Mathematics and Statistics Research

• Research interests: mathematical modeling, optimization, calculus of variations
• Kinetic Monte Carlo modeling on organic solar cells: Domain size, donor-acceptor ratio and thickness
• Optimization of virotherapy for cancer
• The inverse problem of the calculus of variations for systems of second-order partial differential equations in the plane

Google Scholar - Fred Boehm

• Research interests: biostatistics, with a focus in statistical genetics
• Frederick Boehm - GitHub

• Research interests: predictive analytics, financial statistics
• A Credit Evolution, Applied Stochastic Models in Business and Industry

Google Scholar - Gemechis Djira

• Research interests: simultaneous inferences, bioassays, longitudinal data analysis, statistical computing, Bayesian analysis, sequential methods
• Multiple Comparisons of Parametric Models and in Longitudinal Studies (with Ramu Sudhagoni)
• Relative Potency Estimation in Parallel-Line Assays

Google Scholar - Xijin Ge

• Research interests: bioinformatics, genomics and cancer
• Interpreting expression profiles of cancers by genome-wide survey of breadth of expression in normal tissues
• The MicroArray Quality Control (MAQC)-II Study
• Reducing False Positives in Molecular Pattern Recognition

Google Scholar - Jung-Han Kimn

• Research interests: efficient parallel algorithm based on domain decompositions: mathematical analysis and practical implementation
• A convergence theory for an overlapping Schwarz algorithm using discontinuous iterates
• Restricted overlapping balancing domain decomposition methods and restricted coarse problems for the Helmholtz problem
• Numerical implementation of overlapping balancing domain decomposition methods on unstructured meshes
• A numerical approach to space-time finite elements for the wave equation

Google Scholar - Semhar Michael

• Research interests: computational statistics with a focus on finite mixture modeling and model-based clustering
• Studying complexity of model-based clustering
• Semi-supervised model-based clustering with positive and negative constraints
• Recent developments in model-based clustering with applications

Google Scholar - Hossein Moradi

• Research interests: big Data, dimension reduction and variable selection, functional data analysis, multivariate statistics, spatial and spatiotemporal statistics
• Response envelopes for linear coregionalization models
• New Parsimonious Multivariate Spatial Model: Spatial Envelope
• A Bayesian multivariate functional model with spatially varying coefficient approach for modeling hurricane track data
• Robust estimation and variable selection in sufficient dimension reduction

Google Scholar - Michael Puthawala

• Research interests: machine learning: manifold learning, geometric learning, universality; math/applied math: inverse problems, scientific computing, optimal transport
• Deep Invertible Approximation of Topologically Rich Maps between Manifolds
• Universal Joint Approximation of Manifolds and Densities by Simple Injective Flows
• Globally Injective ReLU Networks

Google Scholar - Chris Saunderrs

• Research interests: forensic inference of source, statistical pattern recognition and approximation theory
• Construction and Evaluation of Classifiers for Forensic Document Analysis
• Using Automated Comparisons to Quantify Handwriting Individuality
• A novel application of quantile regression for identification of biomarkers exemplified by equine cartilage microarray data

• Research interests: combinatorics, Ramsey theory on the real numbers
• A zero-sum theorem
• Disjunctive Rado numbers
• On a Variation of Schur Numbers
• Off-Diagonal Generalized Schur Numbers

Google Scholar - Don Vestal

• Research interests: number theory and combinatorics (especially Ramsey theory)
• Construction of Weight Two Eigenforms Via the Generalized Dedekind Eta Function
• The Discrete Rado number for x₁+x₂+...+x_m+c=2x₀

Google Scholar - Sharon Vestal

• Research interests: analyzing and Improving student performance in calculus courses, abstract harmonic analysis and wavelet theory
• Orthonormal wavelets and shift invariant generalized multiresolution analyses
• Improving student success in Calculus 1 using a co-requisite calculus 1 lab

• Vahid Hosseinzadeh – working with Michael Puthawala
  • The intersection of geometric deep learning and power systems stability
• Cole Patten – working with Michael Puthawala and Chris Saunders
  • Contrastive Learning, with Application to Forensic Identification of Source
• Cole Rausch – working with Michael Puthawala

  • Stability of Inverses of Relu Activation Layers in Deep Neural Networks

     

• Emma Brookman (M.S., 2025): Association Between Water Pollution and Other Environmental Factor Exposures with Preterm Births and Potential Subsequent Birth Defects
• Eleanor Cain (M.S., 2025): An Extension of the Spatiotemporal Change of Support Model to Skew-Gaussian Distributions
• Annamarie Dobbs (M.S., 2025): Thinking in Ink: How Notetaking Adapts in a Thinking Classroom
• Nathan Meyer (M.S., 2025): Developing Proportional Hazards Mixture Cure Models and Predicting Risk for Persons With End-Stage Kidney Disease
• Edwin Mutimba (M.S., 2025): Modeling Area Deprivation Index Using Non-Gaussian Fixed Rank Kriging
• Addy Smith (M.S., 2025): Exploring the Role of Clinical and Social Factors in Predicting All-Cause Mortality in End-Stage Kidney Disease Patients: A Machine Learning Framework
• Anthony Glackin (M.S., 2024): Rado Numbers for Two Systems of Linear Equations
• Cole Patten (M.S., 2024): Contrastive Learning, with Application to Forensic Identification of Source
• Cami Fuglsby (Ph.D., 2023): U-Statistics for Characterizing Forensic Sufficiency Studies
• Rachel Bergjord (M.S., 2023): Some 2-Color Rado Numbers For A Linear Equation With A Negative Constant
• Shi Wen Wong (M.S., 2023): A Study of the Local Deep Galerkin Method for the Modified Cahn Hilliard Equation
• Skylar Halverson (M.S., 2022): Totally Multicolored Rado Numbers For the Equation x₁ + x₂ + x₃ + ... + x_m-1 = x_m
• Stephanie Liebl (M.S., 2022): Using Deep Neural Networks to Analyze Precision Agriculture Data
• Rylee Sundermann (M.S., 2022): Efficient Numerical Optimization for Parallel Dynamic Optimal Power Flow Simulation Using Network Geometry
• Tessa Sundermann (M.S., 2022): The Efficacy of the South Dakota State University Summer Jacks LeaP Program
• Madeline Anne Ausdemore (Ph.D., 2021): Development of a Probabilistic Multi-Class Model Selection Algorithm for High-Dimensional and Complex Data
• Nicholas Brown (Ph.D., 2021): Detailing the Connection Between a Family of Polar Graphs and Tremain Equiangular Tight Frames
• Jessie Hendricks (Ph.D., 2021): Development and Properties of the ROC-ABC Bayes Factor for the Quantification of the Weight of Forensic Evidence
• Paul May (Ph.D., 2021): Methods for High-Dimensional Spatial Data: Dimension Reduction and Covariance Approximation
• Rong Zhou (M.S., 2021): Comparison of Software Packages for Detecting Differentially Expressed Genes from Single-Sample Rna-Seq Data
• Abdelbaset Abdalla (Ph.D., 2019): Finite Mixture of Regression Models for Complex Survey Data
• Shaopeng Gu (M.S., 2019): Applying Machine Learning Algorithms for the Analysis of Biological Sequences and Medical Records
• Amanda Jensen (M.S., 2019): Using Social Network Analysis to Examine the Connections within a Noyce Community’s Facebook Group
• Nicholas Stegmeier (M.S., 2019): A Study of Several Applications of Parallel Computing in the Sciences Using PETSC