Ekin D. Cubuk

19.8k citations

59 papers · 7.8k indexed · 5 hit papers · h-index 29

Materials Chemistry top 1%
Artificial Intelligence top 0.2%
Signal Processing top 0.2%
Computer Vision and Pattern Recognition top 0.5%
Electrical and Electronic Engineering top 5%

Co-authors: Barret Zoph Quoc V. Le Samuel S. Schoenholz William Chan Daniel Park Chung‐Cheng ChiuYu ZhangVijay Vasudevan
Topics: Machine Learning in Materials Science (22 papers)Advanced Neural Network Applications (10 papers)Domain Adaptation and Few-Shot Learning (8 papers)
Cited by: Signal Processing Artificial Intelligence Computer Vision and Pattern Recognition
Journals: Nature Proceedings of the National Academy of Sciences Journal of the American Chemical Society
Partner nations: United States United Kingdom China

In The Last Decade

Ekin D. Cubuk

58 papers receiving 7.5k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition

2019 2.1k citations Barret Zoph, Ekin D. Cubuk et al. arXiv (Cornell University) profile →
AutoAugment: Learning Augmentation Strategies From Data

2019 1.5k citations Ekin D. Cubuk, Barret Zoph et al. profile →
Scaling deep learning for materials discovery

2023 667 citations Amil Merchant, Simon Batzner et al. Nature profile →
An autonomous laboratory for the accelerated synthesis of inorganic materials

2023 451 citations Nathan J. Szymanski, Bernardus Rendy et al. Nature profile →
Unveiling the predictive power of static structure in glassy systems

2020 230 citations Ekin D. Cubuk, Samuel S. Schoenholz et al. profile →

Peers

Countries citing papers authored by Ekin D. Cubuk

Since Specialization

Citations

This map shows the geographic impact of Ekin D. Cubuk's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ekin D. Cubuk with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ekin D. Cubuk more than expected).

Fields of papers citing papers by Ekin D. Cubuk

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ekin D. Cubuk. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ekin D. Cubuk. The network helps show where Ekin D. Cubuk may publish in the future.

