Godfrey Cadogan is a Research Scientist in Risk and Uncertainty at the Institute for Innovation and Technology Management, Ted Rogers School of Management, Ryerson University. His research focus is on application of diverse branches of mathematics such as algebraic topology, number theory, group theory, probability theory, and functional analysis to the foundations of risk and uncertainty. His research has been featured in SSRN Top Ten lists in diverse areas that include, but is not limited to, Cognition in Mathematics, Science, & Technology; Behavioral & Experimental Accounting; Uncertainty & Risk Modeling; Statistical Decision Theory; Emerging Research within Organizational Behavior; Behavioral Economics; Econometrics, and Econophysics. His current research includes martingale systems and data mining algorithms that mimic active portfolio management strategies for portfolio alpha from high frequency trading, canonical representation of option pricing formulae to reflect investor sentiment, behavioral response to seemingly fair gambles, quantum cognition, inefficiencies in pricing mechanisms for optimal auctions for internet advertising based on click rates, mechanism design for public-private sector partnerships, and topology of prospect theory’s function space. He holds a B.S. in Actuarial Math, B.S. in Statistics; M.A in Statistics, and ISR Certificate in Modeling American Electoral Politics, all from the University of Michigan, where he is pursuing in interdisciplinary doctoral studies in Behavioral Economics and Probability Theory.