Frank Hutter: h-index, Total Citations, and Citation Map
Frank Hutter's h-index is 107 (268 i10-index, 142,729+ total citations across 518+ publications) according to Google Scholar as of September 2026. Frank Hutter is affiliated with ELLIS Institute Tübingen.
Frank Hutter is a researcher affiliated with ELLIS Institute Tübingen, specializing in various fields. Their work has been cited 142,729 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Frank Hutter's Citation Metrics
Bibliometric impact based on 518 indexed publications. Of these, 19 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 107
- i10-Index
- 268
- Total Citations
- 142,729
- Citing Countries
- 78
As of September 2026.
Frank Hutter has an h-index of 107 and 142,729 total citations across 518 publications, with research cited by institutions in 78 countries.
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Global Impact Map
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Decoupled weight decay regularization
201748,863
Top Citing Countries
Top Citing Institutions
Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
12 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher developed foundational frameworks for automatic algorithm configuration and runtime prediction, establishing a widely adopted methodology for optimizing computational processes.
The researcher pioneered automated machine learning by developing methods for combined algorithm selection and hyperparameter optimization, significantly advancing the efficiency of classification tasks.
The researcher introduced decoupled weight decay regularization, a foundational technique that has become a standard component in modern deep learning optimization practices.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Frank Hutter's research
Frank Hutter is a researcher at ELLIS Institute Tübingen. Their work has been cited 142,729 times across 518 publications (h-index 107), according to Google Scholar.
Their most-cited work, “Decoupled weight decay regularization” (2017), has accumulated 48,863 citations. Other influential works include “Sgdr: Stochastic gradient descent with warm restarts” (2016) with 14,771 citations and “Deep learning with convolutional neural networks for EEG decoding and visualization” (2017) with 4,849 citations.
Citations of Frank Hutter's research come primarily from China, United States and Germany, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
