Levi John Wolf

Associate Professor of Spatial Analysis
University of Bristol

About Me

I am an American expat currently working as an Associate Professor in Spatial Analysis at the University of Bristol’s Quantitative Spatial Science Lab. I work in spatial data science, building new methods and software to learn new things about social and environmental processes. Spatial analysis is a way of using the spatial relationships between things in a system to build a better understanding of that system than would be possible if we studied the elements in isolation. I’ve worked on detecting gerrymandering [1,2], neighborhood social change, local statistical models, affordable rent, bayesian computation, species distribution modelling. If you have a problem like this and would like me to take a look, I am available to consult on spatial analysis, modelling, and optimisation problems. I’ve worked at Nextdoor and CARTO (twice), and have consulted for MondialRelay and now InPost… all as a spatial analyst. I am committed to open science, and serve as a maintainer to geopandas, PySAL, and have more minor contributions to scipy, scikit-learn, and spdep.

For info on how to do spatial analysis, I have written a book with Dani Arribas-Bel and Sergio Rey. If you’re more interested in the theory of spatial analysis, Rich Harris and Alison Heppenstall, and I edited the Research Agenda for Spatial Analysis, a collection of manifestos outlining where spatial analysis is and where people think it ought to go.

Right now, I am:

• on my sabbatical 2025-26
• recording The GLaD Podcast with Dani Arribas-Bel and Rachel Franklin.
• writing Causal Inference in Spatial Analysis with Nick Dorward, due to SAGE UK in fall of 2025—wish us luck!
• consulting for Integer.PL about spatial decision support systems.
• writing papers on:
  • the relationship between income inequality and scaling in urban systems,
  • a new kind of algorithm for spatial prediction problems,
  • a new global dataset to capture how “urban” places feel,
  • better methods for predicting diverse oceanic phytoplankton communities,
  • and a review of spatial theory in causal inference

Information for Prospective Students

If you’re interested in pursuing a PhD at the University of Bristol, that’s great! I’ve got a great track record working with students to win funding on advanced quantitative methods/social science topics. Right now, I’m actively seeking students on the following topics:

1. Classical statistical and machine learning methods assume that we’re all independent of one another; that what you do does not affect your neighbor and vice versa. As a spatial analyst, I am very interested in the fact that our surroundings affect our behavior. So, it’s important to integrate spatial reasoning into data science techniques. This either looks like traditional spatial data science techniques that use augmented spatial information, or involves the development of entirely new spatial statistical models & data science methods. Some people call this “GeoAI”, or “spatial machine learning”, or “geographic data science.” I’m interested in all of those things, and have many publications in this area.
2. I am always interested in working with students on questions about redistricting and election forecasting. This is my main area of public activity in geography, where I have engaged fairly extensively in citizens redistricting processes. So, I’d accept students readily who want to study geography and spatial structure of elections, partisan swing, redistricting, and voter realignment.
3. Causal inference is a really big part of contemporary science, but spatial relationships can really mess with the statistical tools we have to analyze causal relationships. If you’re interested in working on methods for spatial causal inference, I’m your guy.
4. Housing is another area where I am increasingly interested. In particular, renting and rent regulation policy is core to how cities “work”, and it’s important for us to understand the impacts of rent and rental policy. I am very interested in accepting students on this topic.
5. And finally, I am open to new collaborations, students, and work on systems of cities. I am very interested in the distributional dynamics of city systems: why do certain places grow and decline, while others seem to grow without bound? How does social inequality affect urbanisation, and vice versa?