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Professor of Management Science and Engineering
Kay Giesecke
Professor of Management Science and Engineering
Kay Giesecke is Professor of Management Science & Engineering at Stanford University.
He is the Founder and Director of Stanford's Advanced Financial Technologies Laboratory, the Director of the Mathematical and Computational Finance Program and a member of the Institute for Computational and Mathematical Engineering. He has been on the Stanford faculty since 2005, and has held visiting positions at Cornell, UCLA, and the International Monetary Fund. He serves on the Governing Board and Scientific Advisory Board of the Consortium for Data Analytics in Risk and the Council of the Bachelier Finance Society. He is the founder and organizer of Stanford’s annual AI in Fintech Forum. Kay is Editor of Management Science (Finance Area) and Associate Editor for Operations Research, Mathematical Finance, Journal of Financial Econometrics, SIAM Journal on Financial Mathematics and several other leading journals.
Giesecke’s award-winning research sits at the intersection of technology and finance, transforming risk intelligence, market oversight, and investment management. He pioneers stochastic models, statistical machine learning methods, computational algorithms, and software to better understand risk, identify opportunities, and support decision-making. Key application areas include risk management, market surveillance, fair lending, and sustainable investing. His work informs financial regulation, guides institutional practices, and contributes to more transparent, resilient, and equitable financial systems.
In 2020, Kay founded Infima Technologies, a venture-backed SaaS company delivering transformative AI solutions for fixed-income market participants. He served as CEO before becoming Chief Scientist upon his return to Stanford. As Chairman of the Board, he led Infima through an acquisition in 2024.
Kay has published more than 60 research articles in leading academic journals spanning stochastics, operations research, machine learning, econometrics, and financial economics. He is also a co-author of several U.S. patents, some of which underpin commercial investment analytics systems widely used in the financial industry. His research has been recognized with multiple awards, including 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, and the Gauss Prize of the Society for Actuarial and Financial Mathematics of Germany (2003). His work is supported by the National Science Foundation and several leading financial institutions.
Kay has supervised 27 doctoral dissertations, with graduates going on to faculty positions at institutions such as UC Berkeley, Oxford, Wharton, and NYU; leadership roles at firms including Goldman Sachs, Google, JPMorgan, Amazon, and Morgan Stanley; and founding successful technology startups.
Kay is an award-winning educator with extensive experience designing educational programs at all levels. He has created and led successful executive education initiatives that have attracted industry leaders from around the globe.
Kay advises several venture-backed technology startups and has served as a consultant to banks, investment managers, software firms, government agencies, and supranational organizations.
Kay received his doctorate in 2001 from Humboldt Universität zu Berlin where he was a fellow of the Deutsche Forschungsgemeinschaft.
He is the Founder and Director of Stanford's Advanced Financial Technologies Laboratory, the Director of the Mathematical and Computational Finance Program and a member of the Institute for Computational and Mathematical Engineering. He has been on the Stanford faculty since 2005, and has held visiting positions at Cornell, UCLA, and the International Monetary Fund. He serves on the Governing Board and Scientific Advisory Board of the Consortium for Data Analytics in Risk and the Council of the Bachelier Finance Society. He is the founder and organizer of Stanford’s annual AI in Fintech Forum. Kay is Editor of Management Science (Finance Area) and Associate Editor for Operations Research, Mathematical Finance, Journal of Financial Econometrics, SIAM Journal on Financial Mathematics and several other leading journals.
Giesecke’s award-winning research sits at the intersection of technology and finance, transforming risk intelligence, market oversight, and investment management. He pioneers stochastic models, statistical machine learning methods, computational algorithms, and software to better understand risk, identify opportunities, and support decision-making. Key application areas include risk management, market surveillance, fair lending, and sustainable investing. His work informs financial regulation, guides institutional practices, and contributes to more transparent, resilient, and equitable financial systems.
In 2020, Kay founded Infima Technologies, a venture-backed SaaS company delivering transformative AI solutions for fixed-income market participants. He served as CEO before becoming Chief Scientist upon his return to Stanford. As Chairman of the Board, he led Infima through an acquisition in 2024.
Kay has published more than 60 research articles in leading academic journals spanning stochastics, operations research, machine learning, econometrics, and financial economics. He is also a co-author of several U.S. patents, some of which underpin commercial investment analytics systems widely used in the financial industry. His research has been recognized with multiple awards, including 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, and the Gauss Prize of the Society for Actuarial and Financial Mathematics of Germany (2003). His work is supported by the National Science Foundation and several leading financial institutions.
Kay has supervised 27 doctoral dissertations, with graduates going on to faculty positions at institutions such as UC Berkeley, Oxford, Wharton, and NYU; leadership roles at firms including Goldman Sachs, Google, JPMorgan, Amazon, and Morgan Stanley; and founding successful technology startups.
Kay is an award-winning educator with extensive experience designing educational programs at all levels. He has created and led successful executive education initiatives that have attracted industry leaders from around the globe.
Kay advises several venture-backed technology startups and has served as a consultant to banks, investment managers, software firms, government agencies, and supranational organizations.
Kay received his doctorate in 2001 from Humboldt Universität zu Berlin where he was a fellow of the Deutsche Forschungsgemeinschaft.
Education
PhD, Humboldt University Berlin, Germany, Economics (2001)
Contact
(650) 723-9265
Mail Code
4026