Da Wang

836 citations
53 papers · 549 · h-index 13

Impact in

Papers in

Da Wang

46 papers receiving 533 citations

Peers

Da Wang
Comparison fields: 5 of 63
  • Computer Networks and Communications 265
  • Hardware and Architecture 44
  • Artificial Intelligence 151
  • Computational Theory and Mathematics 58
  • Information Systems 71
Replace Hong Ding with:
Hong Ding China
T. Ravichandran India
Peter Grant United States
Shivakumar Sastry United States
Moh. Khalid Hasan South Korea
Chun Liu China
Qiao Zhang China
Chao Gao China
Masoud Sabaei Iran
Da Wang relative to Hong Ding China Hong Ding's profile →
Citations per field
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Hong Ding · 1×
Citations per year

Countries citing papers authored by Da Wang

Since Specialization
Citations

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

Fields of papers citing papers by Da Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201572
2 201459
3 201153
4 202236
5 201434
6 202231
7 201427
8 201925
9 201821
10 202515
11 201114
12 201413
13 201012
14
Computing with Unreliable Resources: Design, Analysis and Algorithms
201410
15 201310
16
1Compression in the Space of Permutations
20148
17 20228
18 20198
19 20157
20 20137

About Da Wang

Da Wang is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Computer Networks and Communications, Hardware and Architecture and Control and Systems Engineering, having authored 53 papers that have together received 549 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (7 papers), Algorithms and Data Compression (5 papers), Error Correcting Code Techniques (5 papers), Geochemistry and Geologic Mapping (4 papers), Cloud Computing and Resource Management (4 papers), Cooperative Communication and Network Coding (4 papers), Distributed and Parallel Computing Systems (4 papers) and Wireless Communication Security Techniques (4 papers). The work is most often cited by research in Computer Networks and Communications (265 citations), Hardware and Architecture (44 citations), Artificial Intelligence (151 citations), Computational Theory and Mathematics (58 citations) and Information Systems (71 citations). Da Wang has collaborated with scholars based in China, United States and Sweden. Frequent co-authors include Gregory W. Wornell, Gauri Joshi, Yuval Kochman, Amir Ingber, Martin Servin, Claude Lacoursière, Arya Mazumdar, Changqing Zhou, Shutang Liu and Wen Wang. Their work appears in journals such as IEEE Transactions on Information Theory, ACM SIGMETRICS Performance Evaluation Review, International Journal for Numerical Methods in Engineering, International Journal of Machine Learning and Cybernetics and Applied Acoustics.

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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