John Hessler

Applied Mathematician, Geographic Information Systems Scientist, and Professor in Baltimore, MD.

John Hessler

Applied Mathematician, Geographic Information Systems Scientist, and Professor in Baltimore, MD.

When not climbing in the Alps or racing a carbon fiber Cervélo, I am an applied mathematician, computer scientist, and lecturer at Johns Hopkins University, specializing in the computational modeling and mapping of the transmission of zoonotic diseases and the movement of their animal hosts.

I am the director of the biomap-lab, where our present research centers on modeling the complex transmission pathways of the 2014-2016 Ebola virus outbreak in West Africa, on mapping the historic spatial transmission patterns of plague in Eurasia and Europe, and on tracing the movement of avian H5N1 influenza in wild bird & mammal populations, using fluid flow and machine learning type models.

My theoretical work concentrates on the development of wavelet and spectral techniques for geographic time-series analysis in spatial epidemiology, studying the foundations Markov random field disease mapping algorithms, and on computational approaches to the uncertain geographic context and the modifiable areal unit problems.

An affiliated researcher at the Data Science & AI Institute at Johns Hopkins, I am exploring the use of machine learning for far from equilibrium and non-stationary problems in spatial epidemiology, and have joined the struggle to understand the function of artificial neural networks, using renormalization group methods.

Over the last decade at Johns Hopkins University, I have given lectures or taught the seminars, Bioinformatics and the Mapping of Disease; Bayesian and Markov Random Field Algorithms for Disease Mapping; the Algorithmic Foundations of Geographic Information Systems; Spectral and Wavelet Analysis for Time-Series Analysis; Quantum Information & Computing; and the Mathematical Foundations of Machine & Deep Learning.

The author or editor of more than one hundred articles and books, including the New York Times bestseller, MAP: Exploring the World, I am now trying to turn a mess of mathematical notes into the book, Lectures on Mereotopology and the Ontological Foundations of Geographic Information Science.

In late summer 2024, I will be giving the plenary address, To Save Lives: Lessons of a Pandemic Cartographer at the annual conference of the Royal Geographical Society, in London.

I find being close to the gentle hum of supercomputers, pondering the complex labyrinths of the renormalization group, and exploring the philosophical knots of quantum cryptography, strangely comforting.