Shuran Song

Shuran Song is a researcher affiliated with Stanford University, specializing in AI & Machine Learning. Their work has been cited 50,999 times. This profile visualizes their global influence, highlighting strong citation networks in US.

AI & Machine Learning

0h-index

0i10-index

0Citations

0Works

0Countries

Stanford University•

Google Scholar

Unlock Full Map — Pro tier (10K–100K citations)

One-time payment. Full data, CSV export, and embed code.

Viewing Limited Data

Showing up to 10 papers and top 10 citing sources. Upgrade to see all 1 paper and complete citation data.

Shuran Song's Citation Metrics

Bibliometric impact based on 1 indexed publication.

H-Index: 1
i10-Index: 1
Total Citations: 50,999
Citing Countries: 4

As of April 2026.

Shuran Song has an h-index of 1 and 50,999 total citations across 1 publication, with research cited by institutions in 4 countries.

Global Impact Map

Visualizing the geographic distribution of institutions that have cited your work.

Marker

Color

Show home

Top Citing Countries(Limited)

United States(US)

China(CN)

United Kingdom(GB)

Australia(AU)

Top Citing Institutions(Limited)

Hohai University

Google DeepMind

Stanford University

University of California, Berkeley

Griffith University

New York University

Carnegie Mellon University

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.

Citer Influence Network

Visa-ready visualisation: each outer ring node is a country citing this scholar. Node size & edge weight scale with citing-paper count. Showing top 4 of 4 countries (12 total citations).

Scholar

Shuran Song

124

China

United States

Australia

United Kingdom

React Flow

Letter of Support — Candidate Recommenders

Ranked by EB-1A / O-1A relevance: independence from your home institution, affiliation with a top-ranked institution, repeat citations of your work, and recency. Reach out to the highest-scoring candidates to request support letters.

#1
Jitendra Malik
7.0
University of California, Berkeley
United States· Cited your work 1 time
IndependentTop institution
#2
Sergey Levine
7.0
University of California, Berkeley
United States· Cited your work 1 time
IndependentTop institution
#3
Abhinav Gupta
8.5
Carnegie Mellon University
· Cited your work 1 time
IndependentTop institutionDiversifies geography
#4
Karol Hausman
8.5
Google DeepMind
United Kingdom· Cited your work 1 time
IndependentTop institutionDiversifies geography
#5
Zewen Li
6.5
Hohai University
China· Cited your work 1 time
IndependentDiversifies geography
#6
Fan Liu
6.5
Hohai University
China· Cited your work 1 time
IndependentDiversifies geography
#7
Jun Zhou
6.5
Griffith University
Australia· Cited your work 1 time
IndependentDiversifies geography
#8
Chelsea Finn
7.0
Stanford University
United States· Cited your work 1 time
IndependentTop institution
#9
Karl Pertsch
7.0
Stanford University
United States· Cited your work 1 time
IndependentTop institution
#10
Lerrel Pinto
7.0
New York University
United States· Cited your work 1 time
IndependentTop institution

Scores combine 5 signals: independence (+3), prestige institution (+2), repeat citations (+2 per paper, cap 5), recent activity (+1), and geography diversity (+1.5). Identity matching uses name + institution; namesakes at the same org are merged.