Daxin Jiang Google Scholar: h-index, Total Citations, and Citation Map
Daxin Jiang's h-index is 69 (184 i10-index, 30,016+ total citations across 271+ publications) according to Google Scholar as of October 2026. Daxin Jiang is affiliated with Microsoft.
Daxin Jiang is a researcher affiliated with Microsoft, specializing in Deep Learning, Foundation Models. Their work has been cited 30,016 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Daxin Jiang's Citation Metrics
Bibliometric impact based on 271 indexed publications. Of these, 19 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 69
- i10-Index
- 184
- Total Citations
- 30,016
- Citing Countries
- 62
As of October 2026.
Daxin Jiang has an h-index of 69 and 30,016 total citations across 271 publications, with research cited by institutions in 62 countries.
Download Exports (PNG, CSV, Poster)
Free Viewing Daxin Jiang's citation map is always free. Pay once to download poster, PNG, and CSV files for offline use or your visa packet.
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.
Codebert: A pre-trained model for programming and natural languages
20205,381
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 Daxin Jiang's research
Daxin Jiang is a researcher in Deep Learning and Foundation Models at Microsoft. Their work has been cited 30,016 times across 271 publications (h-index 69), according to Google Scholar.
Their most-cited work, “Codebert: A pre-trained model for programming and natural languages” (2020), has accumulated 5,381 citations. Other influential works include “Graphcodebert: Pre-training code representations with data flow” (2020) with 2,093 citations and “Cluster analysis for gene expression data: a survey” (2004) with 1,769 citations.
Citations of Daxin Jiang's research come primarily from China, United States and United Kingdom, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
