Keegan E. Hines


University of Texas, 2014
Ph.D. in Neuroscience
Doctoral Advisor: Richard W. Aldrich

Santa Fe Insitute, 2012
Complex Systems Summer School

Washington and Lee University, 2009
B.S. in Physics
magna cum laude



Traditional statistical methods: Multiple regression, logistic regression, survival analysis, etc.

Computational Statistics/Machine Learning methods: Bootstrap, Bayesian inference, Markov chain Monte Carlo, LASSO/LARS shrinkage, Nonparametric Bayes, time series analysis, Hierarchical Dirichlet Process Hidden Markov Models, clustering/segmentation, Dirichlet process mixture models, Neural Networks, genetic algorithms, principal component analysis, deep learning, ConvNets, Network Theory, Natural Language Processing, Topic Modeling, Latent Dirichlet Allocation.

Technical: R, Python, Spark, Scala, HTML, javascript (d3), AWS, git. I also love LaTeX.

Honors & Awards

Best Abstract Award, Austin Conference on Learning and Memory, 2013

Student Research Achievement Award Finalist, Biophysical Society, 2012

Complex Systems Summer School, Santa Fe Institute for Complex Systems, 2012

Graduate Dean's Prestigious Fellowship Supplement, University of Texas at Austin, 2012

Predoctoral Fellowship, American Heart Association, 2012 - 2014

Dean's Excellence Award, University of Texas at Austin, 2009

Edward O. Levy Fellowship, Washington and Lee University, 2008

APS Student Leadership Scholarship, American Physics Society, 2008

Walter Leconte Stevens Award, Washington and Lee University Physics Department, 2008

NSF REU Research Scholarship, National Science Foundation, 2007

R. E. Lee Research Fellowship, Washington and Lee University, 2006


Hines, K., A Primer on Bayesian Inference for Biophysical Systems. Biophysical Journal, in press.

Hines, K., J. Bankston, R. Aldrich. 2015. Analyzing Single Molecule Time Series Using Nonparameteric Bayesian Inference. Biophysical Journal. 108(3): 540-556.

Hines, K., T. Middendorf, R. Aldrich. 2014. Determination of Parameter Identifiability in Nonlinear Biophysical Models: A Bayesian Approach. Journal of General Physiology. 143(3):401-416.

Hines, K. 2013. Inferring Subunit Stoichiometry From Single Molecule Photobleaching. Journal of General Physiology. 141(6):737-746.