World's Best Scientists 2026 revealed!

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Computer Science

D-Index
35
Citations
32814
World Ranking
11412
National Ranking
4688

Research.com Recognitions

  • 1997 - Fellow of American Physical Society (APS) Citation For sustained contributions to the fields of microscience and machine learning by increasing scientific understanding and by developing technology and applying it to systems with commercial and industrial significance
  • 1992 - IEEE Fellow For leadership in the applications of neural networks to pattern recognition and in the development of electronic systems implementing neural networks.

Overview

Lawrence D. Jackel is affiliated with the Toyota Research Institute in the United States. Their research contributions span the fields of microscience and machine learning, with particular emphasis on increasing scientific understanding and the development of technology applied to systems of commercial and industrial significance.

Jackel has been recognized with two major professional distinctions during their career. They were named a Fellow of the American Physical Society (APS) in 1997 for sustained contributions to the combined areas of microscience and machine learning. The citation highlighted their role in advancing scientific knowledge and applying this knowledge to real-world technological systems.

Earlier, in 1992, Jackel was honored as an IEEE Fellow. This award was given for leadership in applying neural networks to pattern recognition as well as for developing electronic systems that implement these neural networks. These contributions reflect a focus on both theoretical and practical aspects of neural network technology within electronic hardware frameworks.

The scientist's work integrates interdisciplinary approaches, linking physical sciences with computational methods. Their expertise lies in areas involving neural networks, pattern recognition, and their application to electronic and industrial systems.

Best Publications

  • Backpropagation applied to handwritten zip code recognition

    Y. LeCun;B. Boser;J. S. Denker;D. Henderson

  • Handwritten Digit Recognition with a Back-Propagation Network

    Yann LeCun;Bernhard E. Boser;John S. Denker;John S. Denker;Donnie Henderson

  • End to End Learning for Self-Driving Cars

    Mariusz Bojarski;Davide Del Testa;Daniel Dworakowski;Bernhard Firner

  • Comparison of classifier methods: a case study in handwritten digit recognition

    L. Bottou;C. Cortes;C. Cortes;J.S. Denker;J.S. Denker;H. Drucker;H. Drucker

  • Learning algorithms for classification: A comparison on handwritten digit recognition

    Yann Lecun;L.D. Jackel;Leon Bottou;Leon Bottou;Corinna Cortes;Corinna Cortes

  • Comparison of learning algorithms for handwritten digit recognition

    Yann Lecun;L.D. Jackel;Leon Bottou;Leon Bottou;A. Brunot

  • Handwritten digit recognition: applications of neural network chips and automatic learning

    Y. Le Cun;L.D. Jackel;B. Boser;J.S. Denker

  • Large Automatic Learning, Rule Extraction, and Generalization.

    John S. Denker;Daniel B. Schwartz;Ben S. Wittner;Sara A. Solla

  • Boosting and other ensemble methods

    Harris Drucker;Corinna Cortes;L. D. Jackel;Yann LeCun

  • Explaining How a Deep Neural Network Trained with End-to-End Learning Steers a Car

    Mariusz Bojarski;Philip Yeres;Anna Choromanska;Krzysztof Choromanski

  • VLSI implementation of a neural network memory with several hundreds of neurons

    H. P. Graf;L. D. Jackel;R. E. Howard;B. Straughn

  • Superconducting junctions utilizing a binary semiconductor barrier

    Evelyn L. Hu;Lawrence D. Jackel

  • VLSI implementation of a neural network model

    Hans P. Graf;Lawrence D. Jackel;Wayne E. Hubbard

  • An analog neural network processor with programmable topology

    B.E. Boser;E. Sackinger;J. Bromley;Y. Le Cun

  • Neural Network Recognizer for Hand-Written Zip Code Digits

    John S. Denker;W. R. Gardner;Hans Peter Graf;Donnie Henderson

  • Application of the ANNA neural network chip to high-speed character recognition

    E. Sackinger;B.E. Boser;J. Bromley;Y. LeCun

  • Learning Curves: Asymptotic Values and Rate of Convergence

    Corinna Cortes;L. D. Jackel;Sara A. Solla;Vladimir Vapnik

  • Image skeletonization method

    John S. Denker;Hans P. Graf;Donnie Henderson;Richard E. Howard

  • Hierarchical constrained automatic learning network for character recognition

    John S. Denker;Richard E. Howard;Lawrence D. Jackel;Yann Lecun

  • Method and apparatus for remotely controlling telephone call-forwarding

    Ronald J. Brachman;Donnie Henderson;Lawrence David Jackel;Frederick Kenneth Schmidt

Frequent Co-Authors

Richard Howard
Richard Howard Rutgers, The State University of New Jersey
John S. Denker
John S. Denker Nokia (United States)
Hans Peter Graf
Hans Peter Graf NEC (United States)
Bernhard E. Boser
Bernhard E. Boser University of California, Berkeley
Yann LeCun
Yann LeCun Facebook (United States)
Harold G. Craighead
Harold G. Craighead Cornell University
Henry S. Baird
Henry S. Baird Lehigh University
Corinna Cortes
Corinna Cortes Google (United States)
Isabelle Guyon
Isabelle Guyon University of Paris-Saclay
Sara A. Solla
Sara A. Solla Northwestern University

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