Past Senior Thesis Students

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2020:

• Helen Lan (2020): “Multiple Comparison Test“; Currently: Analyst, Cornerstone Research.
• Nolan McCafferty (2020): “Style Transfer with Neural Networks“; Currently: Software Engineer, Amazon.
• Zach Senator (2020): “Random Forests and Beyond“; Currently: Business Analyst, Strategy & Operations, Deloitte.
• Amy Watt (2020): “The Expectation Maximization Algorithm in RNA-Sequencing Read Alignment“; Currently: Data Scientist, Analytics, Facebook.

2019:

• Alex Gui (2019): “Local Prediction Confidence for Classification Random Forests“; Currently: MS candidate, Stanford University, Statistics: Data Science
• Frances Hung (2019): “Active Learning Experimental Design of Bayesian Networks“; Currently: PhD candidate, Duke University, Statistics
• Vedant Vohra (2019): “Estimating the proportion who benet from a treatment in a Randomized Controlled Trial“; Currently: Empirical Research Fellow, Stanford Law School
• Justin Weltz (2019): “Over-Policing and Fairness in Machine Learning“; Currently: PhD candidate, Duke University, Statistics

• Christina Duron (2019, PhD CGU): “The Distribution of Betweenness Centrality in Exponential Random Graph Models“; Currently:  Postdoctoral researcher, University of Arizona, Mathematics

2018:

• Chris Barnes (2018): “Artistic Style Transfer using Deep Learning“; Currently: Analyst, KKR & Co. L.P.
• Kalyan Chadalavada (2018): “Partial Least Squares Regression in Football Projections“; MS, Tulane University, Pharmacology.
• Luis Espino (2018): “Racism without a Face: Predictive Statistics in the Criminal Justice System“; Currently: Technology Associate, fwd.us, Community Department.
• Kashvi Tibrewal (2018): “Evaluating Splitting Criteria in Classification Trees“; Currently: IEQ Capital

2017:

• Benji Lu (2017): “Constructing Prediction Intervals for Random Forests”; Ph.D. candidate, UC Berkeley, Statistics.
• Maria Martinez (2017): “The EM algorithm and RNA sequencing”; Currently: Software Engineer, Intuit.
• Yenny Zhang (2017): “Integrating Random Forests into the Bag of Little Bootstraps”; Currently: Data Engineer, Factual Inc.

2016:

• Isaiah Boone (2016): “SVM and the Application of Prediction Rules”; Currently: Associate, Leonard Green & Partners.
• John Bryan (2016): “Developing Inference Frameworks for Random Forests Using Bag of Little Bootstraps and Related Methods”; M.D. candidate, Northwestern University Feinberg School of Medicine.
• Ciaran Evans (2016): “Normalization of RNA-Seq data in the case of asymmetric differential expression”; Ph.D. 2021, Carnegie Mellon University, Statistics.  Currently: Assistant Professor of Mathematics & Statistics, Wake Forest University.
• Dylan Quantz (2016): “Analyzing Centrality in Complex Gene Networks”; Currently: Player Development Trainee, Atlanta Braves.

2015:

• Rebecca Baiman (2015): “A Critical Comparison of Mathods in Statistical Inference Education”; Masters of Education 2017, Math Secondary Education, Vanderbilt University; Currently: Ph.D. candidate, CU Boulder, Atmospheric Science.
• Jacob Fiksel (2015): “Differential Gene Expression Analysis with Microarray and RNA-seq Data”; Ph.D. 2020, Johns Hopkins Bloomberg School of Public Health, Biostatistics;  Currently: Senior Biostatistician, Janssen.

Jacob’s blog (about grad school and data science, among other things)

• Chris Garnatz (2015): “Trusting the Black Box: Confidence with Bag of Little Bootstraps”; Currently: Independent Consultant, Techstyles Sportsware
• Caroline Zaia (2015): “Multilevel Regression in Value Added Modeling for Teacher Assessment”; Currently: Planning Analyst, Stitch Fix

2014:

• Maricela Cruz (2014): “Long-term Averages of the Stochastic Logistic Map”; Ph.D. 2019, University of California, Irvine, Statistics;  Currently: Assistant Investigator at Kaiser Permanente Washington Health Research Institute
• Thalia Rodriguez (2014): “Towards a More Conceptual Way of Understanding and Implementing Inferential Rules”; M.A. in Teaching 2016, the University of Southern California Rossier School of Education; Currently: Mathematics Teacher, Santa Ana Unified School District
• Brian Williamson (2014): “Shrinkage Estimators for High-Dimensional Covariance Matrices”; Ph.D. 2019, University of Washington, Biostatistics; Currently: Postdoctoral Researcher, The Fred Hutchinson Cancer Research Center

2013:

• Melinda Borello (Pitzer, 2013): “Standardization and Singular Value Decomposition in Canonical Correlation Analysis”;
• Jacob Coleman (2013): “Robust Sparse Canonical Correlation Analysis and PITCHf/x”; Ph.D. 2019, Duke University, Statistics; Currently: Senior Quantitative Analyst, Los Angeles Dodgers.
• Karl Kumbier (2013): “Detecting and Estimating Filamentary Structures in the Presence of Background Noise”; Ph.D. 2019, UC Berkeley, Statistics; Currently: Postdoctoral researcher, UCSF.
• Guy Stevens (2013): “Bayesian Statistics and Baseball” ; Currently: Senior Director-Research & Development/Strategy, Kansas City Royals.
• Yuanxi Zhang (2013): “How Does a Bayesian Investor Time the Market”; M.S. 2018, U Chicago, Economics.

