David G. Stork

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David G. Stork
PortraitOfDavidGStork.png
Portrait of David G. Stork
Alma mater Massachusetts Institute of Technology
University of Maryland, College Park
Scientific career
Fields Pattern recognition, machine learning, computer vision, artificial intelligence, technical art analysis
Institutions Wellesley College
Swarthmore College
Clark University
Boston University
Stanford University
Technical University of Vienna
University College London

David G. Stork is a scientist and author, who has made contributions to machine learning, pattern recognition, computer vision, artificial intelligence, computational optics, image analysis of fine art, and related fields.

Contents

Education

Stork received his BS in Physics from the Massachusetts Institute of Technology with a thesis under the direction of Dr. Edwin H. Land, President and CEO of the Polaroid Corporation, and his MS and PhD in Physics from the University of Maryland, College Park with a thesis under the direction of David S. Falk.

Career

Stork has held full-time and visiting faculty positions in Physics, Mathematics, Computer Science, Electrical Engineering, Statistics, Neuroscience, Psychology, Materials Science and Engineering, Informatics, Computational and Mathematical Engineering, Symbolic Systems, Artificial Intelligence, and Art and Art History variously at Wellesley and Swarthmore Colleges and Clark, Boston, and Stanford Universities, the University College London, and the Technical University of Vienna.  He was a Visiting Fellow at the Warburg Institute in London. He has held corporate positions as Chief Scientist at Ricoh Innovations and Fellow at Rambus, Inc. He has served on Advisory Boards of the startup companies, NeuralWare, Neural Applications Corporation, and Metalenz. He has published over 215 peer-reviewed publications, 64 US patents, and nine books/proceedings volumes.

Stork is widely considered a founding pioneer in the application of rigorous computer vision, machine learning, and artificial intelligence to problems in the history and interpretation of fine art paintings and drawings.  He published several of the first scholarly works in the field, offered its first courses (at Stanford University), co-founded its first conference, now called Computer Vision and Analysis of Art (CVAA), [1] and published the first textbook pertaining to the field, Pixels & paintings:  Foundations of computer-assisted connoisseurship (Wiley). [2]

Memberships and awards

Stork is a Fellow of the Institute for Electrical and Electronics Engineers (IEEE), Optical Society of America (OSA)., [3] International Society for Optics and Photonics (SPIE), [4] [5] Society for Imaging Science and Technology (IS&T), International Association for Pattern Recognition (IAPR), [6] and International Academy, Research, and Industry Association (IARIA), [7] Asia-Pacific Artificial Intelligence Association, [8] International Artificial Intelligence Industry Alliance, [9] and 2023 Leonardo@Djerassi Fellow, [10] and has been Senior Member of the Association for Computing Machinery (ACM) and Member of the Association for the Advancement of Artificial Intelligence (AAAI). He was awarded the 2017 Industrial Distinguished Leader Award from the Asia Pacific Signal and Information Processing Association (APSIPA) [11]

Selected works

Related Research Articles

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References

  1. ↑ "Computer Vision and Image Analysis of Art 2024 (CVAA) - About CVAA 2024". www.imaging.org. Retrieved 2023-10-27.
  2. ↑ "Pixels & paintings: Foundations of computer-assisted connoisseurship (Wiley, 2024)". Wiley.
  3. ↑ "2016 OSA Fellows" . Retrieved 2019-12-01.
  4. ↑ "Complete List of SPIE Fellows" . Retrieved 2019-12-01.
  5. ↑ "SPIE Profile: DR. DAVID G. STORK" . Retrieved 2019-12-01.
  6. ↑ "IAPR Fellows" . Retrieved 2019-12-01.
  7. ↑ "IARIA Fellows" . Retrieved 2019-12-01.
  8. ↑ "Asia-Pacific Artificial Intelligence Association".
  9. ↑ "International Artificial Intelligence Industry Alliance ( AIIA )". www.aiia-ai.org. Retrieved 2024-03-23.
  10. ↑ djerassi.org
  11. ↑ "APSIPA Industrial Distinguished Leader Program" . Retrieved 2019-12-01.
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