Lichao Yang

603 total citations · 1 hit paper
25 papers, 359 citations indexed

About

Lichao Yang is a scholar working on Mechanics of Materials, Automotive Engineering and Civil and Structural Engineering. According to data from OpenAlex, Lichao Yang has authored 25 papers receiving a total of 359 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Mechanics of Materials, 6 papers in Automotive Engineering and 5 papers in Civil and Structural Engineering. Recurrent topics in Lichao Yang's work include Autonomous Vehicle Technology and Safety (5 papers), Infrastructure Maintenance and Monitoring (5 papers) and Thermography and Photoacoustic Techniques (5 papers). Lichao Yang is often cited by papers focused on Autonomous Vehicle Technology and Safety (5 papers), Infrastructure Maintenance and Monitoring (5 papers) and Thermography and Photoacoustic Techniques (5 papers). Lichao Yang collaborates with scholars based in United Kingdom, China and Singapore. Lichao Yang's co-authors include Yifan Zhao, Yimin Wu, Zijian Wang, James Brighton, Haochen Liu, Jun Cao, Xiaocai Shan, Ptolemaios G. Sarrigiannis, Zhuangkun Wei and Sri Addepalli and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, Expert Systems with Applications and Sensors.

In The Last Decade

Lichao Yang

24 papers receiving 345 citations

Hit Papers

Fast Personal Protective Equipment Detection for Real Con... 2021 2026 2022 2024 2021 40 80 120

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Lichao Yang United Kingdom 10 92 65 61 60 43 25 359
Volker Wittstock Germany 11 103 1.1× 42 0.6× 37 0.6× 108 1.8× 16 0.4× 46 454
Haosen Chen Australia 9 102 1.1× 214 3.3× 111 1.8× 62 1.0× 30 0.7× 19 677
Norbert Elkmann Germany 16 148 1.6× 29 0.4× 70 1.1× 134 2.2× 6 0.1× 67 772
Arya Haghighat United States 7 79 0.9× 64 1.0× 26 0.4× 12 0.2× 32 0.7× 10 400
José Saenz Germany 13 95 1.0× 13 0.2× 49 0.8× 102 1.7× 8 0.2× 26 477
Prasad Prabhu United States 10 24 0.3× 24 0.4× 119 2.0× 109 1.8× 25 0.6× 21 365
Sara Bagassi Italy 9 42 0.5× 30 0.5× 7 0.1× 26 0.4× 8 0.2× 34 272
Todd M. Ruff United States 9 19 0.2× 34 0.5× 162 2.7× 12 0.2× 40 0.9× 21 327
Byungtae Jang South Korea 10 42 0.5× 11 0.2× 6 0.1× 14 0.2× 25 0.6× 41 425

Countries citing papers authored by Lichao Yang

Since Specialization
Citations

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

Fields of papers citing papers by Lichao Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lichao Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Lichao Yang. A scholar is included among the top collaborators of Lichao Yang 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 Lichao Yang. Lichao Yang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
3.
Liu, Haochen, et al.. (2024). Attention mechanism enhanced spatiotemporal-based deep learning approach for classifying barely visible impact damages in CFRP materials. Composite Structures. 337. 118030–118030. 9 indexed citations
4.
Wei, Zhuangkun, et al.. (2024). A Review of Digital Twin Technologies for Enhanced Sustainability in the Construction Industry. Buildings. 14(4). 1113–1113. 25 indexed citations
5.
Yang, Lichao, et al.. (2024). Achieving On-Site Trustworthy AI Implementation in the Construction Industry: A Framework Across the AI Lifecycle. Buildings. 15(1). 21–21. 3 indexed citations
6.
Cao, Jun, Lichao Yang, Ptolemaios G. Sarrigiannis, D. Blackburn, & Yifan Zhao. (2023). Dementia classification using a graph neural network on imaging of effective brain connectivity. Computers in Biology and Medicine. 168. 107701–107701. 17 indexed citations
7.
Liu, Haochen, et al.. (2023). Classification of barely visible impact damage in composite laminates using deep learning and pulsed thermographic inspection. Neural Computing and Applications. 35(15). 11207–11221. 11 indexed citations
8.
Yang, Lichao, et al.. (2023). Keypoints-based Heterogeneous Graph Convolutional Networks for construction. Expert Systems with Applications. 237. 121525–121525. 5 indexed citations
9.
Yang, Lichao, et al.. (2023). A lightweight temporal attention-based convolution neural network for driver's activity recognition in edge. Computers & Electrical Engineering. 110. 108861–108861. 4 indexed citations
10.
Wang, Yizhong, Haochen Liu, Lichao Yang, et al.. (2023). A full 3D reconstruction of rail tracks using a camera array. Measurement. 225. 114034–114034. 6 indexed citations
11.
Shan, Xiaocai, Shoudong Huo, Lichao Yang, et al.. (2021). A Revised Hilbert-Huang Transformation to Track Non-Stationary Association of Electroencephalography Signals. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 29. 841–851. 11 indexed citations
12.
Yang, Lichao, et al.. (2021). The Identification of Non-Driving Activities with Associated Implication on the Take-Over Process. Sensors. 22(1). 42–42. 7 indexed citations
13.
Yang, Lichao, et al.. (2021). Infer Thermal Information from Visual Information: A Cross Imaging Modality Edge Learning (CIMEL) Framework. Sensors. 21(22). 7471–7471. 3 indexed citations
14.
Wang, Shiyi, et al.. (2021). Machine Learning Approaches to Identify Environmental Damage on Superalloys. SSRN Electronic Journal. 1 indexed citations
15.
Yang, Lichao, et al.. (2021). Recognition of visual-related non-driving activities using a dual-camera monitoring system. Pattern Recognition. 116. 107955–107955. 14 indexed citations
16.
Yang, Lichao, et al.. (2021). Pattern Recognition of Barely Visible Impact Damage in Carbon Composites Using Pulsed Thermography. IEEE Transactions on Industrial Informatics. 18(10). 7252–7261. 10 indexed citations
17.
Wang, Zijian, et al.. (2021). Fast Personal Protective Equipment Detection for Real Construction Sites Using Deep Learning Approaches. Sensors. 21(10). 3478–3478. 138 indexed citations breakdown →
18.
Yang, Lichao, et al.. (2020). The implication of non-driving activities on situation awareness and take-over performance in level 3 automation. IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society. 5075–5080. 4 indexed citations
19.
Yang, Lichao, Tingyu Yang, Haochen Liu, et al.. (2020). A Refined Non-Driving Activity Classification Using a Two-Stream Convolutional Neural Network. IEEE Sensors Journal. 21(14). 15574–15583. 14 indexed citations
20.
Yang, Lichao, et al.. (2019). A Dual-Cameras-Based Driver Gaze Mapping System With an Application on Non-Driving Activities Monitoring. IEEE Transactions on Intelligent Transportation Systems. 21(10). 4318–4327. 41 indexed citations

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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