PeopleofSuperintelligence

Researcher

Miroslav Dudík

Also known as Miro Dudík, Miroslav Dudı́k, Miro Dudik, Miroslav Dudik

Miroslav Dudík is a machine-learning researcher whose work spans contextual bandits and algorithmic fairness. He earned a Princeton PhD in 2007 and taught machine learning at Carnegie Mellon in 2009. In 2011, he coauthored an efficient contextual-bandit algorithm and served as AISTATS’s Proceedings Chair; his 2015 paper extended pairwise policy learning with context. At Microsoft Research, he wrote about contextual-bandit personalization in 2017 and started Fairlearn, which adopted community governance in 2021. He coauthored a 2023 paper on Fairlearn’s AI-fairness tools and a June 2026 paper on curriculum learning; as of October 2026, he is a Sr Principal Researcher Manager at Microsoft Research’s New York City lab.

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Timeline

  1. 2007–2009

    A Princeton PhD and CMU teaching

    He earns his PhD from Princeton in 2007. At Carnegie Mellon University’s School of Computer Science, he teaches the 10-601 Machine Learning course in fall 2009.

  2. 2011

    Efficient Optimal Learning for Contextual Bandits

    In 2011, he coauthors Efficient Optimal Learning for Contextual Bandits, which presents an efficient algorithm with optimal regret. At AISTATS in 2011, he serves as Proceedings Chair at Yahoo! Research.

  3. 2015

    Contextual Dueling Bandits

    In 2015, he coauthors Contextual Dueling Bandits, which extends pairwise-choice learning with context and studies policy selection from relative comparisons.

  4. December 2017

    Contextual-bandit personalization

    In December 2017, he writes about contextual bandits as interactive machine learning for personalized content. He describes uses in news recommendation, advertising, mobile health and digital assistants.

  5. 2018

    Starting Fairlearn

    Fairlearn starts in 2018 as a Microsoft Research Python package he creates to accompany research on fair classification.

  6. 2021

    Fairlearn community governance

    Fairlearn adopts neutral governance in 2021 and becomes a community-driven project.

  7. 2023

    Fairness assessment with Fairlearn

    In 2023, he coauthors the JMLR paper Fairlearn: Assessing and Improving Fairness of AI Systems, which describes an open-source project to assess and improve AI fairness.

  8. As of October 2026

    Sr Principal Researcher Manager

    In June 2026, he coauthors Learning to Reason with Curriculum II: Compositional Generalization. As of October 2026, he is a Sr Principal Researcher Manager at Microsoft Research’s New York City lab.

Career

  1. NowMicrosoft ResearchSr Principal Researcher Manager
  2. 2011YahooProceedings Chair
  3. 2009Carnegie Mellon University

Education

  1. 2007Princeton UniversityPhD

From the biography.

  1. Among employers with 30+ full-time cases, OpenAI leads primary technical role H-1B pay at $310,000, and Amazon, Google and Microsoft file 57% of all casesIncludes Microsoft. Across 440,669 certified US H-1B filings from 44 employers (FY2020–FY2026), OpenAI leads primary technical role base pay at $310,000 and xAI leads overall base pay at $290,000.
  2. Google had the most people shaping AI every year from 2014 to 2025Includes Microsoft. Our estimates of which organizations employed the most people shaping AI each year from 1955 to 2025, tracing the shift from university labs to companies.
  3. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes Microsoft. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  4. Google has the highest combined h-index among AI organizationsIncludes Microsoft. We estimate that Google holds the highest combined h-index at 8,016, while universities account for 73% of the deduplicated total across AI organizations.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Miroslav Dudík yet. Send us a free-licensed photo.

  1. Miro Dudík at Microsoft Research microsoft.com. Checked 21 October 2026.
  2. 10-601 Machine Learning Fall 2009 cs.cmu.edu. Checked 21 October 2026.
  3. Efficient Optimal Learning for Contextual Bandits proceedings.mlr.press. Checked 21 October 2026.
  4. Organizers | Artificial Intelligence and Statistics Conference aistats.org. Checked 21 October 2026.
  5. Contextual Dueling Bandits proceedings.mlr.press. Checked 21 October 2026.
  6. ‘Contextual bandit’ breakthrough enables deeper personalization - Microsoft Research microsoft.com. Checked 21 October 2026.
  7. About Us — Fairlearn 0.12.0 documentation fairlearn.org. Checked 21 October 2026.
  8. Fairlearn: Assessing and Improving Fairness of AI Systems jmlr.org. Checked 21 October 2026.
  9. Miro Dudík at Microsoft Research microsoft.com. Checked 21 October 2026.