Co-authorship network of co-authors of Ekin D. Cubuk

This figure shows the co-authorship network connecting the top 25 collaborators of Ekin D. Cubuk. A scholar is included among the top collaborators of Ekin D. Cubuk based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ekin D. Cubuk. Ekin D. Cubuk is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	Predicting emergence of crystals from amorphous precursors with deep learning potentials 2024 ·Nature Computational Science ·Muratahan Aykol,Amil Merchant,Simon Batzner,Jennifer N. Wei,Ekin D. Cubuk	4
2	Accurate Surface and Finite-Temperature Bulk Properties of Lithium Metal at Large Scales Using Machine Learning Interaction Potentials 2024 ·ACS Omega ·(unknown),(unknown),Simon Batzner,Albert Musaelian,Pin-Wen Guan,Boris Kozinsky,Ekin D. Cubuk,Venkatasubramanian Viswanathan	11
3	Efficient Exploratory Synthesis of Quaternary Cesium Chlorides Guided by In Silico Predictions 2024 ·Journal of the American Chemical Society ·Akira Miura,Muratahan Aykol,S Kozaki,Chikako Moriyoshi,Shintaro Kobayashi,Shogo Kawaguchi,Chul‐Ho Lee,(unknown),Amil Merchant,Simon Batzner,Hiroshi Kageyama,Kiyoharu Tadanaga,Pushmeet Kohli,Ekin D. Cubuk	2
4	Toward self-organizing low-dimensional organic–inorganic hybrid perovskites: Machine learning-driven co-navigation of chemical and compositional spaces 2023 ·MRS Bulletin ·Jonghee Yang,Sergei V. Kalinin,Ekin D. Cubuk,Maxim Ziatdinov,Mahshid Ahmadi	6
5	An autonomous laboratory for the accelerated synthesis of inorganic materialsbreakdown → 2023 ·Nature ·Nathan J. Szymanski,Bernardus Rendy,(unknown),Rishi E. Kumar,Tanjin He,David Milsted,Matthew J. McDermott,Max C. Gallant,Ekin D. Cubuk,Amil Merchant,Haegyeom Kim,Anubhav Jain,Christopher J. Bartel,Kristin A. Persson,Yan Zeng,Gerbrand Ceder	451
6	Discovering the Electron Beam Induced Transition Rates for Silicon Dopants in Graphene with Deep Neural Networks in the STEM 2023 ·Microscopy and Microanalysis ·Kevin M. Roccapriore,(unknown),(unknown),(unknown),(unknown),(unknown),Maxim Ziatdinov,Igor Mordatch,Ekin D. Cubuk,Aaron Courville,Pablo Samuel Castro,Marc G. Bellemare,Sergei V. Kalinin	0
7	Scaling deep learning for materials discoverybreakdown → 2023 ·Nature ·Amil Merchant,Simon Batzner,Samuel S. Schoenholz,Muratahan Aykol,Gowoon Cheon,Ekin D. Cubuk	667
8	Deconstructing the Regularization of BatchNorm 2021 ·International Conference on Learning Representations ·Yann Dauphin,Ekin D. Cubuk	1
9	∂PV: An end-to-end differentiable solar-cell simulator 2021 ·Computer Physics Communications ·(unknown),(unknown),Samuel S. Schoenholz,Ekin D. Cubuk,Steven G. Johnson,Giuseppe Romano	10
10	Revisiting ResNets: Improved Training and Scaling Strategies 2021 ·Neural Information Processing Systems ·Irwan Bello,William Fedus,Xianzhi Du,Ekin D. Cubuk,Aravind Srinivas,Tsung-Yi Lin,Jonathon Shlens,Barret Zoph	2
11	Tradeoffs in Data Augmentation: An Empirical Study 2021 ·International Conference on Learning Representations ·(unknown),Sylvia Smullin,Ekin D. Cubuk,Ethan Dyer	13
12	Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation. 2020 ·arXiv (Cornell University) ·Liang-Chieh Chen,Raphael Gontijo Lopes,Bowen Cheng,Maxwell D. Collins,Ekin D. Cubuk,Barret Zoph,Hartwig Adam,Jonathon Shlens	2
13	Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation 2020 ·arXiv (Cornell University) ·Liang-Chieh Chen,Raphael Gontijo Lopes,Bowen Cheng,Maxwell D. Collins,Ekin D. Cubuk,Barret Zoph,Hartwig Adam,Jonathon Shlens	5
14	ReMixMatch: Semi-Supervised Learning with Distribution Matching and Augmentation Anchoring 2020 ·arXiv (Cornell University) ·David Berthelot,Nicholas Carlini,Ekin D. Cubuk,А.В. Куракин,Kihyuk Sohn,Han Zhang,Colin Raffel	165
15	Rethinking Pre-training and Self-training 2020 ·arXiv (Cornell University) ·Barret Zoph,Golnaz Ghiasi,Tsung-Yi Lin,Yin Cui,Hanxiao Liu,Ekin D. Cubuk,Quoc V. Le	21
16	AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty 2020 ·International Conference on Learning Representations ·Dan Hendrycks,Norman Mu,Ekin D. Cubuk,Barret Zoph,Justin Gilmer,Balaji Lakshminarayanan	61
17	Revealing the Spectrum of Unknown Layered Materials with Superhuman Predictive Abilities 2018 ·The Journal of Physical Chemistry Letters ·Gowoon Cheon,Ekin D. Cubuk,Evan R. Antoniuk,(unknown),Joshua E. Goldberger,Evan J. Reed	25
18	Realistic Evaluation of Semi-Supervised Learning Algorithms. 2018 ·International Conference on Learning Representations ·Avital Oliver,Augustus Odena,Colin Raffel,Ekin D. Cubuk,Ian Goodfellow	30
19	Machine learning determination of atomic dynamics at grain boundaries 2018 ·Proceedings of the National Academy of Sciences ·Tristan A. Sharp,Spencer L. Thomas,Ekin D. Cubuk,Samuel S. Schoenholz,David J. Srolovitz,Andrea J. Liu	70
20	Three-dimensional phase step profilometry with a multicore optical fiber 2012 ·Applied Optics ·Ari Novack,(unknown),Ekin D. Cubuk,Mehmet Nacı Incı,(unknown)	4

About Ekin D. Cubuk

Ekin D. Cubuk is a scholar working on Structural Biology, Materials Chemistry and Condensed Matter Physics, having authored 59 papers that have together received 7.8k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (22 papers), Advanced Neural Network Applications (10 papers) and Domain Adaptation and Few-Shot Learning (8 papers). The work is most often cited by research in Signal Processing (1.4k citations), Artificial Intelligence (2.7k citations) and Computer Vision and Pattern Recognition (1.3k citations). Ekin D. Cubuk has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Barret Zoph, Quoc V. Le, Samuel S. Schoenholz, William Chan, Daniel Park, Chung‐Cheng Chiu, Yu Zhang, Vijay Vasudevan, Efthimios Kaxiras and Evan J. Reed. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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