John W. Hessler is a Specialist in Computational Geography and Geographic Information Science at the Library of Congress.
A Fellow of the Royal Geographical Society, he is the founder of the Election Labs for the Study of the Mathematics of Voting, and is a Lecturer in the Graduate School of Advanced Studies at Johns Hopkins University. He has taught seminars in advanced spatial and cartographic analysis, category theory, game theory and Arrow’s theorem, and the mathematical analysis of gerrymandering.
His current research focuses on the use of renormalization group and random matrix methods to study the mysterious mathematics and computational function of deep learning algorithms and networks. He is also interested in the theory of Markov Chains and their application to mapping, redistricting and gerrymandering problems, and in the application of supercomputing GIS to the study of voting systems around the world.
He is the author of more than one hundred books and articles, including MAP: Exploring the World; The Naming of America: Martin Waldseemüller’s 1507 World Map and the Cosmographiae Introductio; A Renaissance Globemaker’s Toolbox: Johannes Schöner and the Revolution of Modern Science, 1475–1550; Seeing the World Anew: The Radical Vision of Martin Waldseemüller’s 1507 and 1516 World Maps. His work has been featured in many national media outlets including the New York Times, Washington Post, Discover Magazine, the Atlantic’s CITYLAB, the BBC, CBS News and most recently on NPR’s “All Things Considered” and in WIRED. An avid mountaineer, he is also an occasional contributor to Alpinist Magazine, and is currently at work on a book entitled Algorithmic Democracy: Mathematical Approaches to the Study of Gerrymandering.