Bio

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.

Academic Appointments

Administrative Appointments

  • Member, Council of the Bachelier Finance Society (2020 - Present)
  • Director, Stanford Advanced Financial Technologies Laboratory (AFTLab) (2017 - Present)
  • Director, Stanford Mathematical and Computational Finance Program (2015 - Present)
  • Scientific Advisory Board and Governing Board, Consortium for Data Analytics in Risk (2014 - Present)

Honors & Awards

  • JP Morgan AI Faculty Research Award, JP Morgan (2019)
  • SIAM Financial Mathematics and Engineering Conference Paper Prize, Society for Industrial and Applied Mathematics (2014)
  • Paul Pigott Faculty Scholar, Stanford School of Engineering (2013)
  • Fama/DFA Prize for the Best Asset Pricing Paper, Journal of Financial Economics (2011)
  • Meritorious Service Award, Operations Research, INFORMS - Institute for Operations Research and the Management Sciences (2009, 2010, 2012)
  • Graduate Teaching Award, Stanford University (2007)
  • David Morgenthaler II Faculty Scholar, Stanford School of Engineering (2005)
  • Gauss Prize, Society for Actuarial and Financial Mathematics of Germany (2003)
  • Post-Doctoral Research Fellow, National Science Foundation of Germany (2002-2003)
  • Deutsche Bundesbank Fellow, Deutsche Bundesbank (2002)

Boards, Advisory Committees, Professional Organizations

  • Chairman, Infima Technologies, Inc. (2020 - Present)
  • Editor, Management Science (2018 - Present)
  • Associate Editor, Operations Research (2008 - Present)
  • Associate Editor, Journal of Financial Econometrics (2020 - Present)
  • Associate Editor, Mathematical Finance (2013 - Present)
  • Associate Editor, Journal of Financial Data Science (2023 - Present)
  • Associate Editor, Digital Finance (2021 - Present)
  • Associate Editor, SIAM Journal on Financial Mathematics (2013 - Present)
  • Associate Editor, Journal of Risk (2015 - Present)
  • Editorial Board, SIAM Book Series on Financial Mathematics (2013 - Present)
  • Associate Editor, Mathematics and Financial Economics (2017 - 2021)
  • Associate Editor, Finance & Stochastics (2018 - 2021)
  • Associate Editor, Journal of Credit Risk (2016 - 2021)
  • Vice Chair, SIAM Activity Group on Financial Mathematics and Engineering (2013 - 2015)
  • Associate Editor, IIE Transactions (2009 - 2015)
  • Associate Editor, Journal of Banking and Finance (2011 - 2015)
  • Associate Editor, Operations Research Letters (2009 - 2012)

Professional Education

  • PhD, Humboldt University Berlin, Germany, Economics (2001)

Patents

  • Kay Giesecke, Justin Sirignano. "United States Patent 15/331,825 Apparatus for Analyzing the Risk of a Large Loan Pool and Method of Using"
  • Kay Giesecke, Justin Sirignano. "United States Patent 15/613,256 Apparatus for Optimizing a Loan Pool and Method of Using"
  • Kay Giesecke, Randy Correll, Peter McMahon. "United States Patent 62/354,817 A quantum-annealing computer method for selecting the optimum bids in a combinatorial auction"
  • Kay Giesecke, Randy Correll, Peter McMahon, Vincent Su. "United States Patent 62/354,818 A quantum-annealing computer method for financial portfolio optimization"
  • Kay Giesecke. "United States Patent 7536329 Method and Apparatus for an Incomplete Information Model of Credit Risk", Nov 11, 2004

Contact

  • Academic
    giesecke@stanford.edu
    University - Faculty Department: Management Science and Engineering Position: Professor
    • 307 Huang Engineering Center
    • Stanford University
    • 475 Via Ortega
    • Stanford,  California  94305 
    (650) 723-1614 (fax)

Additional Info

Links

Current Research and Scholarly Interests

Kay is a financial technologist whose research agenda is driven by significant applied problems in areas such as investment management, risk analytics, lending, and regulation, where data streams are increasingly large-scale and dynamical, and where computational demands are critical. He develops and analyzes statistical machine learning methods to make explainable data-driven decisions in these and other areas as well as efficient numerical algorithms to address the computational issues arising in this context. The methods and tools support, for example, sound and transparent investment, trading, lending and servicing decisions, measuring and controlling risk, surveilling financial markets, and assessing the impact of climate change on markets and institutions.

2024-25 Courses

Stanford Advisees

All Publications

https://orcid.org/0000-0002-5380-2918