Hao He

39 papers receiving 690 citations

Hao He's Hit Papers

Summary of ChatGPT-Related research and perspective towards the future of large language models 2023 · 442 citations
4420+1+2Years since publication100200300400

Peers

Hao He
Comparison fields: 5 of 120
  • Health Informatics 95
  • Computer Science Applications 57
  • Human-Computer Interaction 43
  • Artificial Intelligence 247
  • Computer Networks and Communications 88
Replace Pengyuan Zhou with:
Pengyuan Zhou China
Mladjan Jovanovic Serbia
Emily Reif United States
Enis Karaarslan Türkiye
Alex Hanna United States
Xiaoyuan Yi China
Kaijie Zhu China
Eduardo Mosqueira-Rey Spain
Cunxiang Wang China
Hao He relative to Pengyuan Zhou China Pengyuan Zhou's profile →
Citations per field
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Citations per year

Countries citing papers authored by Hao He

Since Specialization
Citations

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

Fields of papers citing papers by Hao He

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Summary of ChatGPT-Related research and perspective towards the future of large language models
Hit paper breakdown →
2023442
2 201973
3 202139
4 202215
5 200813
6 201313
7 200711
8 202010
9 20099
10 20219
11 20208
12 20218
13 20226
14 20196
15 20135
16 20204
17 20243
18 20223
19 20173
20 20243

About Hao He

Hao He is a scholar working on Computer Networks and Communications, Education, Electrical and Electronic Engineering, Artificial Intelligence and Information Systems, having authored 41 papers that have together received 714 indexed citations. Recurring topics across this work include Cognitive Radio Networks and Spectrum Sensing (8 papers), Online and Blended Learning (7 papers), Advanced MIMO Systems Optimization (6 papers), Cooperative Communication and Network Coding (5 papers), Virtual Reality Applications and Impacts (4 papers), Topic Modeling (3 papers), Visual and Cognitive Learning Processes (3 papers) and Online Learning and Analytics (3 papers). The work is most often cited by research in Health Informatics (95 citations), Computer Science Applications (57 citations), Human-Computer Interaction (43 citations), Artificial Intelligence (247 citations) and Computer Networks and Communications (88 citations). Hao He has collaborated with scholars based in China and United States. Frequent co-authors include Yuanyuan Yang, Mengshen He, Qiang Ning, Bao Ge, Jiaming Tian, Lin Zhao, Yiheng Liu, Zihao Wu, Xiang Li and Tianming Liu. Their work appears in journals such as ISPRS International Journal of Geo-Information, Technology Knowledge and Learning, Journal of Research on Technology in Education, International Journal of Environmental Research and Public Health and Educational Technology Research and Development.

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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