PeopleofSuperintelligence

Researcher

Jonathan Krause

Also known as Jon Krause

Jonathan Krause is a researcher at Google who works on health AI, with a long run of work on deep learning for diabetic eye disease. He began a PhD in the Stanford Computer Vision Lab in 2011, coauthored the ImageNet Large Scale Visual Recognition Challenge paper, and finished a 2016 thesis on fine-grained recognition advised by Fei-Fei Li. At Google, he was first author of a 2018 Ophthalmology study showing that a small set of adjudicated diabetic retinopathy grades substantially improves a deep learning model. Later papers include Med-Gemini in 2024 and a 2025 study of a retinopathy algorithm deployed at Aravind Eye Hospital in India.

Works
65
Citations
48,391
h-index
25
Badges

Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

  1. 2011–2013

    Fine-grained cars at Stanford

    He begins a PhD in the Stanford Computer Vision Lab in 2011. In 2013, he presents '3D Object Representations for Fine-Grained Categorization' with Michael Stark, Jia Deng and Li Fei-Fei at an ICCV 2013 workshop, along with a paper on collecting a large-scale dataset of fine-grained cars.

  2. 2013–2015

    The ImageNet challenge paper

    A member of the ImageNet research team, he helps organize ILSVRC 2013 and ILSVRC 2014. With Olga Russakovsky, Jia Deng, Andrej Karpathy, Li Fei-Fei and others, he coauthors 'ImageNet Large Scale Visual Recognition Challenge', first posted in September 2014, which describes a benchmark for object classification and detection across hundreds of categories and millions of images.

  3. 2015–2016

    Learning from noisy web data

    With Benjamin Sapp, Andrew Howard, Li Fei-Fei and other coauthors, he writes 'The Unreasonable Effectiveness of Noisy Data for Fine-Grained Recognition', first posted in November 2015 and presented at ECCV 2016. The approach uses free, noisy web data and simple, generic recognition methods, and reports first results at more than 10,000 fine-grained categories.

  4. 2016

    A thesis on fine-grained recognition

    He completes his Stanford PhD in the Computer Science Department in 2016 with the thesis 'Fine-grained recognition: data, recognition, and application'. Fei-Fei Li is his primary advisor, with Stefano Ermon and Silvio Savarese as thesis advisors, and the work covers four fine-grained recognition projects and an application to understanding society from images. He then moves on to Google Brain.

  5. 2017

    Street View cars and image paragraphs

    With Timnit Gebru, Li Fei-Fei and others, he coauthors a 2017 study that identifies the make, model and year of cars in 50 million Google Street View images from 200 American cities to estimate income, race, education and voting patterns. He also presents 'A Hierarchical Approach for Generating Descriptive Image Paragraphs' with Justin Johnson, Ranjay Krishna and Li Fei-Fei at CVPR 2017.

  6. 2017–2018

    Adjudicated grades for eye disease

    At Google, he is first author of a study, first posted in October 2017 and published in Ophthalmology in 2018, which finds that a small set of adjudicated diabetic retinopathy grades substantially improves a deep learning model, lifting its AUC for moderate or worse disease from 0.934 to 0.986. In December 2018, he and Rory Sayres of Google AI Healthcare describe work to improve the model's performance, explainability and clinical use, and announce a new partner, Rajavithi Hospital in Thailand.

  7. 2023–2024

    Deployment lessons and Med-Gemini

    In 2023, he coauthors 'Lessons learned from translating AI from development to deployment in healthcare' in Nature Medicine, drawn from a retinal disease screening tool used in India and Thailand. In 2024, he is a coauthor of 'Capabilities of Gemini Models in Medicine', which introduces the Med-Gemini family of multimodal medical models, and of a Nature Medicine paper on safety principles for medical summarization with generative AI.

  8. As of October 2026

    Health AI research at Google

    He is a researcher at Google working on health AI. His 2025 papers include a JAMA Network Open study of a diabetic retinopathy algorithm deployed at Aravind Eye Hospital in India and a CHI paper on an AI tutor prototype for clinical reasoning, co-designed with medical students.

Career

  1. Since 2018GoogleResearcher
  2. From 2016Google Brain

Education

  1. 2016Stanford UniversityPhD

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

Most-cited works

  1. ImageNet Large Scale Visual Recognition Challenge2015 · International Journal of Computer Vision · 38,923 citationsWith Aditya Khosla, Alexander Berg, Andrej Karpathy, Fei-Fei Li, Jia Deng and Olga Russakovsky
  2. 3D Object Representations for Fine-Grained Categorization2013 · IEEE International Conference on Computer Vision Workshops · 3,499 citationsWith Fei-Fei Li and Jia Deng
  3. Grader Variability and the Importance of Reference Standards for Evaluating Machine Learning Models for Diabetic Retinopathy2018 · Ophthalmology · 556 citationsWith Greg Corrado
  4. How to Read Articles That Use Machine Learning2019 · JAMA · 517 citations
  5. Using deep learning and Google Street View to estimate the demographic makeup of neighborhoods across the United States2017 · Proceedings of the National Academy of Sciences · 516 citationsWith Fei-Fei Li, Jia Deng and Timnit Gebru

From OpenAlex, as of 21 October 2026.

  1. The median h-index is 48 at universities and 14 at frontier AI labsIncludes Jonathan Krause. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.
  2. Google had the most people shaping AI every year from 2014 to 2025Includes Google. 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. Google has the highest combined h-index among AI organizationsIncludes Google. 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.
  4. 20% of people at companies who shape AI also hold a university role, led by Google and Stanford UniversityIncludes Google. We estimate that 539 of the 6,766 people with a known current organization (8%) hold both a university role and a company role, including 20% of people at companies and 13% of people at universities.

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. Stanford Computer Vision Lab : People cs.stanford.edu. Checked 20 October 2026.
  2. Jonathan Krause cs.stanford.edu. Checked 20 October 2026.
  3. [1409.0575] ImageNet Large Scale Visual Recognition Challenge arxiv.org. Checked 20 October 2026.
  4. [1511.06789] The Unreasonable Effectiveness of Noisy Data for Fine-Grained Recognition arxiv.org. Checked 20 October 2026.
  5. Fine-grained recognition : data, recognition, and application | Stanford Digital Repository purl.stanford.edu. Checked 20 October 2026.
  6. [1702.06683] Using Deep Learning and Google Street View to Estimate the Demographic Makeup of the US arxiv.org. Checked 20 October 2026.
  7. [1611.06607] A Hierarchical Approach for Generating Descriptive Image Paragraphs arxiv.org. Checked 20 October 2026.
  8. [1710.01711] Grader variability and the importance of reference standards for evaluating machine learning models for diabetic retinopathy arxiv.org. Checked 20 October 2026.
  9. Grader variability and the importance of reference standards for evaluating machine learning models for diabetic retinopathy research.google. Checked 20 October 2026.
  10. Improving the Effectiveness of Diabetic Retinopathy Models research.google. Checked 20 October 2026.
  11. Jonathan Krause research.google. Checked 20 October 2026.
  12. [2404.18416] Capabilities of Gemini Models in Medicine arxiv.org. Checked 20 October 2026.