Caglar Gulcehre: h-index, Total Citations, and Citation Map
Caglar Gulcehre's h-index is 1 (1 i10-index, 97,918+ total citations across 1+ publications) according to Google Scholar as of June 2026. Caglar Gulcehre is affiliated with MTS @ MAI, Prof at EPFL, Ex-Consultant@DeepMind,@nimble.ai, ex-Research Scientist@Google DeepMind.
Caglar Gulcehre is a researcher affiliated with MTS @ MAI, Prof at EPFL, Ex-Consultant@DeepMind,@nimble.ai, ex-Research Scientist@Google DeepMind, specializing in AI & Machine Learning. Their work has been cited 97,918 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Caglar Gulcehre's Citation Metrics
Bibliometric impact based on 1 indexed publication.
- H-Index
- 1
- i10-Index
- 1
- Total Citations
- 97,918
- Citing Countries
- 5
As of June 2026.
Caglar Gulcehre has an h-index of 1 and 97,918 total citations across 1 publication, with research cited by institutions in 5 countries.
Global Impact Map
Visualizing the geographic distribution of institutions that have cited your work.
Starting…
Pins will appear here as institutions are resolved — no need to refresh.
Learning phrase representations using RNN encoder–decoder for statistical machine translation
201440,254
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.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
Related Guides
Learn how to use citation maps for your research and visa applications.
About Caglar Gulcehre's research
Caglar Gulcehre is a researcher in AI & Machine Learning at MTS @ MAI, Prof at EPFL, Ex-Consultant@DeepMind,@nimble.ai, ex-Research Scientist@Google DeepMind. Their work has been cited 97,918 times across 1 publications, according to Google Scholar.
Their most-cited work, “Learning phrase representations using RNN encoder–decoder for statistical machine translation” (2014), has accumulated 40,254 citations.
Citations of Caglar Gulcehre's research come primarily from United States, China and India, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.











