Runzhe Yang

1.4k total citations
12 papers, 132 citations indexed

About

Runzhe Yang is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Organic Chemistry. According to data from OpenAlex, Runzhe Yang has authored 12 papers receiving a total of 132 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 3 papers in Cognitive Neuroscience and 2 papers in Organic Chemistry. Recurrent topics in Runzhe Yang's work include Topic Modeling (4 papers), Neural dynamics and brain function (3 papers) and Speech and dialogue systems (3 papers). Runzhe Yang is often cited by papers focused on Topic Modeling (4 papers), Neural dynamics and brain function (3 papers) and Speech and dialogue systems (3 papers). Runzhe Yang collaborates with scholars based in China, United States and United Kingdom. Runzhe Yang's co-authors include Karthik Narasimhan, Xiang Zhou, Cheng Chang, Kai Yu, Jingxiao Chen, Xingyuan Sun, Lu Chen, Amy Sterling, Arie Matsliah and Marta Costa and has published in prestigious journals such as Nature, Current Biology and Optics Express.

In The Last Decade

Runzhe Yang

11 papers receiving 126 citations

Peers

Runzhe Yang
Comparison fields: 5 of 45
  • Artificial Intelligence 66
  • Cellular and Molecular Neuroscience 23
  • Cognitive Neuroscience 17
  • Electrical and Electronic Engineering 11
  • Computer Networks and Communications 9
Replace A. Stasik with:
A. Stasik Norway
Josephine Maria Thomas United Kingdom
J. Chan United States
Jeffrey He United States
Nathanaël Aubert-Kato Japan
David Renfrew United States
Teruyoshi Hishiki Japan
Hayato Saigo Japan
Siyuan Shen China
Niv Cohen Israel
A. Stasik Norway View profile →
Citations per field, relative to Runzhe Yang
Runzhe Yang · 1×
Citations per year, relative to Runzhe Yang
Runzhe Yang · 1×

Countries citing papers authored by Runzhe Yang

Since Specialization
Citations

This map shows the geographic impact of Runzhe Yang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Runzhe Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Runzhe Yang more than expected).

Fields of papers citing papers by Runzhe Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Runzhe Yang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Runzhe Yang. The network helps show where Runzhe Yang may publish in the future.

Co-authorship network of co-authors of Runzhe Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Runzhe Yang. A scholar is included among the top collaborators of Runzhe Yang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Runzhe Yang. Runzhe Yang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
# Work Indexed citations
1 2
2 2
3 35
4 4
5 6
6 21
7
A Generalized Algorithm for Multi-Objective Reinforcement Learning and Policy Adaptation
16
8 4
9 0
10 12
11 22
12 8

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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