Lang Lin

1.0k citations
41 papers · 550 · h-index 13

Impact in

Papers in

Lang Lin

35 papers receiving 508 citations

Peers

Lang Lin
Comparison fields: 5 of 33
  • Hardware and Architecture 295
  • Computer Networks and Communications 163
  • Electrical and Electronic Engineering 405
  • Cellular and Molecular Neuroscience 110
  • Artificial Intelligence 165
Replace Urbi Chatterjee with:
Urbi Chatterjee India
İbrahim Ethem Bağcı United Kingdom
Mario Barbareschi Italy
Naghmeh Karimi United States
Sheng Wei United States
Sergei Skorobogatov United Kingdom
Răzvan Nane Netherlands
Bhagirath Narahari United States
David Hély France
André I. Reis Brazil
Lang Lin relative to Urbi Chatterjee India Urbi Chatterjee's profile →
Citations per field
00.5×9.7×
Urbi Chatterjee · 1×
Citations per year

Countries citing papers authored by Lang Lin

Since Specialization
Citations

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

Fields of papers citing papers by Lang Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200991
2 201062
3 201250
4 200243
5 200337
6 200335
7 200823
8 200922
9 199921
10 198519
11 201919
12 201816
13 200015
14 202112
15 200211
16 201110
17 19999
18 20208
19 20226
20 20026

About Lang Lin

Lang Lin is a scholar working on Electrical and Electronic Engineering, Hardware and Architecture, Computer Networks and Communications, Artificial Intelligence and Computational Mechanics, having authored 41 papers that have together received 550 indexed citations. Recurring topics across this work include Physical Unclonable Functions (PUFs) and Hardware Security (15 papers), Advanced Wireless Communication Techniques (12 papers), Integrated Circuits and Semiconductor Failure Analysis (11 papers), Wireless Communication Networks Research (9 papers), Cryptographic Implementations and Security (8 papers), Advanced Wireless Network Optimization (7 papers), Error Correcting Code Techniques (4 papers) and Neuroscience and Neural Engineering (3 papers). The work is most often cited by research in Hardware and Architecture (295 citations), Computer Networks and Communications (163 citations), Electrical and Electronic Engineering (405 citations), Cellular and Molecular Neuroscience (110 citations) and Artificial Intelligence (165 citations). Lang Lin has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Wayne Burleson, Christof Paar, R.S. Cheng, Roy D. Yates, Predrag Spasojević, Dilip Kumar Krishnappa, Dan Holcomb, J.C.-I. Chuang, Leonard J. Cimini and Diqun Yan. Their work appears in journals such as Neural Networks, Chinese Optics Letters, Optical Engineering, Plant Disease and EURASIP Journal on Wireless Communications and Networking.

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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