Song Han

Song Han is a researcher affiliated with Massachusetts Institute of Technology, specializing in AI & Machine Learning. Their work has been cited 93,489 times. This profile visualizes their global influence, highlighting strong citation networks in US.

AI & Machine Learning

0h-index

0i10-index

0Citations

0Works

0Countries

Massachusetts Institute of Technology•

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.

Song Han's Citation Metrics

Bibliometric impact based on 1 indexed publication.

H-Index: 1
i10-Index: 1
Total Citations: 93,489
Citing Countries: 4

As of April 2026.

Song Han has an h-index of 1 and 93,489 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)

Australia(AU)

China(CN)

United States(US)

Top Citing Institutions(Limited)

University of Texas at Austin

NVIDIA

Stanford University

Massachusetts Institute of Technology

The University of Adelaide

University of California, San Diego

Meta AI

Adobe Research

Harbin Institute of Technology

University of California, Berkeley

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 (19 total citations).

Scholar

Song Han

194

United States

USA

Australia

China

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
Tianlong Chen
7.0
University of Texas at Austin
United States· Cited your work 1 time
IndependentTop institution
#2
Ruisi Cai
7.0
University of Texas at Austin
United States· Cited your work 1 time
IndependentTop institution
#3
Christopher Ré
8.5
Stanford University
USA· Cited your work 1 time
IndependentTop institutionDiversifies geography
#4
Miao Zhang
8.5
Harbin Institute of Technology
China· Cited your work 1 time
IndependentTop institutionDiversifies geography
#5
Hongrong Cheng
6.5
The University of Adelaide
Australia· Cited your work 1 time
IndependentDiversifies geography
#6
Javen Qinfeng Shi
6.5
The University of Adelaide
Australia· Cited your work 1 time
IndependentDiversifies geography
#7
Zhao Song
6.5
Adobe Research
· Cited your work 1 time
IndependentDiversifies geography
#8
Zhenyu Zhang
7.0
University of Texas at Austin
United States· Cited your work 1 time
IndependentTop institution
#9
Zhangyang Wang
7.0
University of Texas at Austin
United States· Cited your work 1 time
IndependentTop institution
#10
Ying Sheng
7.0
Stanford 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.