What is he best known for?
The fields of study he is best known for:
The scientist’s investigation covers issues in Microeconomics, Behavioral economics, Shareholder, Newspaper and Control.
As a part of the same scientific study, Sendhil Mullainathan usually deals with the Microeconomics, concentrating on Liberian dollar and frequently concerns with Temptation, Investment, Set, Neoclassical economics and Self.
His Behavioral economics study integrates concerns from other disciplines, such as Poverty, Marketing, Competitor analysis and Positive economics.
Sendhil Mullainathan usually deals with Shareholder and limits it to topics linked to Corporate law and State, Earnings, Incentive, Monetary economics and Enforcement.
Sendhil Mullainathan has included themes like Social class and Media bias in his Newspaper study.
His Corporate governance research includes themes of Productivity, Profitability index and Market economy.
His most cited work include:
- How Much Should We Trust Differences-In-Differences Estimates? (5245 citations)
- Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination (2297 citations)
- Enjoying the Quiet Life? Corporate Governance and Managerial Preferences (1441 citations)
What are the main themes of his work throughout his whole career to date?
Sendhil Mullainathan mostly deals with Microeconomics, Public economics, Behavioral economics, Artificial intelligence and Machine learning.
The study incorporates disciplines such as Principal–agent problem, Savings account and Shareholder in addition to Microeconomics.
His Shareholder study is concerned with the field of Corporate governance as a whole.
His Welfare research extends to Public economics, which is thematically connected.
His study in Welfare is interdisciplinary in nature, drawing from both Actuarial science and Value.
His studies deal with areas such as Loan and Marketing as well as Behavioral economics.
He most often published in these fields:
- Microeconomics (21.04%)
- Public economics (13.59%)
- Behavioral economics (12.62%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (9.06%)
- Machine learning (8.41%)
- Task (5.18%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Artificial intelligence, Machine learning, Task, Algorithm and Health care.
His work deals with themes such as Quality, Inference and Health records, which intersect with Machine learning.
His studies in Quality integrate themes in fields like Simplicity, Disadvantaged, Interpretability and Statistical discrimination.
His Task research integrates issues from Actuarial science, Stochastic game, Value, Counterfactual conditional and Decision rule.
His Algorithm study which covers Equity that intersects with Forcing.
The Health care study which covers MEDLINE that intersects with Mortality trends and Demography.
Between 2015 and 2021, his most popular works were:
- Dissecting racial bias in an algorithm used to manage the health of populations (464 citations)
- Inherent Trade-Offs in the Fair Determination of Risk Scores (455 citations)
- Machine Learning: An Applied Econometric Approach (398 citations)
In his most recent research, the most cited papers focused on:
- Law
- Statistics
- Artificial intelligence
His primary scientific interests are in Artificial intelligence, Machine learning, Health care, MEDLINE and Algorithm.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in Criminal justice, Recommender system, Boolean function and As is.
His Machine learning research incorporates themes from Simplicity, Unmeasured confounding and Inference.
His biological study spans a wide range of topics, including Socioeconomics, Revenue and Financial health.
His MEDLINE study combines topics from a wide range of disciplines, such as Demography and Mortality trends.
Sendhil Mullainathan integrates many fields, such as Framingham Risk Score and engineering, in his works.
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