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Nova · Professor Researcher · re-ranking top 20…
Sendhil Mullainathan

Sendhil Mullainathan

Verified

Massachusetts Institute of Technology · Electrical Engineering & Computer Science

Active 1993–2024

h-index108
Citations80.1k
Papers38571 last 5y
Funding
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Research topics

  • Computer Science
  • Artificial Intelligence
  • Medicine
  • Mathematics
  • Machine Learning
  • Data Mining
  • Psychology
  • Nursing
  • Applied psychology
  • Management science
  • Environmental health
  • Algorithm
  • Data science
  • Business
  • Advertising
  • Social psychology
  • Econometrics
  • Virology
  • Mathematical economics
  • Family medicine

Selected publications

  • A 680,000-person megastudy of nudges to encourage vaccination in pharmacies

    Proceedings of the National Academy of Sciences · 2022 · 191 citations

    • Computer Science
    • Artificial Intelligence
    • Medicine

    Encouraging vaccination is a pressing policy problem. To assess whether text-based reminders can encourage pharmacy vaccination and what kinds of messages work best, we conducted a megastudy. We randomly assigned 689,693 Walmart pharmacy patients to receive one of 22 different text reminders using a variety of different behavioral science principles to nudge flu vaccination or to a business-as-usual control condition that received no messages. We found that the reminder texts that we tested increased pharmacy vaccination rates by an average of 2.0 percentage points, or 6.8%, over a 3-mo follow-up period. The most-effective messages reminded patients that a flu shot was waiting for them and delivered reminders on multiple days. The top-performing intervention included two texts delivered 3 d apart and communicated to patients that a vaccine was "waiting for you." Neither experts nor lay people anticipated that this would be the best-performing treatment, underscoring the value of simultaneously testing many different nudges in a highly powered megastudy.

  • Measuring the Completeness of Economic Models

    Journal of Political Economy · 2021 · 51 citations

    Senior authorCorresponding
    • Computer Science
    • Data Mining
    • Econometrics

    Economic models are evaluated by testing the correctness of their predictions. We suggest an additional measure, “completeness”: the fraction of the predictable variation in the data that the model captures. We calculate the completeness of prominent models in three problems from experimental economics: assigning certainty equivalents to lotteries, predicting initial play in games, and predicting human generation of random sequences. The completeness measure reveals new insights about these models, including how much room there is for improving their predictions.

  • Integrating explanation and prediction in computational social science

    Nature · 2021 · 357 citations

    • Computer Science
    • Computer Science
    • Data science
  • Megastudies improve the impact of applied behavioural science

    Nature · 2021 · 254 citations

    • Psychology
    • Applied psychology
    • Medicine

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