John W. Hessler, FRGS

Mathematician, GIS Scientist, and Professor in Baltimore, MD

John W. Hessler, FRGS

Mathematician, GIS Scientist, and Professor in Baltimore, MD

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When not climbing in the Alps or racing a carbon fiber Cervélo, I am the director and founder of the λ-LAB, where our philosophy is to apply high-performance computing and geospatial analysis, to some of the most difficult humanitarian and policy issues facing the world today.

We are focused on developing new statistical tools for mapping and modeling the dynamics of far from equilibrium spatial processes, like the spread of pandemics and mass population movements and refugee flows.

Recently, the lab's research has centered on the geospatial dynamics of the West African Ebola outbreak in 2014-2016, and on the use of evolutionary computation to study the dynamics of refugee movements using fluid flow models derived from the Cahn-Hilliard equations. We are also interested in related applications of spatial game theory to epidemiological modeling.

Our theoretical work has expanded to include data driven social justice issues, like the mathematics of the database reconstruction theorems and the effects of differential privacy algorithms, like Top Down, on the data of the 2020 Census.

A lecturer at the Johns Hopkins University, over the last few years I have given lectures about or taught seminars in Evolutionary and Algorithmic Game Theory; Quantum Algorithms & Information Theory; Mereology & the Foundations of Geographic Information Science (GIS); the Mathematical Modeling Refugee Flows; and the Mathematics of the Redistricting & Gerrymandering Problem. I also teach courses in algorithm design and the foundations of GIS in the Pierre and Marie Curie Faculty at Sorbonne Université in Paris.

The author of more than one hundred articles and books, including the New York Times bestseller, MAP: Exploring the World, my work has been featured in many media outlets including the New York Times, Washington Post, the BBC, CBS News and NPR’s All Things Considered.

Imagining a four-dimensional and process based ontology for the next generation of temporal GIS computing, I am trying to turn a mess of mathematical course notes into the book, Lectures on Mereotopology and the Ontological Foundations of Geographic Information Science.

A Fellow of the Royal Geographical Society, I find being close to the gentle hum of supercomputers, pondering the depths of quantum category theory and confronting the intricate philosophical knots of evolutionary algorithms, strangely comforting.