Pinyan Lu

77 papers receiving 892 citations

Peers

Pinyan Lu
Comparison fields: 5 of 63
  • Statistics and Probability 400
  • Discrete Mathematics and Combinatorics 110
  • Computational Theory and Mathematics 428
  • Computational Mathematics 14
  • Management Science and Operations Research 266
Replace Akimichi Takemura with:
Akimichi Takemura Japan
Shayan Oveis Gharan United States
Noureddine El Karoui United States
Daniel Berend Israel
Ron Holzman Israel
Arup Bose India
Gordon Simons United States
Gleb Koshevoy Russia
Ehud Friedgut Israel
Ulrich Krengel Germany
Pinyan Lu relative to Akimichi Takemura Japan Akimichi Takemura's profile →
Citations per field
00.5×1.5×1.8×
Akimichi Takemura · 1×
Citations per year

Countries citing papers authored by Pinyan Lu

Since Specialization
Citations

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

Fields of papers citing papers by Pinyan Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Pinyan Lu, 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 Pinyan Lu Line = papers co-authored together Pinyan Lu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 82 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201078
2 201155
3 200947
4 201235
5
Correlation decay up to uniqueness in spin systems
201333
6 201133
7 201332
8 200831
9 201330
10 200728
11 201327
12 201221
13 201121
14 201020
15 202220
16 201819
17 201418
18
Approximate counting via correlation decay in spin systems
201217
19 201517
20 200616

About Pinyan Lu

Pinyan Lu is a scholar working on Computational Theory and Mathematics, Statistics and Probability, Management Science and Operations Research, Marketing and Artificial Intelligence, having authored 82 papers that have together received 941 indexed citations. Recurring topics across this work include Markov Chains and Monte Carlo Methods (34 papers), Complexity and Algorithms in Graphs (30 papers), Auction Theory and Applications (25 papers), Advanced Graph Theory Research (22 papers), Consumer Market Behavior and Pricing (17 papers), Game Theory and Voting Systems (10 papers), Optimization and Search Problems (9 papers) and Limits and Structures in Graph Theory (7 papers). The work is most often cited by research in Statistics and Probability (400 citations), Discrete Mathematics and Combinatorics (110 citations), Computational Theory and Mathematics (428 citations), Computational Mathematics (14 citations) and Management Science and Operations Research (266 citations). Pinyan Lu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Jin‐Yi Cai, Mingji Xia, Nick Gravin, Ning Chen, Yitong Yin, Liang Li, Sangxia Huang, Xi Chen, Yajun Wang and Heng Guo. Their work appears in journals such as SIAM Journal on Computing, Computational Complexity, Journal of Computer and System Sciences, Algorithmica and Theoretical Computer Science.

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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