Faculty

Institution

Unit

Venue

Kay Giesecke

Professor of Management Science and Engineering

Stanford University

Affiliations

School of Engineering

Management Science & Engineering

Kay Giesecke is currently serving as a Management Science & Engineering Professor of Management Science and Engineering at Stanford University.

Honors

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Experiences

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Education

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Kay Giesecke

Stanford University

Professor of Management Science and Engineering

You can click a keyword to filter the displayed items

finance financial economics economics empirical finance social sciences social science research applied mathematics risk management operations research management science mathematical finance portfolio optimization machine learning econometrics financial risk management point processes corporate finance valuation economic dynamics finance research financial mathematics financial econometrics information economics affine point processes incomplete information economic analysis blockchain financial cryptography computational intelligence financial stability dynamic economics risk analysis (business) blockchain protocols cryptocurrency blockchain security blockchain privacy portfolio management explainable ai prescriptive analytics computational finance portfolio credit risk credit contagion credit risk modeling crypto economics risk analysis efficient simulation credit risk neural networks significance tests data-driven prescriptive analytics decision science quantitative management information technology numerical simulations economic research entrepreneurship machine learning research retail banking behavioral finance information theory default logic economic control income security stochastic differential equations stochastic calculus emerging risk riskbenefit ratio filtering technique computational economics dynamic pricing derivative pricing sensitivity analysis estimation theory default clustering cyclical correlations portfolio losses

Video Presentations

Notable Scholarly Works

Notable Federal Grants

Collaborators

AICO: Feature Significance Tests for Supervised Learning. ArXiv.org (2025)

machine learningfeature learningmachine learning researchcomputer scienceautomated machine learning

A Set-Sequence Model for Time Series. ArXiv.org (2025)

data modelingtime seriesgranular computingstatisticsnonlinear time seriesapplied mathematics

Learning Illiquid Asset Prices. SSRN Electronic Journal (2025)

financial intelligenceasset pricingfinance researchfinance

P Aico: Feature Significance Tests for Supervised Nbsp; Span Learning /Span /P. SSRN Electronic Journal (2025)

diagnostic criteriainformaticsdata sciencedocumentation

P a Set-Sequence Model for Time Series /P. SSRN Electronic Journal (2025)

technological forecastingtime seriesstatisticsfinancial time series analysis

Predicting Rating Transitions Using Machine Learning. SSRN Electronic Journal (2025)

predictive analyticstrend predictionintelligent classificationanalyticsstatisticsknowledge discoverydata science

Call for Papers— Management Science Virtual Special Issue on AI for Finance and Business Decisions. Management Science (2024)

Barış AtaLin William CongKay GieseckePeng SunChung Piaw Teo

strategic managementtechnologymanagement sciencemanagementinformation economicsbusiness scienceartificial intelligenceinformation technologydata sciencecomputational intelligencequantitative managementcognitive sciencecomputer scienceoperations research

Call for Papers— Management Science Virtual Special Issue on Digital Finance. Management Science (2024)

Lin William CongKay GieseckeCami Kuhnen

entrepreneurshiptechnologymanagement sciencemanagementcomputational financeinformation economicsbusiness sciencesocial sciencesdigital economydata sciencecognitive sciencecomputer science

Advances in Blockchain and Crypto Economics. Management Science (2023)

Bruno BiaisAgostino CapponiLin William CongVishal GaurKay Giesecke

blockchain privacycrypto economicsblockchainfintechblockchain protocolsfinancebusinessfinancial cryptographycryptocurrencyblockchain securityfinancial engineeringblockchain economicsmanagement science

Computationally Efficient Feature Significance and Importance for Predictive Models. (2022)

Enguerrand HorelKay Giesecke

computer sciencepredictive modelsmachine learning

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Kay Giesecke

Professor of Management Science and Engineering

Stanford University

Affiliations

School of Engineering

Management Science & Engineering

Kay Giesecke is currently serving as a Management Science & Engineering Professor of Management Science and Engineering at Stanford University.

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

Kay Giesecke

Stanford University

Professor of Management Science and Engineering

You can click a keyword to filter the displayed items

Video Presentations

Notable Scholarly Works

Notable Federal Grants

Collaborators

AICO: Feature Significance Tests for Supervised Learning. ArXiv.org (2025)

machine learningfeature learningmachine learning researchcomputer scienceautomated machine learning

A Set-Sequence Model for Time Series. ArXiv.org (2025)

data modelingtime seriesgranular computingstatisticsnonlinear time seriesapplied mathematics

Learning Illiquid Asset Prices. SSRN Electronic Journal (2025)

financial intelligenceasset pricingfinance researchfinance

P Aico: Feature Significance Tests for Supervised Nbsp; Span Learning /Span /P. SSRN Electronic Journal (2025)

diagnostic criteriainformaticsdata sciencedocumentation

P a Set-Sequence Model for Time Series /P. SSRN Electronic Journal (2025)

technological forecastingtime seriesstatisticsfinancial time series analysis

Predicting Rating Transitions Using Machine Learning. SSRN Electronic Journal (2025)

predictive analyticstrend predictionintelligent classificationanalyticsstatisticsknowledge discoverydata science

Call for Papers— Management Science Virtual Special Issue on AI for Finance and Business Decisions. Management Science (2024)

Barış AtaLin William CongKay GieseckePeng SunChung Piaw Teo

Call for Papers— Management Science Virtual Special Issue on Digital Finance. Management Science (2024)

Lin William CongKay GieseckeCami Kuhnen

entrepreneurshiptechnologymanagement sciencemanagementcomputational financeinformation economicsbusiness sciencesocial sciencesdigital economydata sciencecognitive sciencecomputer science

Advances in Blockchain and Crypto Economics. Management Science (2023)

Bruno BiaisAgostino CapponiLin William CongVishal GaurKay Giesecke

Computationally Efficient Feature Significance and Importance for Predictive Models. (2022)

Enguerrand HorelKay Giesecke

computer sciencepredictive modelsmachine learning

1
2
3
4
5
9
10 / page

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game theory

agency problems

Ravi Jagannathan

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