About Dan Spencer

Education

Ph.D. Statistical Science, UC Santa Cruz, Department of Applied Math and Statistics, Degree earned June 2020

Dissertation:

Spencer, D. (2020). Inference and uncertainty quantification for high-dimensional tensor regression with tensor decompositions and Bayesian methods. University of California, Santa Cruz.

Finalist for the 2020 Savage Award in Applied Methodology

Master’s in Applied Statistics, Penn State University, Department of Statistics, Degree earned August 2010

B.S. Mathematics, Economics minor, Penn State University, Degree earned August 2009

Publications

Spencer, D., Yue, Y. R., Bolin, D., Ryan, S., & Mejia, A. F. (2022). Spatial Bayesian GLM on the cortical surface produces reliable task activations in individuals and groups. NeuroImage, 118908.

Guhaniyogi, R., & Spencer, D. (2021). Bayesian tensor response regression with an application to brain activation studies. Bayesian Analysis, 16(4), 1221-1249.

Spencer, D., Guhaniyogi, R., & Prado, R. (2020). Joint Bayesian estimation of voxel activation and inter-regional connectivity in fMRI experiments. Psychometrika, 85(4), 845-869.

Spencer, D., Bolin, D., & Mejia, A. Fast Bayesian estimation of brain activation with cortical surface and subcortical fMRI data using EM. arXiv preprint arXiv:2203.00053. Under review at Computational Statistics and Data Analysis.

Spencer, D., Guhaniyogi, R., Shinohara, R., & Prado, R. Bayesian scalar-on-tensor regression using the Tucker decomposition for sparse spatial modeling finds promising results analyzing neuroimaging data. arXiv preprint arXiv:2203.04733. Under review at Biostatistics.

Parlak, F., Pham, D., Spencer, D., Welsh, R., & Mejia, A. Sources of Residual Autocorrelation in Multiband Task fMRI and Strategies for Effective Mitigation. arXiv preprint arXiv:2209.06783. Under review at Frontiers in Neuroscience.

Shadmon, R., Spencer, D., & Arden, O. Proximal Consensus: Responsive data pipelines with approximate fault detection. Available upon request. Under review for IEEE Symposium on Security and Privacy.

Awards and Honors

Poster Award, Junior International Society for Bayesian Analysis Category - Fast Bayesian estimation of brain activation with cortical surface and subcortical fMRI data using EM - ISBA World Meeting - June 2022

Featured Poster - Surface-based spatial Bayesian GLM produces reliable task activations in individuals and groups - Organization for Human Brain Mapping World Meeting - June 2021

Finalist, 2020 Savage Dissertation Award in Applied Methodology, International Society of Bayesian Analysis - Inference and Uncertainty Quantification for High-dimensional Tensor Regression with Tensor Decompositions and Bayesian Methods

Student Poster Award - Bayesian Mixed Effect Sparse Tensor Response Regression Model with Joint Estimation of Activation and Connectivity - Statistical Methods in Imaging - June 2019

Conference Presentations

Structural differences in Alzheimer’s Disease using Bayesian Tensor Regression, Joint Statistical Meeting, Washington, DC, August 2022.

Fast Bayesian estimation of brain activation with cortical surface and subcortical fMRI data using EM, World Meeting of the International Society of Bayesian Analysis, Montreal, Quebec, Canada, June 2022. Winner of a Poster Award

Analyzing task-fMRI the Bayesian way, Statistical Methods in Imaging, Vanderbilt University, Nashville, TN, May 2022

Surface-based Bayesian General Linear Model: An EM Approach, CM Statistics Conference, King’s College London, London, UK, December 2021.

Inference and Uncertainty Quantification for High-dimensional Tensor Regression with Tensor Decompositions and Bayesian Methods, World Meeting of the International Society of Bayesian Analysis, Virtual, June 2021.

Surface-based spatial Bayesian GLM produces reliable task activations in individuals and groups, Organization for Human Brain Mapping World Meeting, June 2021. Featured Poster

Bayesian Mixed Effect Sparse Tensor Response Regression Model with Joint Estimation of Activation and Connectivity, Statistical Methods in Imaging Conference, Department of Statistics, University of California, Irvine, Irvine, CA, June 2019. Winner of a Student Award

Bayesian Tensor Regression, Workshop on Distributed and Parallel Data Analysis, Statistical and Applied Mathematical Sciences Institute, Raleigh, NC, September 2016

Bayesian Tensor Regression, AMS/CAFIN Workshop, UC Santa Cruz, Santa Cruz, CA, April 2016

Service

Organizer - Statistics in Imaging Working Group. A monthly meeting to present and share work and connect with others in the statistical imaging community.

