Richard Peng

3.5k citations
56 papers · 1.0k · h-index 20

Impact in

Papers in

Richard Peng

53 papers receiving 985 citations

Peers

Richard Peng
Comparison fields: 5 of 88
  • Computational Mathematics 33
  • Computational Theory and Mathematics 549
  • Statistical and Nonlinear Physics 174
  • Artificial Intelligence 437
  • Computer Networks and Communications 270
Replace Ravindran Kannan with:
Ravindran Kannan United States
Yin Tat Lee United States
Virginia Vassilevska Williams United States
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David Steurer United States
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S. Vempala United States
Yuri Rabinovich Israel
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Citations per field
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Citations per year

Countries citing papers authored by Richard Peng

Since Specialization
Citations

This map shows the geographic impact of Richard Peng'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 Richard Peng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Richard Peng more than expected).

Fields of papers citing papers by Richard Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Richard Peng. 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 Richard Peng. The network helps show where Richard Peng may publish in the future.

Co-authors

The 25 scholars most cited alongside Richard Peng, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Richard Peng Line = papers co-authored together Richard Peng links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201086
2 201583
3 201263
4 202259
5 201450
6 201847
7 201342
8 201338
9 201634
10 201332
11 202030
12 201430
13 201128
14 202027
15 201524
16 201723
17 201522
18
Faster Algorithms for Computing the Stationary Distribution, Simulating Random Walks, and More
201621
19 202121
20 201720

About Richard Peng

Richard Peng is a scholar working on Computational Theory and Mathematics, Artificial Intelligence, Computer Networks and Communications, Computational Mechanics and Statistics and Probability, having authored 56 papers that have together received 1.0k indexed citations. Recurring topics across this work include Complexity and Algorithms in Graphs (28 papers), Advanced Graph Theory Research (14 papers), Markov Chains and Monte Carlo Methods (9 papers), Sparse and Compressive Sensing Techniques (9 papers), Graph theory and applications (8 papers), Optimization and Search Problems (7 papers), Advanced Graph Neural Networks (6 papers) and Matrix Theory and Algorithms (6 papers). The work is most often cited by research in Computational Mathematics (33 citations), Computational Theory and Mathematics (549 citations), Statistical and Nonlinear Physics (174 citations), Artificial Intelligence (437 citations) and Computer Networks and Communications (270 citations). Richard Peng has collaborated with scholars based in United States, Canada and Puerto Rico. Frequent co-authors include Gary L. Miller, Ioannis Koutis, Shen Xu, Charalampos E. Tsourakakis, Michael B. Cohen, Rasmus Kyng, Jakub Pachocki, Sushant Sachdeva, Kanat Tangwongsan and Michael Mitzenmacher. Their work appears in journals such as SIAM Journal on Computing, Communications of the ACM, Algorithmica, Journal of Food Protection and Theory of Computing Systems.

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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