Department of Statistics Unitmark
Dietrich College of Humanities and Social Sciences

Thesis Topics

Following is a list of students who recently received their Ph.D. degree from the department and where they were first employed.


Longitudinal Conditionally Independent Dyad Models for Analyzing Networks over Time, Samrachana Adhikari; Department of Health Care Policy and Department of Biostatistics at Harvard Medical School

Methodological Innovations in the Collection and Analysis of Human Rights Violations Data, Jana Asher; American Association for Blood Banks

Statistical Inference using Geometric Features, Yen-Chi Chen; University of Washington

Characteristics of cross-validation methods for model selection in the stochastic block networks, Beau Dabbs; Lawrence Livermore National Laboratory

Constructing Approximately Sufficient ABC Summary Statististics, Michael Vespe; Capital One

Statistical Inference about Functional Connectivity from Multi-Neuron Data, Giuseppe Vinci; Post-doctoral position at Rice University


Clustering Strategies for DNA Genotyping, Gaia Bellone

Statistical Inference for Topological Data Analysis Fabrizio Lecci; New York LIfe Insurance

High Dimensional Sparse Precision Matrix Estimation Shiqiong Huang; Citibank

A Bayesian Partitioning Approach to Duplicate Detection and Record Linkage Mauricio Sadinle; Duke University and the National Institute of Statistical Science

Duration Models, Mingyu Tang; Arxis Capital

Large-Scale Classification and Clustering Methods with Applications in Record Linkage Sam Ventura; Pittsbugh Penquins Hockey

A Method to Exploit the Structure of Genetic Ancestry Spaces to Enhance Case-Control Studies Corneliu Bodea

Network Comparisons Using Sample Splitting, Lawrence Wang;

Nonparametric Techniques for Functional Data Analysis, Mattia Ciollaro:

Understanding the Genetic Basis of Schizophrenia and other Mental Disorders by using RNA-Sequencing Data, Cong Lu; eBay-StubHub


Geometric Approaches to Inference: Non-Euclidean Data and Networks, Dena Asta (joint Statistics and Engineering and Public Policy)

A Statistical Contribution to Historical Linguistics,  Rafael Stern

Computational and Statistical Advances in Testing and Learning Aaditya Ramdas - 2015 (joint Statistics and Machine Learning

Statistical Methods in Diffusion Connectomics Patrick Foley; Stitch Fix

Social Network Modeling and the Evaluation of Structural Similarity for Community Detection, Xiaolin Yang

Scalable Privacy-Preserving Data Sharing Methodologies for Genome-Wide Association Studies Fei Yu; Bell Labs


Classification Via Auxiliary Information, Beatriz Estefania Etchegaray; IBM Research Postdoc

A Spectral Series Approach to High-Dimensional Nonparametric Inference, Rafael Izbicki; Assistant Professor, Dept of Statistics, Federal University of São Carlos, Brazil

Level Set Trees for Applied Statistics, Brian Kent; Dato

Local Log-Linear Models for Capture-Recapture, Zachary Kurtz; Marketing Data Scientist

Statistical Multi-coil MRI Reconstruction, Jionglin Liu; PNC Quantitative Analyst

The Efficacy of the Hedges Correction for Unmodeled Clustering, and Its Generalizations in Practical Settings, Nathan VanHoudnos; Postdoc, Northwestern University

Toward a Processing Pipeline for Two-Photon Calcium Imaging of Neural Populations, Bronwyn Woods; Software Engineering Institute, CMU

A New Parametric Model for the Point Spread Function (PSF) and Its Application to Hubble Space Telescope Data, Lubov Zeifman; University of Alaska

Statistically and computationally efficient inference from multi-neuron spike trains, Sonia Todorova; Google, New York

Spectral-HCT Approach for Clustering Problems in High Dimensional Data, Wanjie Wang; Post Doc, University of Pennsylvania

High Dimensional Statistical Analysis to Reveal the Genetic Basis of Autism, Li Liu


Mixed Membership Distributions with Applications to Modeling Multiple Strategy Usage, April Galyardt; Assistant Professor, University of Georgia

Learning Spatio-Temporal Dynamics: Nonparametric Methods for Optimal Forecasting and Automated Pattern Discovery, Georg Matthias Goerg; Google, NY

New Statistical Applications for Differential Privacy, Robert Hall; Etsy

Comparing Data Sources in High Dimensions, Di Liu; Google, NY

Incorporating Learning Over Time into the Cognitive Assessment Framework, Cassandra Studer; WeddingWire

Statistical Network Models for Replications and Experimental Interventions, Tracy Morrison Sweet; Assistant Professor; University of Maryland


High-Dimensional Adaptive Basis Density Estimation, Susan Buchman; Alcoa

Creation and Analysis of Differentially-Private Synthetic Datasets, Anne-Sophie Charest; Université Laval, Quebec, Canada

Using Dimension Reduction Techniques to Model Genetic Relatedness for Association Studies, Andrew Crossett; West Chester University

Clustering Trajectories in the Presence of Informative Monotone Missingness, Gabrielle Flynt; Assistant Professor, Bucknell University

Sequential Estimation and Detection in Statistical Inverse Problems, Darren Homrighausen; Assistant Professor, Colorado State University

Techniques for the Estimation and Prediction of Surface Segregation Occurring in Alloys, Gary Klein; SAS Institute

Generalization Error Bounds for State-Space Models, Daniel McDonald; Assistant Professor, Indiana University, Bloomington

Structured Sparsity, Daniel Percival; Google, New York

Behavioral Modeling of Botnet Populations Viewed Through Internet Protocol Address Space, Rhiannon Weaver; Software Engineering Institute, Carnegie Mellon University


Longitudinal Mixed Membership Models with Applications to Disability Survey Data, Daniel Manrique; Post-doc, Duke University

Fast and Accurate Estimation for Astrophysical Problems in Large Databases, Joey Richards; Center for Time Domain Informatics, University of California, Berkeley

A Model of Limit-order Book Dynamics and a Consistent Estimation Procedure, Linqiao Zhao; PNC Bank

Detection of Bursts in Neuronal Spike Trains Using Hidden Semi-Markov Point Process Models, Judy Xi; PNC Bank

The Short Time Fourier Transform and Local Signals, Shuhei Okamura;


Nonparametric Learning in High Dimensions, Han Liu; Assistant Professor, Princeton University

NPredicting Performance and Scaling Up Estimates of Student Skill Knowledge, Elizabeth Ayers; Post-doc, University of California, Berkeley

Adaptive Source Detection, David Friedenberg; Batelle Institute

Cues and Heuristics on Capitol Hill: Relational Models of Decision-Making in the U.S. Senate, Justin Gross; Assistant Professor, University of North Carolina, Chapel Hill

System-Oriented Characterization of the Human Visual System, Eric Huang; Biometric Research Branch, National Cancer Institute

Hyper Markov Non-Parametric Processes for Mixture Modeling and Model Selection, Daniel Heinz; CNA Insurance

Power Prediction in Large Scale Multiple Testing: A Fourier Approach, Avranil Sarkar; LinkedIn