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, I am a specialist in Computational Geography & Geographic Information Science (GIS) at the Library of Congress and a lecturer at the Johns Hopkins University in Baltimore, MD. I also teach courses in the geospatial analysis of epidemics & GIS in the Pierre and Marie Curie Faculty at Sorbonne Université in Paris.

Over the last few years I have given lectures about or taught seminars in Evolutionary Game Theory; Bats & the Biogeography of Zoonotic Diseases Bioinformatics & Spatial Analysis; and Mereology & the Foundations of GIS.

I am the founder of the λ-LAB, where our philosophy is to apply high-performance computing, mathematical modeling, and geospatial analysis, to some of the most difficult humanitarian and policy issues facing the world today.

We are focused developing new statistical tools for mapping far from equilibrium and chaotic processes, like the spread of pandemics, the biogeography of zoonotic spillover of diseases, like Monkeypox, and mass population movements and refugee flows.

Recently, our research has centered the use evolutionary computation and advanced GIS to study the complex problem of the dynamics of refugee flows using recent innovations in phase field theory, and the Cahn-Hilliard Equations, along with new research on the scaling laws of mass population movement.

Our theoretical work has expanded to include the mathematics of the database reconstruction theorems and the effects of differential privacy algorithms, like Top Down, on the data of the 2020 Census, and on the theoretical foundations of Boolean Satisfiability Theorems.

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 GIS, 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 informational depths of phylogenetics, and confronting the intricate philosophical knots of evolutionary algorithms, strangely comforting.