Mohan Li

1.4k citations
89 papers · 809 · 1 hit paper · h-index 11

Impact in

Papers in

Mohan Li

72 papers receiving 776 citations

Mohan Li's Hit Papers

Block-DEF: A secure digital evidence framework using blockchain 2019 · 238 citations
2380+2+4Years since publication50100150200

Peers

Mohan Li
Comparison fields: 5 of 111
  • Signal Processing 142
  • Information Systems 263
  • Computer Networks and Communications 235
  • Artificial Intelligence 299
  • Computer Vision and Pattern Recognition 89
Replace Ray-Shine Run with:
Ray-Shine Run Taiwan
Nicolai M. Josuttis Switzerland
Gong Zhang China
Shaoying Liu Japan
Xiaoyuan Xie China
Qishi Wu United States
Shuai Wang China
Maninder Singh India
Liran Katzir Israel
Ripon Patgiri India
Mohan Li relative to Ray-Shine Run Taiwan Ray-Shine Run's profile →
Citations per field
00.5×5.1×
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Citations per year

Countries citing papers authored by Mohan Li

Since Specialization
Citations

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

Fields of papers citing papers by Mohan Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 89 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Block-DEF: A secure digital evidence framework using blockchain
Hit paper breakdown →
2019238
2 2019114
3 202048
4 202046
5 201640
6 202222
7 201315
8 202013
9 202413
10 202112
11 201912
12 202210
13 202310
14 202410
15 20188
16 20238
17 20228
18 20218
19 20198
20 20237

About Mohan Li

Mohan Li is a scholar working on Artificial Intelligence, Computer Networks and Communications, Signal Processing, Information Systems and Radiology, Nuclear Medicine and Imaging, having authored 89 papers that have together received 809 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (11 papers), Privacy-Preserving Technologies in Data (8 papers), Topic Modeling (7 papers), Data Quality and Management (7 papers), Advanced X-ray and CT Imaging (7 papers), Network Security and Intrusion Detection (7 papers), Music and Audio Processing (6 papers) and Anomaly Detection Techniques and Applications (5 papers). The work is most often cited by research in Signal Processing (142 citations), Information Systems (263 citations), Computer Networks and Communications (235 citations), Artificial Intelligence (299 citations) and Computer Vision and Pattern Recognition (89 citations). Mohan Li has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Yanbin Sun, Zhihong Tian, Shen Su, Meikang Qiu, Hui Lu, Sabita Maharjan, Rama Doddipatla, Chunsheng Zhu, Nadra Guizani and Mohsen Guizani. Their work appears in journals such as Computers, materials & continua/Computers, materials & continua (Print), Tribology International, Biochemical Genetics, IEEE Internet of Things Journal and Neurocomputing.

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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