Dr. Jack Peterson
is Core Developer at the
Augur combines the magic of prediction markets with the power of a decentralized network to create a stunningly accurate forecasting tool — and the chance for real money trading profits.
Jack is a physicist, entrepreneur, and software developer. He became fascinated by distributed networks while finishing his Ph.D. at UCSF. He has delved into scientific computing (1, 2, 3, 4, 5, 6, 7), blockchain programming (1, 2, 3, 4, 5), computer vision, neural networks, peer-to-peer networking, GIS, and web development. He was a National Defense Science and Engineering Graduate Fellow, and has published several peer-reviewed articles on complex networks and information theory, including modeling and simulation of protein-protein interaction networks and social networks, automated kinetic model extraction for single-molecule experiments, and the statistical mechanics of “heavy-tailed” distributions.
His papers include Nonuniversal power law scaling in the probability distribution of scientific citations, A maximum entropy framework for nonexponential distributions, Mutant Telomeric Repeats in Yeast Can Disrupt the Negative Regulation of Recombination-Mediated Telomere Maintenance and Create an Alternative Lengthening of Telomeres-Like Phenotype, Simulated Evolution of Protein-Protein Interaction Networks with Realistic Topology, Single Molecule Conformational Memory Extraction: P5ab RNA Hairpin, Augur: a decentralized, open-source platform for prediction markets, and False shares in verifiable secret sharing with finite field commitments.
Jack earned his Bachelor of Science (B.S.) in Physics and Genetics at The University of Georgia in 2007 and his Doctor of Philosophy (Ph.D.) in Biophysics at the University of California, San Francisco in 2012.
Watch Augur’s Dr. Jack Peterson Speaks at Ethereum’s 2015 ÐΞVCON1 Conference and Jack Peterson of Augur speaks at Boise Bitcoin Meetup July 20th 2016. Read his GitHub page. View his Google Scholar profile and LinkedIn profile. Follow his Twitter feed.