Daniel Wu

901 citations
31 papers · 645 · h-index 14

Impact in

Papers in

Daniel Wu

30 papers receiving 622 citations

Peers

Daniel Wu
Comparison fields: 5 of 35
  • Computer Networks and Communications 280
  • Electrical and Electronic Engineering 473
  • Hardware and Architecture 49
  • Computer Vision and Pattern Recognition 105
  • Signal Processing 28
Replace René Guillaume with:
René Guillaume Germany
David Larrabeiti Spain
Reem Melki Lebanon
Christian Zenger Germany
Fredrik Hekland Norway
Alejandra Mercado United States
Martin Collier Ireland
Xiaoming Xu China
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Wu

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010184
2 201194
3 201534
4 201133
5 200632
6 201031
7 201022
8 201222
9 201221
10 201119
11 201118
12 202217
13 200816
14 201314
15 200612
16 201212
17 201012
18 200710
19 20128
20 20147

About Daniel Wu

Daniel Wu is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications, Hardware and Architecture, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 31 papers that have together received 645 indexed citations. Recurring topics across this work include Mobile Ad Hoc Networks (13 papers), Wireless Networks and Protocols (10 papers), Advancements in PLL and VCO Technologies (9 papers), Opportunistic and Delay-Tolerant Networks (7 papers), Radio Frequency Integrated Circuit Design (7 papers), Cooperative Communication and Network Coding (5 papers), VLSI and Analog Circuit Testing (5 papers) and 3D IC and TSV technologies (4 papers). The work is most often cited by research in Computer Networks and Communications (280 citations), Electrical and Electronic Engineering (473 citations), Hardware and Architecture (49 citations), Computer Vision and Pattern Recognition (105 citations) and Signal Processing (28 citations). Daniel Wu has collaborated with scholars based in United States, China and South Korea. Frequent co-authors include Prasant Mohapatra, An Chan, Kai Zeng, Nam‐Hoon Kim, Dong‐Wook Kim, Arif Rahman, Dhruv Gupta, Kannan Govindan, Parag Upadhyaya and Jafar Savoj. Their work appears in journals such as Pervasive and Mobile Computing, IEEE Journal of Solid-State Circuits, Journal of the American Society for Mass Spectrometry, Ad Hoc Networks and IEEE Transactions on Mobile Computing.

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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