Shang Li

558 citations
17 papers · 371 indexed · h-index 7
Topics
Parallel Computing and Optimization Techniques (9 papers)Advanced Data Storage Technologies (4 papers)Advanced Memory and Neural Computing (3 papers)
Partner nations
United StatesChinaCanada

In The Last Decade

Shang Li

15 papers receiving 358 citations

Peers

Shang Li
Comparison fields: 5 of 36
  • Hardware and Architecture 228
  • Computer Networks and Communications 195
  • Electrical and Electronic Engineering 124
  • Artificial Intelligence 100
  • Computer Vision and Pattern Recognition 73
Replace Michael Kinsner with:
Michael Kinsner United States
James Hegarty United States
Utku Aydonat Canada
Dionysios Diamantopoulos Switzerland
Ching-Hsiang Chu United States
Denis Foley United States
Kermin Fleming United States
Mohammad Ali Ghodrat United States
Ofer Shacham United States
Shang Li relative to Michael Kinsner United States Michael Kinsner's profile →
Citations per field
00.5×5.8×
Michael Kinsner · 1×
Citations per year

Countries citing papers authored by Shang Li

Since Specialization
Citations

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

Fields of papers citing papers by Shang Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shang Li

This figure shows the co-authorship network connecting the top 25 collaborators of Shang Li. A scholar is included among the top collaborators of Shang Li based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Shang Li. Shang Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
#WorkIndexed citations
1 3
2 0
3 1
4 2
5 20
6 3
7 178
8 7
9 6
10 3
11 6
12 2
13 3
14 122
15 4
16 5
17 6

About Shang Li

Shang Li is a scholar working on Hardware and Architecture, Energy Engineering and Power Technology and Computer Networks and Communications, having authored 17 papers that have together received 371 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (9 papers), Advanced Data Storage Technologies (4 papers) and Advanced Memory and Neural Computing (3 papers). The work is most often cited by research in Hardware and Architecture (228 citations), Computer Networks and Communications (195 citations) and Computer Vision and Pattern Recognition (73 citations). Shang Li has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Bruce Jacob, Ankur Srivastava, Zhiyuan Yang, Robert P. Dick, Xi Chen, Haris Lekatsas, Lei Yang, Wenbo Wan, Yan Liu and Lili Meng. Their work appears in journals such as IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Optik and IEEE Micro.

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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