Research

The Dr. Bing Zhang Department of Statistics is home to an exciting and dynamic research environment.   The experience of our established faculty combines seamlessly with the energy and fresh perspectives of our younger faculty, creating a synergy that helps to facilitate the production of high quality, modern research designed to meet the needs and interests of a changing student body and a changing world. While the department retains a strong interest in mathematical statistics, as has been our tradition, most of our faculty are focused on research that is in some way highly computational and outcomes-focused.   

Faculty have access to the College of Arts & Sciences shared cluster, which consists of 4 compute nodes (160 cores) and is on a Dell R640 Server. Each node has 128 GB of 2900 MHz RAM and a 480 GB local SSD and runs Linux OS (CentOS 7). The cluster also houses 2 GPU nodes (24 CPU cores, 11,520 GPU cores) and is on a Dell R730 Server. Each GPU node as 128GB of 2133 MHz RAM and a 300 GB local (internal) SAS disk @ 10K RPM.  In addition, faculty utilize the University of Kentucky’s Lipscomb High Performance Computing cluster.  This is a Dell PowerEdge C6100 Cluster and is rated at just over 140 teraflops. This service provides access to a computing cluster with 376 nodes, 36 GB of memory per node, and 250 TB of global disk space.

Below are the research areas, publication outlets, and funding sources that were documented in our most recent faculty merit review.    

 

 

Represented Research Areas  

Applied Probability

Goodness-of-Fit

Quality Control

Astrostatistics

High-Dimensional Inference

Quantile Regression

Bayesian Modeling

Large Sample Theory

Ranks-Based Methods

Bioinformatics

Linear Models

Reliability Theory

Cardiovascular Health

Longitudinal Data Analysis

Semi-parametric Models

Causal Inference

Microarray Data Analysis

Spatial Statistics

Chemometrics

Mixture Modeling

Statistical Genetics

Clinical Trials

Mixture Models

Survey Data Analysis

Compartmental Models

Model Combining

Survival Analysis

Computational Statistics

Models for Network Data

Time Series

Data Depth

Multivariate Methods

Tolerance Regions

Decision Theory

Nonlinear Models

Variable Selection

Dimension Reduction

Nonparametric Methods

Zero-inflated Models

Disease Clustering

Phylogenetics

 

Econometrics

Predictive Modeling in Big Data

 

Epidemiology

 

 

 

 

 

 

 

Recent Faculty Publication Outlets 

Advances in Data Analysis and Classification

Journal of Neuroscience Methods

Applied Stochastic Models in Business and Industry

Journal of Nonparametric Statistics

Biometrical Journal

Journal of Statistical Computation and Simulation

Cancer Informatics

Journal of Statistical Distributions and Applications

Communications in Statistics

Journal of Statistics

Computational Statistics and Data Analysis

Journal of Statistics Education

Drug and Alcohol Dependence

Journal of the Royal Statistical Society

IEICE, Neurocomputing

Methodology and Computing in Applied Probability

Journal of Alzheimer’s Disease

Neurology

Journal of American Statistical Association

Pharmaceutical Statistics

Journal of Animal Science

Scandinavian Journal of Statistics

Journal of Applied Statistics

Statistica Neerlandica

Journal of Chemometrics

Statistical Methods in Medical Research

 

Statistical Science

 

 

Current or Recent Funding Sources

In FY20: $40,698,748.00 in collaborative funding involved the Dr. Bing Zhang Department of Statistics.  This amounted to more than 36% of all grants and contracts coming to UK that were associated with Arts & Sciences departments, while the department faculty account for less than 4% of all faculty in the college.

American Heart Association

NIH/NHLBI

Carnegie Corporation

NIH/NIA

Centers for Disease Control

NIH/NIAMS

Chan Zuckerberg Initiative

NIH/NIDA

Department of Defense

NIH/NIDDK

KY Cabinet for Health and Family Services

NIH/NIGMS

KY Transportation Cabinet

NIH/NINDS

National Multiple Sclerosis Society

Patient-Centered Outcomes Research Institute (PCORI)

Neilsen Foundation

US Army

NIH/NCRR

US Department of Education

 

 

Our Ph.D. Graduates

A program’s Ph.D. graduates are always a reflection of the faculty that taught them.  You can find completed dissertations at https://uknowledge.uky.edu/statistics_etds/.  Please keep in mind that there is an initial embargo period once a dissertation is completed.

Alumni of our doctoral program are hired immediately upon graduation with a virtually 100% placement rate. They find homes in academics, industry, and government, working to advance methods used within the field of statistics as well as to better the world through using data to improve decision-making.  Our doctoral level graduates hold a variety of positions, including:

  • Endowed Professor and Chair, Department of Biostatistics, University of Kentucky
  • Professor, Department of Statistics and Data Science, Cornell University
  • Associate Professor, South Dakota State University
  • Assistant Professor of Biostatistics and Bioinformatics, Duke University
  • Assistant Professor, Virginia Commonwealth University
  • Assistant Professor, Miami University
  • President of MacroStat, Inc.
  • President of EarlyPhase Sciences
  • Executive Director of Biostatistics – Novartis
  • Owner and Founder, Stat Tenacity Consulting

 

Our faculty and students always have the opportunity to participate in research training from a variety of unique sources.  Here are some of the opportunties that they have now or have just had recently.

 

KBRIN - Applied Statistics Core

The primary goal of the KY INBRE Applied Statistics Core is to improve the breadth and quality of statistical support for scholarship in the KY INBRE Network. Partnering with the University of Kentucky Applied Statistics Laboratory (ASL), statistical support is offered to research staff in the Network.  Multiple students have been trained through this program already. 

 

State University Partnership Program

As part of a funded program entitled “Using Data Science Tools to Analyze Medicaid Claims Data,” faculty are providing data science training for students to analyze large claims data sets. Students will then use this training to complete several summer practicum projects, producing results to inform policy makers.

 

Statistics Undergraduate Research Experience (SURE)

The purpose of SURE was to launch an undergraduate component of the NSF-supported SRCOS Summer Research Conference to encourage STEM majors from under-represented groups to pursue graduate education and career opportunities in the statistical sciences or other STEM fields.  SURE had 37 participants in 2019; more than 60% of these participants were women or were from underrepresented groups.

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