Shi Han

2.9k citations
84 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

75 papers receiving 1.6k citations

Peers

Shi Han
Comparison fields: 5 of 109
  • Software 304
  • Information Systems 591
  • Artificial Intelligence 571
  • Computer Networks and Communications 389
  • Signal Processing 157
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
Tao Yue Norway
Geguang Pu China
Hui Song China
Zhi Quan Zhou Australia
Shi Han relative to H.H. Ammar United States H.H. Ammar's profile →
Citations per field
00.5×10×15×18.3×
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 84 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018171
2 2012122
3 201775
4 202172
5 201868
6 201354
7 202254
8 202253
9 201952
10 201351
11 201851
12 201950
13 201148
14 202443
15 202240
16 201237
17 201136
18 202131
19 201430
20 200629

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 84 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), Time Series Analysis and Forecasting (6 papers), Data Quality and Management (6 papers), Advanced Graph Neural Networks (6 papers) and Spreadsheets and End-User Computing (6 papers). The work is most often cited by research in Software (304 citations), Information Systems (591 citations), Artificial Intelligence (571 citations), Computer Networks and Communications (389 citations) and Signal Processing (157 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, Ge Song, Yanlin Wang, Rui Ding, Junqi Chen and Simin Liu. Their work appears in journals such as Empirical Software Engineering, Automated Software Engineering, IEEE Software, Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment and Journal of Building Engineering.

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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