Alexandre Belloni
Alexandre Belloni
Westgate Distinguished Professor of Decision Sciences and Statistical Science at Duke University
and Amazon Scholar WW FBA
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Alexandre Belloni is the Westgate Distinguished Professor of Decision Sciences and Statistical Science at Duke University and an Amazon Scholar WW FBA. His research spans AI, statistics, economics and operations research. His work focuses on developing and applying advanced methods in causal inference, high-dimensional statistics, econometrics, machine learning, and mechanism design to solve complex decision-making problems in business, public policy, and digital settings.
Alexandre Belloni is the Westgate Distinguished Professor of Decision Sciences and Statistical Science at Duke University and an Amazon Scholar WW FBA. His research spans AI, statistics, economics and operations research. His work focuses on developing and applying advanced methods in causal inference, high-dimensional statistics, econometrics, machine learning, and mechanism design to solve complex decision-making problems in business, public policy, and digital settings.
A central goal of Belloni’s research is to understand how data and algorithms can be harnessed to improve decision processes, particularly in environments characterized by strategic selection and interaction, uncertainty, and constrained information.
A central goal of Belloni’s research is to understand how data and algorithms can be harnessed to improve decision processes, particularly in environments characterized by strategic selection and interaction, uncertainty, and constrained information.
His work blends rigorous theory with practical relevance, often addressing questions such as: How can firms and policymakers extract causal insights from large-scale observational data? How should incentives be structured in digital settings? And how optimization and machine learning be combined to make better predictions, counterfactuals and decisions?
His work blends rigorous theory with practical relevance, often addressing questions such as: How can firms and policymakers extract causal insights from large-scale observational data? How should incentives be structured in digital settings? And how optimization and machine learning be combined to make better predictions, counterfactuals and decisions?
Professor Belloni's research has appeared in top journals across economics, statistics, and operations research, he has served as associate editor to journals in Economics, Operations Research and Statistics, and he was the inaugural Area Editor for Machine Learning and Data Science Area of Operations Research. He has co-authored influential work on the development of valid inference in high-dimensional settings, bridging machine learning and causal inference in econometric settings. He has also worked extensively on optimization and the design of optimal mechanisms under information constraints.
Professor Belloni's research has appeared in top journals across economics, statistics, and operations research, he has served as associate editor to journals in Economics, Operations Research and Statistics, and he was the inaugural Area Editor for Machine Learning and Data Science Area of Operations Research. He has co-authored influential work on the development of valid inference in high-dimensional settings, bridging machine learning and causal inference in econometric settings. He has also worked extensively on optimization and the design of optimal mechanisms under information constraints.
He is also a frequent collaborator with industry partners, working on applications in areas such as online advertisement, energy, and supply chains. His academic and industry work has been recognized with awards and honors, including the 2007 Young Researchers Competition in Continuous Optimization Award, the 2022 Bank of America Award at Fuqua, and was part of the team that won the 2022 Da Vinci award at Amazon SCOT.
He is also a frequent collaborator with industry partners, working on applications in areas such as online advertisement, energy, and supply chains. His academic and industry work has been recognized with awards and honors, including the 2007 Young Researchers Competition in Continuous Optimization Award, the 2022 Bank of America Award at Fuqua, and was part of the team that won the 2022 Da Vinci award at Amazon SCOT.
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