Shaohan Hu

66 papers receiving 2.1k citations

Shaohan Hu's Hit Papers

Evidence of scaling advantage for the quantum approximate optimization algorithm on a classically intractable problem 2024 · 81 citations
810+3+6Years since publication100200300400500

Peers

Shaohan Hu
Comparison fields: 5 of 84
  • Computer Science Applications 368
  • Computer Vision and Pattern Recognition 546
  • Artificial Intelligence 483
  • Computer Networks and Communications 295
  • Transportation 70
Replace Shuochao Yao with:
Shuochao Yao United States
Yuanqing Zheng Hong Kong
Guangtao Xue China
Youngki Lee South Korea
Yu Xiao Finland
Longfei Shangguan United States
Pengfei Zhou Singapore
Eyal de Lara Canada
Guobin Shen China
Lama Nachman United States
Shaohan Hu relative to Shuochao Yao United States Shuochao Yao's profile →
Citations per field
00.5×2×4×5.9×
Shuochao Yao · 1×
Citations per year

Countries citing papers authored by Shaohan Hu

Since Specialization
Citations

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

Fields of papers citing papers by Shaohan Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 69 papers — load more, or switch the sort, to bring in the rest.

#Work
1
DeepSense
Hit paper breakdown →
2017542
2 2010178
3 2015162
4 2011142
5 2018105
6
Evidence of scaling advantage for the quantum approximate optimization algorithm on a classically intractable problem
Hit paper breakdown →
202481
7 201348
8 201446
9 201845
10 201444
11 201543
12 201543
13 201943
14 202242
15 201441
16 202136
17 201635
18 202333
19 202128
20 201524

About Shaohan Hu

Shaohan Hu is a scholar working on Computer Science Applications, Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications and Hardware and Architecture, having authored 69 papers that have together received 2.2k indexed citations. Recurring topics across this work include Mobile Crowdsensing and Crowdsourcing (17 papers), Quantum Computing Algorithms and Architecture (11 papers), Context-Aware Activity Recognition Systems (10 papers), Distributed Sensor Networks and Detection Algorithms (5 papers), Target Tracking and Data Fusion in Sensor Networks (4 papers), Advanced Neural Network Applications (4 papers), Cloud Computing and Resource Management (3 papers) and Green IT and Sustainability (3 papers). The work is most often cited by research in Computer Science Applications (368 citations), Computer Vision and Pattern Recognition (546 citations), Artificial Intelligence (483 citations), Computer Networks and Communications (295 citations) and Transportation (70 citations). Shaohan Hu has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Tarek Abdelzaher, Shuochao Yao, Yiran Zhao, Aston Zhang, Lü Su, Hengchang Liu, Andrew Thomas Campbell, Tanzeem Choudhury, Hong Lu and Hongyan Wang. Their work appears in journals such as Computer, IEEE Transactions on Mobile Computing, ACM Transactions on Sensor Networks, Quantum and Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies.

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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