The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where David D. Cox sits on this spectrum.
This scientist: 121 publications — 15th percentile
15% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 991 publications or more.
The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where David D. Cox sits on this spectrum.
This scientist: 53 D-Index — 67th percentile
67% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 131 D-Index or more.
David D. Cox is affiliated with IBM in the United States and has contributed extensively to the field of computer science, particularly focusing on artificial intelligence and cognitive neuroscience. Their research spans multiple subfields, including artificial intelligence, cognitive neuroscience, computer vision and pattern recognition, signal processing, and cellular and molecular neuroscience.
The scientist's work covers key topics such as neural dynamics and brain function, adversarial robustness in machine learning, multimodal machine learning applications, topic modeling, speech recognition and synthesis, speech and audio processing, and natural language processing techniques.
David D. Cox has published numerous articles in leading venues, with a concentration of work appearing in arXiv (Cornell University) and bioRxiv (Cold Spring Harbor Laboratory). Other publication venues include The New Scientist, JAMA Network Open, and Nature Machine Intelligence.
Frequent collaborators in their research include Rameswar Panda, Shiyu Chang, Javier Masís, Rogério Feris, and Kaizhi Qian. This network of co-authors indicates a collaborative approach across various topics within computer science and neuroscience.
The scientist's main fields of study emphasize computational and cognitive approaches in understanding neural functions and advancing machine learning techniques. Their work interlinks the development of artificial intelligence with insights from brain research, particularly focusing on enhancing robustness and multimodal learning capabilities.
James Bergstra;Daniel Yamins;David Cox
David D Cox;Robert L Savoy
Stephanie Lowry;Niko Sunderhauf;Paul Newman;John J. Leonard
James J. DiCarlo;David D. Cox
James Bergstra;Brent Komer;Chris Eliasmith;Dan Yamins
James Bergstra;Dan Yamins;David D. Cox
Nicolas Pinto;David Daniel Cox;David Daniel Cox;David Daniel Cox;James J DiCarlo;James J DiCarlo
William Edward Lotter;Gabriel Kreiman;David Daniel Cox
Andrew M Saxe;Yamini Bansal;Joel Dapello;Madhu Advani
Eleonora Vig;Michael Dorr;David Cox
Thomas Schaffter;Diana S. M. Buist;Christoph I. Lee;Yaroslav Nikulin
Nicolas Pinto;Nicolas Pinto;David Doukhan;David Doukhan;James J. DiCarlo;James J. DiCarlo;David Daniel Cox;David Daniel Cox;David Daniel Cox
Lilianne R. Mujica-Parodi;Helmut H. Strey;Blaise DeBonneval Frederick;Robert L. Savoy
Nicolas Pinto;James J DiCarlo;David D Cox
David Cox;Nicolas Pinto
Davide Zoccolan;David D. Cox;James J. DiCarlo
David Daniel Cox;Thomas Dean
Hanlin Tang;Martin Schrimpf;William Lotter;Charlotte Moerman
Oliver Skocek;Tobias Nöbauer;Lukas Weilguny;Francisca Martínez Traub
David Cox;Ethan Meyers;Pawan Sinha
Philippe Tillet;H. T. Kung;David Cox
Nicolas Pinto;David Doukhan;James J. DiCarlo;David D. Cox
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Natural Environment Research Council
