PeopleofSuperintelligence

Researcher

Alina Beygelzimer

Alina Beygelzimer is a machine-learning researcher whose work spans active learning, contextual bandits, online boosting, and memory systems for machine learning. She completed a computer science thesis at Rochester Institute of Technology in 1999 and earned a PhD in computer science from the University of Rochester in 2003. Her papers developed methods for active learning and contextual bandits, algorithms for online boosting and machine-learning memory, and she served as a Program Co-chair for NeurIPS 2021. In 2023 and 2024, she coauthored studies of disagreement in conference reviews and of how authors judge the scientific contribution of their papers. She is a Principal Research Scientist at Yahoo Research and serves on COLT's 2026 Senior Program Committee.

Links
Website

Timeline

  1. 1999–2003

    Geometry thesis and PhD

    In 1999, she completes a computer science thesis on extremal problems in geometry at Rochester Institute of Technology. She earns a PhD in computer science from the University of Rochester in 2003.

  2. 2006–2009

    Active learning at ICML and IBM

    At ICML in 2006, she coauthors “Agnostic Active Learning” with Maria-Florina Balcan and John Langford. In 2009, she coauthors “Importance Weighted Active Learning” with Sanjoy Dasgupta and John Langford; the paper presents a practical, statistically consistent method for learning binary classifiers under general loss functions.

  3. 2011

    A contextual bandit algorithm

    In 2011, she coauthors “Contextual Bandit Algorithms with Supervised Learning Guarantees” with John Langford, Lihong Li, Lev Reyzin, and Robert Schapire. The paper presents Exp4.P, an algorithm for contextual-bandit learning with high-probability regret guarantees.

  4. 2015

    An ICML Best Paper

    In 2015, she coauthors “Optimal and Adaptive Algorithms for Online Boosting” with Satyen Kale and Haipeng Luo. The paper develops two algorithms that convert weak online learners into strong online learners and receives an ICML Best Paper Award.

  5. 2019

    Contextual Memory Trees

    At ICML in 2019, she coauthors “Contextual Memory Trees,” a learning controller that inserts memories into an unbounded experience store. It supports logarithmic-time insertion and retrieval and can augment statistical learning algorithms.

  6. 2021

    NeurIPS program co-chair

    At NeurIPS 2021, she is a Program Co-chair and a Senior Research Scientist at Yahoo Research.

  7. 2023–2024

    Two studies of peer review

    In 2023, she coauthors a study of the NeurIPS 2021 review process that finds two independent committees disagree on accept-or-reject recommendations for 23% of papers. In 2024, she coauthors a PLOS One study that surveys NeurIPS 2021 authors about predicted acceptance, their rankings of their papers by scientific contribution, and how reviews change their views.

  8. As of October 2026

    Principal scientist at Yahoo

    As of October 2026, she is a Principal Research Scientist at Yahoo Research in New York, where she works on machine learning and algorithms. In 2026, she serves on COLT's Senior Program Committee.

Career

  1. YahooSenior Research Scientist

Education

  1. 2003University of RochesterPhD in computer science
  2. 1999Rochester Institute of Technology

From the biography.

  1. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes Alina Beygelzimer. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  2. Universities keep AI researchers for a median of 6 years, compared with 2 years at frontier labsIncludes Yahoo. Across 15,811 dated work stays (6,529 people), median role tenure runs from 6 years at universities to 2 years at frontier labs. We compare all five organization types, starting decades from the 1970s to the 2020s, and the organizations that keep people longest.
  3. 23% of people shaping AI who left a university for a company later returned to a universityIncludes Yahoo. We estimate that 468 of the 2,011 people shaping AI who left a university for a company (23%) later returned to a university after a median of 5 years, and 163 of 829 (20%) made the reverse round trip.
  4. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes Yahoo. 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.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

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  1. Combinatorial computing approach to selected extremal problems in geometry by Alina Beygelzimer repository.rit.edu. Checked 21 October 2026.
  2. KDD 2010: Tutorials kdd.org. Checked 21 October 2026.
  3. ICML 2006 Proceedings icml.cc. Checked 21 October 2026.
  4. Importance weighted active learning for ICML 2009 - IBM Research research.ibm.com. Checked 21 October 2026.
  5. Contextual Bandit Algorithms with Supervised Learning Guarantees proceedings.mlr.press. Checked 21 October 2026.
  6. Optimal and Adaptive Algorithms for Online Boosting proceedings.mlr.press. Checked 21 October 2026.
  7. Awards | ICML Lille icml.cc. Checked 21 October 2026.
  8. Contextual Memory Trees proceedings.mlr.press. Checked 21 October 2026.
  9. OpenReview NeurIPS 2021 Summary Report docs.openreview.net. Checked 21 October 2026.
  10. Has the Machine Learning Review Process Become More Arbitrary as the Field Has Grown? The NeurIPS 2021 Consistency Experiment arxiv.org. Checked 21 October 2026.
  11. How do authors’ perceptions of their papers compare with co-authors’ perceptions and peer-review decisions? journals.plos.org. Checked 21 October 2026.
  12. Alina Beygelzimer hunch.net. Checked 21 October 2026.
  13. COLT 2026 - Program Committee learningtheory.org. Checked 21 October 2026.