PeopleofSuperintelligence

Researcher

Henry A. Rowley

Also known as Henry Rowley, Henry Allan Rowley

Henry Rowley is a computer vision researcher at Google whose Carnegie Mellon work on neural network face detection won the 2006 Longuet-Higgins Prize. With Shumeet Baluja and his advisor Takeo Kanade, he built a system in which a retinally connected neural network scans small image windows for faces, and he completed his PhD on it in 1999. After jobs at Zaxel Systems and at Microsoft, where he worked on Chinese, Japanese and Korean handwriting recognition, he coauthored a 2006 adult-content image filter that ran in a web image search engine. At Google he was part of the handwriting team that brought handwriting input to 82 languages on Android in 2015 and coauthored an LSTM recognizer for 102 languages in 2019, and in 2016 he helped build the drawing game Quick, Draw! Today he is a member of the Google Research group, where his recent work centers on handwriting recognition.

Timeline

  1. 1992–1994

    Degrees at Minnesota and Carnegie Mellon

    He earns BS degrees in electrical engineering and computer science from the University of Minnesota in 1992. In 1994, he completes a master's in computer science at Carnegie Mellon University.

  2. 1995–1999

    Neural network face detection

    In 1995, he presents “Human Face Detection in Visual Scenes” at NIPS with Shumeet Baluja and Takeo Kanade; a retinally connected neural network examines small windows of an image and decides whether each one contains a face. He completes his PhD thesis, “Neural Network-Based Face Detection,” in May 1999 in the VASC group of Carnegie Mellon's Computer Science Department, with Kanade as his advisor. After graduating, he works at Zaxel Systems on lossless video compression and multi-view stereo reconstruction, and at Microsoft on Chinese, Japanese and Korean handwriting recognition.

  3. 2006

    The Longuet-Higgins Prize

    In 2006, he and Shumeet Baluja, both at Google, share the Longuet-Higgins Prize with CMU professor Takeo Kanade for their 1996 paper “Neural Network-Based Face Detection.” The award, given at the 2006 CVPR conference, honors a contribution that has stood the test of time.

  4. 2006–2011

    Web image filtering and annotation

    In 2006, he coauthors an adult-content image filter with Yushi Jing and Shumeet Baluja that combines face detection with a support vector machine and runs in a search engine covering a large fraction of the images on the web. In 2011, he coauthors an ICCV paper on annotating web images with visual synsets, tested on a database of more than 200 million images.

  5. 2015–2016

    Google Handwriting Input

    In April 2015, he and his colleagues on the Google Research handwriting team announce Google Handwriting Input for Android in 82 languages. In 2016, the team describes the recognizer in IEEE Transactions on Pattern Analysis and Machine Intelligence: it supports 22 scripts and 97 languages and runs in Google Translate and as an Android input method.

  6. 2016

    Building Quick, Draw!

    Released in November 2016, Quick, Draw! is a game from Google Creative Lab and the Data Arts Team in which a neural network tries to guess what a player is drawing. He is one of its builders, alongside Jonas Jongejan, Takashi Kawashima, Jongmin Kim and Nick Fox-Gieg.

  7. 2019–2020

    LSTM handwriting in 102 languages

    In February 2019, he and nine coauthors describe an LSTM-based online handwriting recognizer that supports 102 languages with one deep neural network architecture and replaces the team's earlier segment-and-decode system. The handwriting team launches RNN-based handwriting recognition in Gboard in 2019, and the paper appears in the International Journal on Document Analysis and Recognition in 2020.

  8. As of October 2026

    Handwriting research at Google

    In February 2022, he coauthors Inkorrect, a data- and label-efficient method for spelling correction in digital ink, with Andrii Maksai, Jesse Berent and Claudiu Musat. He is a member of the Google Research group, where he works on computer vision, machine learning and, most recently, handwriting recognition.

  1. Google had the most people shaping AI every year from 2014 to 2025Our estimates of which organizations employed the most people shaping AI from 1961 to 2025, with a year-by-year chart.
  2. The United States employs an estimated 53% of people in our data with a known employment countryOur estimates of where AI careers are concentrated now and how countries’ shares of dated positions changed over time.
  3. 46% of living people in our data with known birth and employment countries work outside their birth countryOur estimate of cross-border careers in AI, from country of birth and the country of each current organization.
  4. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionOur estimates of where the people shaping AI studied and where their careers led, from education records in cited biographies.

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. Henry A. Rowley research.google. Checked 19 October 2026.
  2. Human Face Detection in Visual Scenes papers.nips.cc. Checked 19 October 2026.
  3. Henry Rowley's Home Page cs.cmu.edu. Checked 19 October 2026.
  4. Neural Network-Based Face Detection - Robotics Institute Carnegie Mellon University ri.cmu.edu. Checked 19 October 2026.
  5. Henry Rowley - The Mathematics Genealogy Project mathgenealogy.org. Checked 19 October 2026.
  6. And the Awards Go To ... research.google. Checked 19 October 2026.
  7. Large Scale Image-Based Adult-Content Filtering – SCITEPRESS scitepress.org. Checked 19 October 2026.
  8. Google Handwriting Input in 82 languages on your Android mobile device research.google. Checked 19 October 2026.
  9. Quick, Draw! by Google Creative Lab - Experiments with Google experiments.withgoogle.com. Checked 19 October 2026.
  10. Quick, Draw! - Wikipedia en.wikipedia.org. Checked 19 October 2026.
  11. [1902.10525] Fast Multi-language LSTM-based Online Handwriting Recognition arxiv.org. Checked 19 October 2026.
  12. [2202.13794] Inkorrect: Online Handwriting Spelling Correction arxiv.org. Checked 19 October 2026.