Hangwei Lu

12 papers receiving 224 citations

Peers

Hangwei Lu
Comparison fields: 5 of 54
  • Hardware and Architecture 137
  • Industrial and Manufacturing Engineering 56
  • Biophysics 22
  • Electrical and Electronic Engineering 158
  • Media Technology 18
Replace Navid Asadizanjani with:
Navid Asadizanjani United States
Cédric Marchand France
Heiko Lohrke Germany
Abdullah Nazma Nowroz United States
Juejian Wu China
Shaojun Wei China
Mingtao Zhan China
Jinian Bian China
Arjun Chaudhuri United States
Kaushik Vaidyanathan United States
Hangwei Lu relative to Navid Asadizanjani United States Navid Asadizanjani's profile →
Citations per field
00.5×11×
Navid Asadizanjani · 1×
Citations per year

Countries citing papers authored by Hangwei Lu

Since Specialization
Citations

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

Fields of papers citing papers by Hangwei Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

13 of 13 papers shown
#Work
1 202155
2 202045
3 201836
4 201923
5 201914
6 202112
7 202111
8 202211
9 20246
10 20206
11 20205
12 20195
13 20131

About Hangwei Lu

Hangwei Lu is a scholar working on Electrical and Electronic Engineering, Hardware and Architecture, Artificial Intelligence, Cellular and Molecular Neuroscience and Industrial and Manufacturing Engineering, having authored 13 papers that have together received 230 indexed citations. Recurring topics across this work include Integrated Circuits and Semiconductor Failure Analysis (9 papers), Physical Unclonable Functions (PUFs) and Hardware Security (8 papers), Neuroscience and Neural Engineering (3 papers), Industrial Vision Systems and Defect Detection (3 papers), Adversarial Robustness in Machine Learning (2 papers), Bee Products Chemical Analysis (1 paper), Image and Object Detection Techniques (1 paper) and Stability and Control of Uncertain Systems (1 paper). The work is most often cited by research in Hardware and Architecture (137 citations), Industrial and Manufacturing Engineering (56 citations), Biophysics (22 citations), Electrical and Electronic Engineering (158 citations) and Media Technology (18 citations). Hangwei Lu has collaborated with scholars based in United States and China. Frequent co-authors include Damon L. Woodard, Navid Asadizanjani, Mark Tehranipoor, Mir Tanjidur Rahman, Ronald S. Wilson, Domenic Forte, Qihang Shi, Haoting Shen, Fatemeh Ganji and Mark Tehranipoor. Their work appears in journals such as ACM Journal on Emerging Technologies in Computing Systems, Molecular Pharmaceutics, American Journal of Health Behavior, IEEE Access and IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

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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