A Primary Care-Based Medical-Legal Partnership. Beck, AF; Henize, AW; Qiu, T; Huang, B; Zhang, Y; Klein, MD; Parrish, D; Fink, EE; Kahn, RS. Health Affairs. 2022; 41:341-349.

Selected

Comparative effectiveness and persistence of TNFi and non-TNFi in juvenile idiopathic arthritis: a large paediatric rheumatology centre in the USA. Yue, X; Huang, B; Hincapie, AL; Wigle, PR; Li, Y; Qiu, T; Lovell, DJ; Morgan, EM; Guo, JJ. Rheumatology. 2021; 60:4063-4073.

Selected

Subgroup causal effect identification and estimation via matching tree. Zhang, Y; Schnell, P; Song, C; Huang, B; Lu, B. Computational Statistics and Data Analysis. 2021; 159:107188.

View All Publications in Google Scholar