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	Epidemiology	Quality Control
Astrostatistics	Goodness-of-Fit	Quantile Regression
Bayesian Modeling	High-Dimensional Inference	Ranks-Based Methods
Bioinformatics	Large Sample Theory	Reliability Theory
Cardiovascular Health	Linear Models	Semi-parametric Models
Causal Inference	Longitudinal Data Analysis	Spatial Statistics
Chemometrics	Machine Learning	Statistical Genetics
Clinical Trials	Microarray Data Analysis	Survey Data Analysis
Compartmental Models	Mixture Models	Survival Analysis
Computational Statistics	Model Combining	Time Series
Data Depth	Models for Network Data	Tolerance Regions
Data Science	Multivariate Methods	Uncertainty Quantification (UQ)
Decision Theory	Nonlinear Models	Variable Selection
Dimension Reduction	Nonparametric Methods	Zero-inflated Models
Disease Clustering	Phylogenetics
Econometrics	Predictive Modeling in Big Data

 

 

 

 

 

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 the 2019-2020 fiscal year, $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.