2012:

• Tim Stutz (2012): “Modeling the Evolution of Sexual Diploid Populations via a Stochastic Moran Process”; Ph.D. candidate, UCLA, Biomathematics.

2011:

• Kate Brieger (EA, independent study, 2011): “The Evolution of Statistics in Medicine” ; M.D. / Ph.D. candidate, University of Michigan, Biostatistics.
• Christine Ju (Scripps, 2011): “Determining Overrepresentation of Gene Ontology Terms using the Hypergeometric Distribution”; M.S. 2013, Duke, Biostatistics; Currently: Senior Biostatistician, Roche Sequencing Solutions.

2010:

• Minsoo Kim (2010): “Statistical Classification”; M.S. 2015, U Georgia, Statistics; Currently: Scientific Computing Professional Associate, Carl Vinson Institute of Government.
• Mary Owen (2010): “Tukey’s Biweight Correlation and the Breakdown”; Currently: Pastry Cook, Marta.
• Mark Simon (2010): “Randomly Generating Computationally Stable Correlation Matrices”; Currently: Financial Analyst, Taal Capital Management.

2009:

• Patrick Kimes (2009): “Understanding q-values as a More Intuitive Alternative to p-values”; Ph.D. 2015 (“New Statistical Learning Approaches with Applications to RNA-Sequencing Data.”  Advisor: J.S. Marron), UNC, Statistics; Currently: Post-doctoral fellow, Dana-Farber Cancer Institute / Harvard School of Public Health.
• Alison Kosel (2009): “Simulating Correlated Multivariate Normal Data”; Ph.D. 2016 (“Local Estimation of Patient Prognosis”), U Washington, Biostatistics; Currently: Data Scientist, Facebook.
• Daniel Scinto (2009): “Stock Ranking and Portfolio Selection: Revising and Developing Z-scores“; Currently: Senior Portfolio Manager, BFAM Partners.

2008:

• Brianna Pasco (Scripps, Dec 2008): “A Basic Introduction and Comparison of Linear Discriminant Analysis and Support Vector Machines”.
• Nick Conway (2008): “A Resistant Measure of Distance in DNA Microarrays”.
• Austen Head (2008): “Correlation Correction of Sample Measures from Bivariate Distributions”; Ph.D. 2014, Stanford, Statistics; Currently: Head of Data Science, PayJoy.
• Robert Kurtzman (2008): “The Advantages of a Biweight Metric in Clustering Microarray Data”; Ph.D. 2015, UCLA, Economics; Currently:  Senior Economist, Federal Reserve Board.

2007:

• Jeffery Joe Nanda (2007): “Correcting for Bias in Correlation Coefficients Due to Intraindividual Variability”; MBA 2011, Stanford; Currently: Investment Manager, IFC Asset Management Company. 
• Andrea Vijverberg (2007): “Clustering Microarray Data”; M.S. Computational Finance 2008; Currently: FX Options Trader, Bunge.
• Jonathan Buster Zalkind (2007): “Four Colors is not Enough: Visualizations of Simulated Spatial-Model Elections Under Different Voting Methods”.

2006:

• Aya Mitani (Pitzer, 2006): “Biweight Correlation as a Measure of Distance between Genes on a Microarray” (abstract, presentation); MPH 2008, Yale, Biostatistics; Ph.D. 2019, Boston University, Biostatistics; Currently: postdoc with Sebastien Haneuse, Harvard Biostatistics.

2005:

• Joseph Richards (2005): “Classification of Geologic Units on Ganiki Planitia Quadrangle (V14) Venus Using Statistical Clustering Methods”, Ph.D. 2010, Carnegie Mellon University, Statistics; Currently: Head of Operations, Down to Cook.
• Alison Wise (2005): “Statistical Analysis of Microarrays to Determine Genetic Changes in Aging Yeast”; Ph.D. candidate, UNC, Biostatistics.

2004:

• Lee (Strassenburg) Shanahan (Dec 2004): “A Statistical Comparison of the Average Waiting Times Between Flares in Lupus Patients”, Currently: Innovation Consultant, American Family Insurance.

2003:

• Veronica (Montes De Oca) Aispuro (2003): “Methods for Evaluating Health Care Claims Data”  (an application of Bootstrapping); Ph.D. 2008, University of California, Riverside, Applied Statistics; Currently: Senior Healthcare Economic Consultant, UnitedHealthcare Medicare & Retirement.