Daniel Zhang

2.1k citations
70 papers · 1.4k indexed · h-index 23

Impact in

Papers in

Daniel Zhang

68 papers receiving 1.3k citations

Peers

Daniel Zhang
Comparison fields: 5 of 94
  • Computer Science Applications 530
  • Transportation 229
  • Artificial Intelligence 560
  • Computer Networks and Communications 319
  • Health Informatics 16
Replace Xiangrong Tong with:
Xiangrong Tong China
Chuan Zhang China
Jia Xu China
Zhixu Li China
Dingqi Yang China
Neil Y. Yen Japan
Shou-De Lin Taiwan
Xiaolin Gui China
Daniel Zhang relative to Xiangrong Tong China Xiangrong Tong's profile →
Citations per field
00.5×5.3×
Xiangrong Tong · 1×
Citations per year

Countries citing papers authored by Daniel Zhang

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004138
2 201867
3 201664
4 201956
5 201749
6 201847
7 202047
8 201846
9 202044
10 202043
11 201843
12 202139
13 201737
14 201835
15 201931
16 201931
17 201929
18 201728
19 201927
20 202026

About Daniel Zhang

Daniel Zhang is a scholar working on Computer Science Applications, Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition and Transportation, having authored 70 papers that have together received 1.4k indexed citations. Recurring topics across this work include Mobile Crowdsensing and Crowdsourcing (38 papers), IoT and Edge/Fog Computing (15 papers), Human Mobility and Location-Based Analysis (14 papers), Privacy-Preserving Technologies in Data (9 papers), Evacuation and Crowd Dynamics (9 papers), Anomaly Detection Techniques and Applications (7 papers), Misinformation and Its Impacts (7 papers) and Spam and Phishing Detection (5 papers). The work is most often cited by research in Computer Science Applications (530 citations), Transportation (229 citations), Artificial Intelligence (560 citations), Computer Networks and Communications (319 citations) and Health Informatics (16 citations). Daniel Zhang has collaborated with scholars based in United States, Singapore and United Kingdom. Frequent co-authors include Dong Wang, Yang Zhang, Liang Zhou, Md Tahmid Rashid, Nathan Vance, Lanyu Shang, Ziyi Kou, Yang Zhang, Yue Ma and Xiaobo Sharon Hu. Their work appears in journals such as IEEE Transactions on Big Data, Pervasive and Mobile Computing, Knowledge-Based Systems, Proceedings of the ACM on Human-Computer Interaction and Social Network Analysis and Mining.

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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