Shane Jensen Shane T. Jensen

 Associate Professor
 Department of Statistics
 The Wharton School
 University of Pennsylvania

 463 Huntsman Hall
 3730 Walnut Street

 stjensen at

My current cv is available for download in PDF format.

A list of my publications can be found here: Publication List

My Google Scholar profile: Google Scholar Profile


 Urban Analytics

My current primary research focus is urban analytics: the quantitative analysis of the functioning of local areas within large cities. The recent explosion in data collection on so many aspects of city life gives us the opportunity to investigate urban environments at a higher resolution than ever before. Philadelphia is an ideal focus for our work as it is a city undergoing rapid change and development against a backdrop of difficult civic challenges including substantial economic disparity and dramatic variation in safety between different neighborhoods of the city.

My research program is a collaborative and multidisciplinary effort that spans the fields of architecture, urban planning, criminology and statistics. Our endeavor is to take the available data on cities and set up artificial experimental situations that allow us to learn as objectively as possible about what aspects of city environments are associated with safety and other outcomes.

You can read more about our data collection and analysis pipeline in our paper:

Analysis of Urban Vibrancy and Safety in Philadelphia by C. Humphrey, S.T. Jensen, D. Small and R. Thurston. arXiv: 1702.07909.

You can also read more about our goals in these media articles:

Next City: Philly Streets Get Test of Jane Jacobs Eyes on the Street Effect

Knowledge@Wharton: How Urban Planners Can Encourage Vibrancy — and Create Safer Cities. This article also has a podcast link to an interview I did on the Wharton Business radio show "Dollars and Change".

Our urban analytics research program has received generous support from the Wharton Social Impact Initiative.

 Other Research Interests

I enjoy developing statistical methodology and doing applied data science for a wide variety of application areas. Beyond urban analytics, some of my other research interests are:

1. Genetics and Molecular Biology

Developing sophisticated statistical models for the evolution of genomic sequences. Areas of application include the response of HIV under various therapies as well as evolution during cancer progression. Developing models for combining heterogeneous data sources to refine predictions about co-regulated genes and regulatory networks in cells.

Check out this TED talk on the power of molecular biology and genetics.

2. Statistics in Sports

Developing novel statistical models for the comparison of baseball players in terms of on-field performance. Evaluation of fielding ability as well as prediction of future hitting and pitching performance. Quantifying player performance in hockey.

3. Bayesian Nonparametrics

Extensions of Dirichlet processes for grouped and ordered data. Alternative prior processes for non-parametric clustering. Tree-based approaches for high-dimensional settings.

4. Economics and Marketing

Estimating income volatility while allowing for heterogeneity over time and between individuals in the population. Exploring the relationship between income volatility and risk aversion. Modeling career choice as a function of risk aversion. Models for missing data in marketing research.

 Individual Project Pages

SAFE: Spatial Aggregate Fielding Evaluation, our methodology for measuring fielding ability in major league baseball players using a hierarchical probit model. Results are presented across seven seasons of high-resolution ball-in-play data.

COGRIM: Bayesian variable selection model for regulatory network inference through the integration of gene expression data, ChIP binding data and sequence motif data.

PHYLOCLUS: Suite of perl programs for clustering co-regulated genes based on phylogenetically discovered transcription factor binding motifs.

MOTIF CLUSTERING: Perl programs and supplemental material for clustering transcription factor binding motif matrices based on a hierarchical Bayesian model.

 Past Media Attention

2015/10/13: Articles about my collaboration with researchers investigating why elephants get less cancer than humans: Newsweek and IFLscience

2013/02/13: Article about my hockey research with Bobby Gramacy and Matt Taddy at Chicago Booth School of Business which was also linked by the Wall Street Journal

2009/10/26: Another interview about my fielding research on Scienceline

2009/01/26: More coverage of my income volatility research with Stephen Shore on the Marginal Revolution Blog

2008/07/14: Another mention of our fielding research in Slate

2008/06/25: Coverage of my income volatility research with Stephen Shore on the Freakonomics Blog

2008/02/21: The NY Post and Jeter himself responds to our fielding research! NY Post Jeter Response

"Maybe it was a computer glitch" - Derek Jeter

2008/02/17: Media Attention for our Baseball Fielding Research: AP Boston Globe Popular Science Wired Science Citizen

2008/02/11: Media/Blog Discussion of our NY Times article: ESPN article Freakonomics Blog Statistics Blog

2008/02/10: Our NY Times article about Roger Clemens: NY Times Link PDF file


Shane Jensen Webpage by Aline N. (2008)