Statistics and Probability
Statistics research at the Department focuses on the broad areas of simultaneous inference, analysis of nonEuclidean data, analysis of categorical data, Bayesian modeling, objectoriented data analysis, spatial data analysis, and inference under dynamic parametric models. These include more specific areas of interest such as control and estimation of the false discovery rate, statistical modeling of data on the sphere, statistical analysis of trees, images, and functional data, empirical studies of machine learning models, and changepoint analysis under fixed dimensions as well as high dimensions. Statistics faculty members at the Department often conduct research in collaboration within the Department and with the School of Food Science, Department of Pharmaceutical Sciences, School of Materials Sciences and Mechanical Engineering, College of Veterinary Medicine, Department of Engineering and Computer Science, and Department of Management, Information systems, and Entrepreneurship.
Chencheng Cai
https://www.math.wsu.edu/faculty/ccai chencheng.cai@wsu.edu Neill 405 Causal inference and experimental design under interference; Time series analysis; highdimensional matrix decomposition; Monte Carlo methods. Statistics and Probability Data Analytics Probability and Stochastic Processes 
Optimizing Randomized and Deterministic Saturation Designs under Interference KoPA: Automated Kronecker Product Approximation 
Xiongzhi Chen
http://math.wsu.edu/faculty/xchen/ xiongzhi.chen@wsu.edu Neill 230 Simultaneous inference, theoretical foundation of analysis of nonEuclidean data and of deep learning models, statistics of stochastic differential equations, and harmonic analysis. Applied Mathematics Statistics and Probability Probability and Stochastic Processes 
Uniformly consistently estimating the proportion of false null hypotheses via Lebesgue–Stieltjes integral equations A weighted FDR procedure under discrete and heterogeneous null distributions 
Nairanjana Dasgupta
http://www.math.wsu.edu/faculty/ndasgupta/ dasgupta@wsu.edu Neill 403 Genomics and Bioinformatics. Dealing with large scale multiplicity in genomic, proteomic and metabolomic data sets. Dealing with dependencies in binary and ordinal data. Modeling growth and bloom phases of WA apples. Multiple Comparisons, Comparison to Control, Logistic Distribution, Optimal Designs. Statistics and Probability Biostatistics Data Analytics 

Daryl DeFord
http://www.math.wsu.edu/faculty/ddeford/ daryl.deford@wsu.edu Neill 328 My research focuses on applications of combinatorial and algebraic methods to the analysis of social data including political redistricting and social network analysis. Recent projects include the following with more details on Applied Mathematics Statistics and Probability Pure Mathematics Data Analytics Probability and Stochastic Processes Number Theory and Combinatorics 
Maximum a Posteriori Inference of Random Dot Product Graphs via Conic Programming ReCombination: A family of Markov Chains for Redistricting 
Krishna (Assoc Chair) Jandhyala
http://www.math.wsu.edu/faculty/jand/ jandhyala@wsu.edu Neill 407 The problem of multiple changepoints in timeseries with applications to environmental data. Statistics and Probability Probability and Stochastic Processes 

Dean/Harry Johnson
http://www.math.wsu.edu/faculty/djohnson/ dean_johnson@wsu.edu Neill 414 Statistical Consulting and Statistics Education Statistics and Probability 
Factors Relating to the Degree to Which Statistical Consulting Clients Deem Their Consulting Experiences to be a Success Traditional versus Nontraditional Teaching: Perspectives of Students in Introductory Statistics Classes 
Bala Krishnamoorthy
http://www.math.wsu.edu/faculty/bkrishna/ kbala@wsu.edu Vanc Applied algebraic topology, Geometric measure theory,Mathematical aspects of 3D printing,Discrete and nonlinear optimization,Geometry and topology in physical chemistry,Computational models for surgical and biomedical applications,Computational biology. Applied Mathematics Statistics and Probability Mathematical Biology Optimization and Data Analytics Data Analytics Probability and Stochastic Processes Analysis and PDEs Geometry and Topology 
Optimal homology and linear programming Continuous toolpath planning in 3D printing 
Sergey Lapin
http://www.math.wsu.edu/faculty/slapin/ slapin@wsu.edu Evrt 405 Numerical modeling of biological fluids, fluidstructure interaction problems Applied Mathematics Statistics and Probability Mathematics Education Mathematical Biology Fluid and Solid Mechanics Data Analytics 
Waveform parameters of retrobulbar vessels in glaucoma patients with different demographics and disease severity Modeling Refugee Movement Based on a Continuum Mechanics Phase  Field Approach of Porous Media 
Haijun Li
http://www.math.wsu.edu/math/faculty/lih/ liklu@wsu.edu Neill 317 Copula Theory for Multivariate Extremes, Risk and Choquet Capacities, Free Probability under GroupInvariance Statistics and Probability Pure Mathematics Mathematical Finance Probability and Stochastic Processes 
Tail dependence functions and vine copulas Orthant tail dependence of multivariate extreme value distributions 
Xueying/Snow Wang
http://www.math.wsu.edu/faculty/xueying/ xueying.wang@wsu.edu Neill 201 Integrating techniques from the fields of dynamical systems, stochastic processes and statistics to develop and analyze mathematical models. Application areas: (a) computational neuroscience; (b) infectious disease modeling; (c) population ecology. Applied Mathematics Statistics and Probability Mathematical Biology Optimization and Data Analytics Probability and Stochastic Processes Analysis and PDEs 
A reactionadvectiondiffusion model of cholera epidemics with seasonality and human behavior change Patterns of synchronization in 2D networks of inhibitory neurons 
Yuan Wang
http://www.math.wsu.edu/faculty/ywang/ yuan.wang@wsu.edu Neill 409 ObjectedOriented Data Analysis, Bayesian Statistics, Nonparametric methods, classification and clustering analysis Statistics and Probability Bayesian Inference Biostatistics Data Analytics 
Nonparametric Regression Model with Treestructured Response Functional Model for Classification of Correlated Objects 