Reviewer - Reviewer in several journals for articles on tensor regressions, Bayesian methods, and software for the following publications:

  • Annals of Applied Statistics
  • Biostatistics
  • Computational Statistics and Data Analysis
  • NeuroImage
  • Psychometrika
  • RJournal

Employment History

Indiana University Bloomington

Postdoctoral Researcher - 2020 - present

UC Santa Cruz

Instructor - 2016, 2018, 2019

Teaching Assistant - 2015 - 2020

JP Morgan Chase & Co.

Intern - June 2017 - September 2017, June 2018 - September 2018

United States Peace Corps - Mozambique, Africa

Peace Corps Education Volunteer - September 2011 - November 2013

Statistical Consulting Center – Penn State University

Consultant – August 2010 - June 2011

Teaching

Statistics Workshop – Microbiology and Environmental Toxicology Department – UC Santa Cruz

Course designer and Instructor – September 2016

“This short course was designed with the intention of providing graduate students and staff in the biological sciences with the statistical tools and understanding necessary to perform publication-worthy analyses on a diverse set of experimental design schemes.”

AMS 5: Statistics – UC Santa Cruz

Teaching Assistant – Fall 2016, Spring 2016, Winter 2016, Fall 2015, Winter 2015

“Introduction to statistical methods/reasoning. This is designed to be a first course in statistics.”

AMS 7: Statistical Methods For The Biological, Environmental, And Health Sciences - UC Santa Cruz

Teaching Assistant - Winter 2017, Spring 2019

“Case-study-based introduction to statistical methods as practiced in the biological, environmental, and health sciences.”

AMS 80A: Gambling and Gaming - UC Santa Cruz

Teaching Assistant - Spring 2017

“Games of chance and strategy motivated early developments in probability, statistics, and decision theory. Course uses popular games to introduce students to these concepts, which underpin recent scientific developments in economics, genetics, ecology, and physics.”

AMS/STAT 132: Classical and Bayesian Inference - UC Santa Cruz

Teaching Assistant - Winter 2019, Winter 2020

“Introduction to statistical inference at a calculus-based level: maximum likelihood estimation, sufficient statistics, distributions of estimators, confidence intervals, hypothesis testing, and Bayesian inference.”

AMS/STAT 266A - Data Visualization and Statistical Programming in R - UC Santa Cruz

Teaching Assistant - Fall 2017

Instructor - Fall 2018, Fall 2019

Introduces graduate students to data visualization and statistical programming techniques using the R language. Covers the basics of the language, descriptive statistics, visual analytics, and applied linear regression.

STAT 200: Elementary Statistics – Penn State University

Instructor, World Campus – Spring 2014 - Summer 2018, Summer 2011

Instructor, University Park - Spring 2011, Fall 2010, Summer 2010

“STAT 200 is a standard first course in statistics, covering descriptive statistics, frequency distributions, probability, binomial and normal distributions, statistical inference, linear regression, and correlation.”

STAT 250: Introduction to Biostatistics - Penn State University

Teaching Assistant - Spring 2010

“STAT 250 is a standard first course in statistics, with an emphasis on applications and statistical techniques of particular relevance to the biological sciences.”

STAT 480: Introduction to SAS - Penn State University

Instructor, University Park - Summer 2010

“This course introduces students to basic knowledge in programming, data management, and exploratory data analysis using SAS software. Students are provided the opportunity to learn a comprehensive set of SAS data-related techniques through lessons, demonstrations, and homework assignments.”

8th Grade Mathematics and 10th Grade Technology – Escola Secundária de Zóbuè, Zóbuè, Moçambique

US Peace Corps Education Volunteer – September 2011 through November 2013

“Mathematical education in basic algebra, plotting, and solving systems of linear equations. Technology education covering the history of modern technology covering radio through the use of the internet, including practical courses introducing students to Microsoft Office.”

Morgan Academic Support Center for Student Athletes – Penn State University

Tutor – May 2008 through September 2010