2026 David G. Stork: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	50	5451	5297	2483	2398	263	66156

Research.com Recognitions

2018 - IEEE Fellow For contributions to pattern recognition and image analysis
2016 - OSA Fellows David G. Stork Rambus Inc., United States For pioneering contributions to the theory and practice of computational imaging, computer vision and pattern recognition, including their application to the study of art.
2016 - ACM Senior Member
2012 - SPIE Fellow
2008 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to pattern recognition education, machine learning, speech recognition, and the application of computer vision to the study of art.
1965 - Fellow of John Simon Guggenheim Memorial Foundation

Overview

David G. Stork is affiliated with Stanford University in the United States and has a notable record of research in computer science and neuroscience, with a focus on computer vision and pattern recognition.

Their recent scholarly work includes publications in a range of journals and conference venues. Notable papers are:

"Deep transfer learning for visual analysis and attribution of paintings by Raphael," 2023, Heritage Science
"Reducing Bias in AI-based Analysis of Visual Artworks," 2022, IEEE BITS the Information Theory Magazine
"Computer Vision, ML, and AI in the Study of Fine Art," 2024, Communications of the ACM
"Recovery of underdrawings and ghost-paintings via style transfer by deep convolutional neural networks: A digital tool for art scholars," 2021, Electronic Imaging
"Improving semantic segmentation of fine art images using photographs rendered in a style learned from artworks," 2022, Electronic Imaging

The primary publication venues for their work include:

Electronic Imaging
arXiv (Cornell University)
Leonardo
Heritage Science
IEEE BITS the Information Theory Magazine

Frequent collaborators in their research are:

Anthony Bourached
George Cann
Ryan-Rhys Griffiths
Thomas Heitzinger
Jesper Eriksson

David G. Stork's work spans several main areas of study:

Computer Science
Neuroscience

Within these, their subfields of study are:

Computer Vision and Pattern Recognition
Cognitive Neuroscience
Conservation
Computer Graphics and Computer-Aided Design
Archeology

The primary topics covered in their research include:

Aesthetic Perception and Analysis
Generative Adversarial Networks and Image Synthesis
Conservation Techniques and Studies
Image Retrieval and Classification Techniques
Multimodal Machine Learning Applications
Cultural Heritage Materials Analysis
3D Surveying and Cultural Heritage

David G. Stork has received multiple professional recognitions and fellowships, such as:

IEEE Fellow (2018) for contributions to pattern recognition and image analysis
ACM Senior Member (2016)
OSA Fellow (2016) for contributions to computational imaging, computer vision, and pattern recognition applied to art study
SPIE Fellow (2012)
Fellow of the International Association for Pattern Recognition (IAPR) (2008) for education and application of computer vision to art
Fellow of John Simon Guggenheim Memorial Foundation (1965)

Best Publications

Pattern Classification

Peter E. Hart;Richard O. Duda;David G. Stork

48339
Citations
Pattern Classification (2nd ed.)

Richard O. Duda;Peter E. Hart;David G. Stork

3404
Citations
Second order derivatives for network pruning: Optimal Brain Surgeon

Babak Hassibi;David G. Stork

2091
Citations
Pattern Classification (2nd Edition)

Richard O. Duda;Peter E. Hart;David G. Stork

1994
Citations
ELECTRONIC DOCUMENT HANDLING SYSTEM, ELECTRONIC DOCUMENT HANDLING METHOD, AND WRITING INSTRUMENT

Gregg Wolf;Stork David G

1028
Citations
Optimal Brain Surgeon and general network pruning

B. Hassibi;D.G. Stork;G.J. Wolff

820
Citations
Content based web advertising

Jamey Graham;David G. Stork

489
Citations
INFORMATION PROCESSOR AND METHOD FOR RETRIEVING DOCUMENT

Graham Jamey;Stork David G

360
Citations
Speechreading by Man and Machine: Models, Systems, and Applications

David G. Stork;Marcus E. Hennecke

300
Citations
Calibration of a system for tracking a writing instrument with multiple sensors

David G. Stork;Michael Angelo;Gregory J. Wolff

275
Citations
Speechreading by Humans and Machines

David G. Stork;Marcus E. Hennecke

255
Citations
The Physics and Chemistry of Color: The Fifteen Causes of Color

Kurt Nassau;David G. Stork

239
Citations
SPEECH RECOGNITION AND SENSORY INTEGRATION

Dominic W. Massaro;David G. Stork

228
Citations
Speech Recognition and Sensory Integration A 240-year-old theorem helps explain how people and machines can integrate auditory and visual information to understand speech

Dominic W. Massaro;David G. Stork

224
Citations
Hal's Legacy: 2001's Computer as Dream and Reality

David G. Stork;Arthur Charles Clarke

222
Citations
Facial feature extraction method and apparatus for a neural network acoustic and visual speech recognition system

K. Venkatesh Prasad;David G. Stork

213
Citations
Neural network lipreading system for improved speech recognition

D.G. Stork;G. Wolff;E. Levine

202
Citations
Optimal Brain Surgeon: Extensions and performance comparisons

Babak Hassibi;David G. Stork;Gregory Wolff

184
Citations
Visionary Speech: Looking Ahead to Practical Speechreading Systems

Marcus E. Hennecke;David G. Stork;K. Venkatesh Prasad

183
Citations
Method, system and computer code for content based web advertising

Jamey Graham;David G. Stork;Chuck Lam

166
Citations

Frequent Co-Authors

Gregory J. Wolff UnaMesa Association

Jamey Graham Ricoh (Japan)

Peter E. Hart Independent Scientist / Consultant, US

Michael J. Gormish Clarifai

Marco F. Duarte University of Massachusetts Amherst

Rob van Glabbeek Stanford University

Babak Hassibi California Institute of Technology

Antonio Criminisi Microsoft (United States)

Dominic W. Massaro University of California, Santa Cruz

Aggelos K. Katsaggelos Northwestern University

External Links

Wikipedia of David G. Stork Personal website of David G. Stork Google Scholar page

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