Qi Han

3.1k citations
131 papers · 2.2k · h-index 21

Impact in

Papers in

Qi Han

124 papers receiving 2.1k citations

Peers

Qi Han
Comparison fields: 5 of 94
  • Computer Science Applications 612
  • Transportation 400
  • Computer Networks and Communications 908
  • Computer Vision and Pattern Recognition 315
  • Electrical and Electronic Engineering 805
Replace Prashanth Mohan with:
Prashanth Mohan United States
Lenin Ravindranath United States
Xufei Mao China
Dong Zhao China
Raghu Ganti United States
Jiangtian Nie Singapore
Matthias Hollick Germany
Zhiyong Yu China
Claudio Fiandrino Spain
Quinn Jacobson United States
Qi Han relative to Prashanth Mohan United States Prashanth Mohan's profile →
Citations per field
00.5×
Prashanth Mohan · 1×
Citations per year

Countries citing papers authored by Qi Han

Since Specialization
Citations

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

Fields of papers citing papers by Qi Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 131 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007258
2 2016207
3 2017117
4 2010107
5 200785
6 201675
7 201674
8 201773
9 201959
10 200455
11 201946
12 201545
13 201042
14 200338
15 201735
16 201635
17 200933
18 202029
19 200427
20 201025

About Qi Han

Qi Han is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Transportation and Computer Science Applications, having authored 131 papers that have together received 2.2k indexed citations. Recurring topics across this work include Energy Efficient Wireless Sensor Networks (39 papers), Human Mobility and Location-Based Analysis (21 papers), Indoor and Outdoor Localization Technologies (21 papers), Mobile Crowdsensing and Crowdsourcing (20 papers), Context-Aware Activity Recognition Systems (19 papers), Mobile Ad Hoc Networks (18 papers), Opportunistic and Delay-Tolerant Networks (15 papers) and Green IT and Sustainability (11 papers). The work is most often cited by research in Computer Science Applications (612 citations), Transportation (400 citations), Computer Networks and Communications (908 citations), Computer Vision and Pattern Recognition (315 citations) and Electrical and Electronic Engineering (805 citations). Qi Han has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Zhiwen Yu, Bin Guo, Alan Marchiori, Nalini Venkatasubramanian, Anura P. Jayasumana, Huihui Chen, Yan Liu, Wenle Wu, Tissa H. Illangasekare and Liang Wang. Their work appears in journals such as IEEE Transactions on Mobile Computing, Pervasive and Mobile Computing, IEEE Transactions on Parallel and Distributed Systems, IEEE Internet of Things Journal and Journal of Parallel and Distributed Computing.

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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