Lei Tang

9.9k citations
176 papers · 5.3k indexed · 1 hit paper · h-index 36

Impact in

Papers in

Lei Tang

156 papers receiving 5.0k citations

Hit Papers

Relational learning via latent social dimensions 2009 · 442 citations
4422009202620142020100200300400

Peers

Lei Tang
Comparison fields: 5 of 162
  • Statistical and Nonlinear Physics 1.7k
  • Artificial Intelligence 2.3k
  • Computational Mathematics 40
  • Transportation 397
  • Computer Vision and Pattern Recognition 1.1k
Replace Yu‐Ru Lin with:
Yu‐Ru Lin United States
Jason J. Jung South Korea
Aixin Sun Singapore
Andreas Hotho Germany
Qun Jin Japan
Juanzi Li China
Zhoujun Li China
Guandong Xu Australia
Nan Cao China
Suhang Wang United States
Lei Tang relative to Yu‐Ru Lin United States Yu‐Ru Lin's profile →
Citations per field
00.5×1.5×2.3×
Yu‐Ru Lin · 1×
Citations per year

Countries citing papers authored by Lei Tang

Since Specialization
Citations

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

Fields of papers citing papers by Lei Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20241
2 20244
3 20231
4 20232
5 202314
6 20221
7 202245
8 20222
9 20208
10 20201
11 201918
12 201916
13 201914
14 20190
15 20186
16 20188
17 201811
18 20182
19 20144
20
An Analysis of Anticipated Behavioral Responses to Real-Time Transit Information Systems
20072

About Lei Tang

Lei Tang is a scholar working on Transportation, Statistical and Nonlinear Physics, Computational Mathematics, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 176 papers that have together received 5.3k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (27 papers), Opinion Dynamics and Social Influence (20 papers), Human Mobility and Location-Based Analysis (14 papers), Mobile Ad Hoc Networks (13 papers), Transportation and Mobility Innovations (11 papers), Opportunistic and Delay-Tolerant Networks (10 papers), Transportation Planning and Optimization (9 papers) and Text and Document Classification Technologies (8 papers). The work is most often cited by research in Statistical and Nonlinear Physics (1.7k citations), Artificial Intelligence (2.3k citations), Computational Mathematics (40 citations), Transportation (397 citations) and Computer Vision and Pattern Recognition (1.1k citations). Lei Tang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Huan Liu, Huan Liu, Xufei Wang, Jieping Ye, Yanjun Sun, Omer Gurewitz, David B. Johnson, Nitin Agarwal, Philip S. Yu and Piyushimita Thakuriah. Their work appears in journals such as ACM Transactions on Knowledge Discovery from Data, IEEE Access, Neurocomputing, Data Mining and Knowledge Discovery and Remote Sensing.

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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