UF Research Conference on Machine Learning in Finance Speakers
Kay Giesecke is Professor of Management Science and Engineering at Stanford University and is the founder, Executive Chairman and Chief Scientist of Infima Technologies, a capital markets technology company building transformative prediction systems for fixed-income market participants. At Stanford, Kay is the Director of both the Advanced Financial Technologies Laboratory and the Mathematical and Computational Finance Program and is a member of the Institute for Computational and Mathematical Engineering. He also serves on the Governing Board and Scientific Advisory Board of the Consortium for Data Analytics in Risk.
Much of Kay’s work is driven by important applications in areas such as credit risk management, investment management, and, most recently, housing finance. Together with his students at Stanford, Kay has pioneered the core elements of the deep learning and computational technologies underpinning Infima’s solutions and has co-authored five patents. His research has been funded by the National Science Foundation, JP Morgan, State Street, Morgan Stanley, Swiss Re, American Express, Moody’s, and several other organizations.
Kay has published numerous articles in operations research, probability, and finance journals. He is an Editor of Management Science in the Finance Area and an Associate Editor for Mathematical Finance, Operations Research, SIAM Journal on Financial Mathematics, Finance and Stochastics, Mathematics and Financial Economics, Journal of Credit Risk, and Journal of Risk.
Kay has won the JP Morgan AI Faculty Research Award (2019), the SIAM Financial Mathematics and Engineering Conference Paper Prize (2014), the Fama/DFA Prize for the Best Asset Pricing Paper in the Journal of Financial Economics (2011), and the Gauss Prize of the Society for Actuarial and Financial Mathematics of Germany (2003). Kay is the recipient of the Management Science & Engineering Graduate Teaching Award (2007), a DFG Postdoctoral Fellowship (2002-03), and a Deutsche Bundesbank Fellowship (2002).
Kay advises several financial technology startups and has been a consultant to banks, investment and risk management firms, governmental agencies, and supranational organizations.
RebellionResearch.com’s CEO Alexander Fleiss has spoken about Artificial Intelligence Investing in the Wall Street Journal, New York Times, Fox News, BusinessWeek, Bloomberg News, MIT Technology Review, Yomiuri Shimbun, Wired, Geo Magazine, The Economist and Institutional Investor. Chapter 24 of Wall Street Journal Reporter Scott Patterson’s book Dark Pools is on Mr. Fleiss. Mr. Fleiss teaches at Cornell Financial Engineering & Fordham Gabelli School of Business and has guest taught at Amherst College for over a decade and Yale School of Management for 5 years & Rutgers Engineering for 4.
Prior to co-founding RebellionResearch.com, Mr. Fleiss was a Principal at KMF Partners LP, a long-short US equity hedge fund co-managed by John Merriwether of Michael Lewis’ Liars Poker. Mr. Fleiss began his career as a programmer for Sloate, Weisman, Murray & Co which was acquired by Neuberger Berman. Mr. Fleiss developed investment algorithms with the firm’s CEO, Laura Sloate who is now a partner at Neuberger Berman and one of the investors featured in Peter Tanous’ book Investment Gurus. Then Mr. Fleiss managed an Amherst College-funded Ai research project with Amherst College’s Math Department Chair. Mr. Fleiss was a developer on the computer game Flight of the Intruder. Mr. Fleiss received a BA Degree from Amherst College & advanced to the 2nd round of the 2001 US National Math Championships.
Industry Insights and Perspectives Speaker
Dr. Michael Kotarinos is the Chief Technology Officer at Oxyml, where he oversees the firm’s intellectual property pipeline and the design of new and innovative algorithms. Before his time at Oxyml, Michael was a researcher in interactive artificial intelligence systems at the University of South Florida. Michael holds a Ph.D. in Statistics from USF and a Master’s in Statistics from the University of Florida. Michael regularly shares his insights on data analytics, algorithms, and digital transformation with universities, corporations, and not-for-profits across the globe.