R, WinBugs, OpenBugs, STAN, SAS

JUN ZHANG

**** ********** *****

Durham, NC *****7

Phone: 832-***-****

Email: ac4c9y@r.postjobfree.com; ac4c9y@r.postjobfree.com

EDUCATION

Ph.D. visiting student, Duke Clinical Research Institute, Duke University, Durham, NC.

Ph.D. student, Biostatistics, University of Texas Health Science Center, Houston, TX.

M.S., Biostatistics, University of North Texas Health Science Center, Fort Worth, TX.

M.S., Financial Mathematics, Florida State University, Tallahassee, FL.

B.S., Chemical Engineering, Dong Hua University, Shanghai, China

PROFESSIONAL EXPERIENCE

2017-Present

Graduate Assistant, Duke Clinical Research Institute, Durham, NC

Provided statistical analysis, joint modeling, multidimensional latent variable modeling, conducted statistical programming & computation.

Conducted parallel computing on clusters.

Drafted manuscript for the new findings using new statistical approaches.

2017-present

Intern, HRL Laboratories LLC, Malibu, CA.

Conducted Bayesian Computations in modeling spiking Neurons.

Designed applicable Gibbs sampling process.

Conducted simulations to mimic targeted process.

2013-2017

Graduate Research Assistant, University of Texas Health Science Center, Houston, TX

Developed Bayesian based joint modeling framework to conduct statistical computing and analysis.

Conducted statistical analysis in the areas of regression models, mixed effect models, hierarchical models, survival analysis, ordinal logistic analysis, and missing data. Used latent variable models to link unobserved disease features.

Designed and conducted simulations to test models, run extensive simulations on Super Computer (TACC), consolidated the results, made comparison between models.

Worked with MDs to prepare and review statistical methods, ensured the quality and integrity of data, and provided data visualization.

Designed working statistical methods to conduct EMR data mining to find effective drugs and treatments. Used ICD-9 to derive disease data. Implemented penalized cox model to test hundreds of drugs for different types of cancer based on big observational data.

Utilized clinical trial data, conducted longitudinal, multivariate analysis, ordinal response analysis, logistic analysis and mixed effect study to assess the treatment effect. Joint analysis the longitudinal outcomes and survival outcomes, identified the time-dependent disease progression, and evaluated the impairment of disease.

Based on hourly touch phone data to build predictive model, providing early warning signals for disease.

Prepared manuscript for new research and methodology.

Generated interactive plots to interpret statistical concepts to students.

Used nonparametric methods to build approaches and algorithms to analyze nonlinear disease progression and its impact on failure times. Extended the nonparametric approach to model competing risks

2011-2013

Graduate Assistant, University of North Texas Health Science Center, Fort Worth, TX.

Analyzed clinical trial data based on Bayesian design.

Provided survey sampling consultant.

Led a group to prepare the Asthma section of the Community-wide Children’s health Assessment & Planning Survey.

Combined and verify data from various sources.

Prepared study protocol and documentation for IRB.

Designed and provided statistical analysis to assess the ongoing wellness program.

Conducted population based Metabolic Syndrome study based on NHANES’ survey data.

Developed statistical models and generate graphs using R.

Provided training workshop for SPSS, designed online tutorial module.

Provided statistical consulting.

PUBLICATIONS & PRESENTATIONS

Poster Presentation: Joint modeling of multiple longitudinal ordinal outcomes and competing risks: an application to Parkinson's Disease study, JSM 2017, Baltimore, MD

Poster Presentation: Bayesian analysis of multiple longitudinal outcomes of mixed types with nonparametric treatment effects. ENAR, March 2017, Washington, DC.

Ramphal, L., Zhang, J., & Suzuki, S. (2014). A cohort analysis of cardiovascular risk factors in employees of a pediatric hospital wellness program from 2009-2012. Baylor University Medical Center Proceedings, 27(2):1-4

Suzuki, S., Chen, S., & Zhang, J. (2012). Bayesian two-stage sequential design for Phase II clinical trials. Paper presented at the Joint Statistical Meeting, July 28-August 2, 2012, San Diego, CA.

CERTIFICATES & CREDENTIALS

Certified SAS Advanced Programmer

Certified in Public Health

TECHNICAL SKILLS & TRANINING

SAS, SAS Macro, STATA, R, C++, SQL, LaTex, Access, Excel, WinBugs, OpenBugs, Stan, Python, Machine Learning.

PROFESSIONAL MEMBERSHIPS

American Mathematical Society

Pi Mu Epsilon Society

American Statistical Association

Contact this candidate