Ruosong Wang

Ruosong Wang is a researcher affiliated with Assistant Professor, Peking University, specializing in AI & Machine Learning. Their work has been cited 6,047 times. This profile visualizes their global influence, highlighting strong citation networks in US.

AI & Machine Learning

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0i10-index

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Assistant Professor, Peking University•

Google Scholar

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Ruosong Wang's Citation Metrics

Bibliometric impact based on 1 indexed publication.

H-Index: 1
i10-Index: 1
Total Citations: 6,047
Citing Countries: 2

As of April 2026.

Ruosong Wang has an h-index of 1 and 6,047 total citations across 1 publication, with research cited by institutions in 2 countries.

Global Impact Map

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

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Top Citing Countries(Limited)

United States(US)

China(CN)

Top Citing Institutions(Limited)

University of California, Berkeley

Google Research

Shanghai Jiao Tong University

University of California, San Diego

Shanghai Jiao Tong University; Shanghai Artificial Intelligence Laboratory

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 2 of 2 countries (9 total citations).

Scholar

Ruosong Wang

United States

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
Ren Ng
7.0
University of California, Berkeley
United States· Cited your work 1 time
IndependentTop institution
#2
Matthew Tancik
7.0
University of California, Berkeley
United States· Cited your work 1 time
IndependentTop institution
#3
Yaoyu Zhang
8.5
Shanghai Jiao Tong University
China· Cited your work 1 time
IndependentTop institutionDiversifies geography
#4
Zhi-Qin John Xu
8.5
Shanghai Jiao Tong University
China· Cited your work 1 time
IndependentTop institutionDiversifies geography
#5
Sara Fridovich-Keil
7.0
University of California, Berkeley
United States· Cited your work 1 time
IndependentTop institution
#6
Nithin Raghavan
7.0
University of California, Berkeley
United States· Cited your work 1 time
IndependentTop institution
#7
Utkarsh Singhal
7.0
University of California, Berkeley
United States· Cited your work 1 time
IndependentTop institution
#8
Tao Luo
8.5
Shanghai Jiao Tong University; Shanghai Artificial Intelligence Laboratory
China· Cited your work 1 time
IndependentTop institutionDiversifies geography
#9
Ravi Ramamoorthi
7.0
University of California, San Diego
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.

Cited by 5 papers

5 / 5 independent

Citations flagged as non-independent share the scholar's home institution (Carnegie Mellon University). EB-1A & O-1A petitions typically quote the independent-citation count as the stronger evidence of outside recognition.

(title pending — citation is still being processed)
· cites “Fine-grained analysis of optimization and generalization for overparameterized two-layer neural networks”
Overview frequency principle/spectral bias in deep learning
Zhi-Qin John Xu, Yaoyu Zhang, Tao Luo
Communications on Applied Mathematics and Computation· cites “Fine-grained analysis of optimization and generalization for overparameterized two-layer neural networks”
Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains
Matthew Tancik, Pratul P. Srinivasan, Ben Mildenhall, Sara Fridovich-Keil + 5 more
34th Conference on Neural Information Processing Systems (NeurIPS 2020)· cites “Fine-grained analysis of optimization and generalization for overparameterized two-layer neural networks”
(title pending — citation is still being processed)
· cites “Fine-grained analysis of optimization and generalization for overparameterized two-layer neural networks”
(title pending — citation is still being processed)
· cites “Fine-grained analysis of optimization and generalization for overparameterized two-layer neural networks”

Top Cited Works(Showing 1 of 1)

Fine-grained analysis of optimization and generalization for overparameterized two-layer neural networks

2019 • 1342 Citations

Published in 36th International Conference on Machine Learning (ICML 2019)

Citation trend (last 10 years)Click to expand

Citation Trend (Last 10 Years)

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1,342 citations

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