Jiaming Pei

49 papers receiving 734 citations

Jiaming Pei's Hit Papers

A Review of Federated Learning Methods in Heterogeneous Scenarios 2024 · 114 citations
1140+1Years since publication255075100

Peers

Jiaming Pei
Comparison fields: 5 of 86
  • Artificial Intelligence 272
  • Management Science and Operations Research 91
  • Computer Vision and Pattern Recognition 119
  • Computer Networks and Communications 72
  • Information Systems 80
Replace Geon Heo with:
Geon Heo South Korea
Qifeng Zhou China
Tapan Kumar Das India
Michal Jakob Czechia
Mohd Hilmi Hasan Malaysia
Sumit Kumar India
Amril Nazir United Arab Emirates
P. Ajay India
Ranjit Panigrahi India
Jiaming Pei relative to Geon Heo South Korea Geon Heo's profile →
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Countries citing papers authored by Jiaming Pei

Since Specialization
Citations

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

Fields of papers citing papers by Jiaming Pei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A Review of Federated Learning Methods in Heterogeneous Scenarios
Hit paper breakdown →
2024114
2 2021109
3 202354
4 202250
5 202144
6 202238
7 202232
8 202329
9 202226
10 202224
11 202322
12 202321
13 202220
14 202316
15 202316
16 202313
17 202513
18 202411
19 20219
20 20219

About Jiaming Pei

Jiaming Pei is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Computer Networks and Communications and Media Technology, having authored 57 papers that have together received 785 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (24 papers), Video Surveillance and Tracking Methods (6 papers), Remote-Sensing Image Classification (3 papers), Recommender Systems and Techniques (3 papers), Traffic control and management (3 papers), Transportation Planning and Optimization (2 papers), Evaluation and Optimization Models (2 papers) and Electric Vehicles and Infrastructure (2 papers). The work is most often cited by research in Artificial Intelligence (272 citations), Management Science and Operations Research (91 citations), Computer Vision and Pattern Recognition (119 citations), Computer Networks and Communications (72 citations) and Information Systems (80 citations). Jiaming Pei has collaborated with scholars based in China, Australia and United Kingdom. Frequent co-authors include Jinhai Li, Lukun Wang, Zhi Hong Yu, Kaiyang Zhong, Chao Liu, Wenxuan Liu, Yifan Wang, Shike Li, Kuruva Lakshmanna and Wenxuan Liu. Their work appears in journals such as IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Consumer Electronics, IEEE Internet of Things Journal, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing and IEEE Journal on Selected Areas in Communications.

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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