The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Ekin D. Cubuk sits on this spectrum.
This scientist: 129 publications — 18th percentile
18% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 804 publications or more.
The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Ekin D. Cubuk sits on this spectrum.
This scientist: 52 D-Index — 64th percentile
64% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 107 D-Index or more.
Ekin D. Cubuk is affiliated with Google in the United States. Their research spans multiple fields, with a strong focus on computer science and materials science. The subfields that characterize their work include materials chemistry, artificial intelligence, computer vision and pattern recognition, electrical and electronic engineering, and atomic and molecular physics and optics.
The scientist's recent publications illustrate the diversity and depth of their research interests. Selected papers include:
The scientist has collaborated frequently with several coauthors. The most prominent among these are Samuel S. Schoenholz, Barret Zoph, Amil Merchant, Quoc V. Le, and Simon Batzner. These collaborations have contributed to a wide range of studies, particularly in machine learning approaches applied to material sciences and computer vision.
Several venues regularly publish their work, reflecting their active engagement with the academic community in both foundational and applied research. The main publication venues include:
The main topics covered by their work reflect the intersection of machine learning and materials science as well as advanced imaging and analysis techniques. These topics include:
The scope of Ekin D. Cubuk's research positions them at the crossroads of computational methods and experimental materials research, addressing challenges in both data-driven modeling and practical material characterization. The combination of AI techniques with materials chemistry underlines a multidisciplinary approach that is evident through the diverse fields, topics, and publication outlets involved in their body of work.
Daniel S. Park;William Chan;Yu Zhang;Chung-Cheng Chiu
Ekin Dogus Cubuk;Barret Zoph;Jon Shlens;Quoc Le
Ekin D. Cubuk;Barret Zoph;Dandelion Mane;Vijay Vasudevan
Kihyuk Sohn;David Berthelot;Chun-Liang Li;Zizhao Zhang
Kihyuk Sohn;David Berthelot;Chun-Liang Li;Zizhao Zhang
Ekin Dogus Cubuk;Barret Zoph;Dandelion Mane;Vijay Vasudevan
Unknown
Avital Oliver;Augustus Odena;Colin A. Raffel;Ekin Dogus Cubuk
Golnaz Ghiasi;Yin Cui;Aravind Srinivas;Rui Qian
Dan Hendrycks;Norman Mu;Ekin Dogus Cubuk;Barret Zoph
Barret Zoph;Ekin D. Cubuk;Golnaz Ghiasi;Tsung-Yi Lin
Samuel S. Schoenholz;Ekin D. Cubuk;Daniel M. Sussman;Efthimios Kaxiras
Dan Hendrycks;Norman Mu;Ekin D. Cubuk;Barret Zoph
E. D Cubuk;Samuel Schoenholz;Jennifer M Rieser;B. D Malone
David Berthelot;Nicholas Carlini;Ekin D. Cubuk;Alex Kurakin
Austin D. Sendek;Qian Yang;Ekin D. Cubuk;Karel-Alexander N. Duerloo
Austin D. Sendek;Qian Yang;Ekin D. Cubuk;Karel-Alexander N. Duerloo
Barret Zoph;Golnaz Ghiasi;Tsung-Yi Lin;Yin Cui
Yi Cui;Jin Xie
Barret Zoph;Golnaz Ghiasi;Tsung-Yi Lin;Yin Cui
V. Bapst;T. Keck;A. Grabska-Barwińska;C. Donner
Unknown
Austin D. Sendek;Ekin D. Cubuk;Ekin D. Cubuk;Evan R. Antoniuk;Gowoon Cheon
Ekin Dogus Cubuk;Robert Ivancic;Samuel S. Schoenholz;Samuel S. Schoenholz;Danny Strickland
Ekin D. Cubuk;Barret Zoph;Jonathon Shlens;Quoc V. Le
Dong Yin;Raphael Gontijo Lopes;Jonathon Shlens;Ekin D. Cubuk
David Berthelot;Nicholas Carlini;Ekin D. Cubuk;Alex Kurakin
Justin Gilmer;Nicolas Ford;Nicholas Carlini;Ekin D. Cubuk
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