Shi Han

3.0k citations
86 papers · 1.7k · h-index 24

Impact in

  • Software top 1%
    • Software Testing and Debugging Techniques
    • Software Reliability and Analysis Research
    • Software Engineering Research

Papers in

Shi Han

76 papers receiving 1.7k citations

Peers

Shi Han
Comparison fields: 5 of 109
  • Software 305
  • Information Systems 600
  • Artificial Intelligence 606
  • Computer Networks and Communications 393
  • Signal Processing 169
Replace H.H. Ammar with:
H.H. Ammar United States
Bahman Arasteh Iran
Paolo Arcaini Japan
He Jiang China
Jitender Kumar Chhabra India
Kexin Pei United States
Andrea Bondavalli Italy
Tao Yue Norway
Zhi Quan Zhou Australia
Geguang Pu China
Shi Han relative to H.H. Ammar United States H.H. Ammar's profile →
Citations per field
00.5×10×15.5×
H.H. Ammar · 1×
Citations per year

Countries citing papers authored by Shi Han

Since Specialization
Citations

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

Fields of papers citing papers by Shi Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 86 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018178
2 2012125
3 201779
4 202176
5 201868
6 201959
7 202258
8 202255
9 201353
10 202451
11 201351
12 201851
13 201950
14 201148
15 202245
16 201237
17 201136
18 202131
19 201430
20 202329

About Shi Han

Shi Han is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Computer Networks and Communications and Software, having authored 86 papers that have together received 1.7k indexed citations. Recurring topics across this work include Topic Modeling (21 papers), Natural Language Processing Techniques (14 papers), Software Engineering Research (13 papers), Software System Performance and Reliability (10 papers), Advanced Graph Neural Networks (7 papers), Data Quality and Management (6 papers), Spreadsheets and End-User Computing (6 papers) and Time Series Analysis and Forecasting (6 papers). The work is most often cited by research in Software (305 citations), Information Systems (600 citations), Artificial Intelligence (606 citations), Computer Networks and Communications (393 citations) and Signal Processing (169 citations). Shi Han has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Dongmei Zhang, Tao Xie, Lun Du, Yingnong Dang, Bin Yu, Rui Ding, Yanlin Wang, Ge Song, Simin Liu and Qin Ma. Their work appears in journals such as Empirical Software Engineering, Journal of Building Engineering, International Journal of Biological Macromolecules, IEEE Transactions on Biomedical Circuits and Systems and Insight - Non-Destructive Testing and Condition Monitoring.

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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