John W. Hessler
Alpinist, GIS Scientist, and Professor in Baltimore, MD
When not climbing in the Alps or racing in the saddle of a carbon fiber Cervelo, I am a Specialist in Computational Geography & Geographic Information Science (GIS) at the Library of Congress in Washington, DC and a lecturer in Evolutionary & Quantum Computing in the Graduate School of Advanced Studies of the Krieger School of the Arts and Sciences at the Johns Hopkins University.
An avid mountaineer, I am a frequent contributor to Alpinist Magazine where I write on high-altitude physiology, glaciology and climate change.
Over the past few years I have given lectures or taught seminars in quantum field theory and computing, algorithmic game theory, evolutionary computation, the mathematics of deep learning and algorithm design for supercomputing GIS. Interested in the interface of computation and neuroscience, I have also taught classes in the mapping of the human brain, the visual cortex & deep networks & neural engineering.
The founder of the Topology Lab for Applied Geoinformatics, we use deep and machine learning techniques, in conjunction with advanced GIS and spatial computation, to help solve problems in climate change, bioinformatics and epidemiology.
My current theoretical research focuses on the mathematics and conceptual foundations of deep learning and on the use of the renormalization group, to study the complexity of convolutional neural networks. My main line of inquiry concentrates on the topological structure of non-convex loss landscapes and search spaces, along with the mysteries of back propagation.
Also interested in the mereotopological foundations of GIS, I am currently working on a book entitled, Spatial Algebras: a formalization of the topological & mereological foundations of Geographic Information Science.
The author of more than one hundred articles and books, including the New York Times best-seller, MAP: Exploring the World, my writing and work has been featured in many national media outlets including the New York Times, Washington Post, Discover Magazine, WIRED, the Atlantic’s CITYLAB, the BBC, CBS News and most recently on NPR’s All Things Considered.
I find being close to the gently hum of supercomputers, looking at the subtle, yet aerodynamically significant lines of the Cervelo racing bike, and struggling with the mind-bending complexities of higher topos theory, strangely comforting.