Lie Yang

31 papers receiving 440 citations

Lie Yang's Hit Papers

Human-Guided Continual Learning for Personalized Decision-Making of Autonomous Driving 2025 · 16 citations
160Years since publication51015

Peers

Lie Yang
Comparison fields: 5 of 65
  • Human-Computer Interaction 49
  • Cognitive Neuroscience 159
  • Automotive Engineering 60
  • Control and Systems Engineering 103
  • Experimental and Cognitive Psychology 58
Replace Amin Hosseini with:
Amin Hosseini Iran
Ye Wang United States
Ce Zhang United States
Éric Monacelli France
Ali Farzamnia Malaysia
Jinwei Sun China
Luis J. Manso Spain
Omid Dehzangi United States
M.P. Paulraj Malaysia
Lie Yang relative to Amin Hosseini Iran Amin Hosseini's profile →
Citations per field
00.5×2.9×
Amin Hosseini · 1×
Citations per year

Countries citing papers authored by Lie Yang

Since Specialization
Citations

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

Fields of papers citing papers by Lie Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202179
2 202141
3 202040
4 202034
5 202128
6 202324
7 202324
8 202419
9 202018
10 202017
11
Human-Guided Continual Learning for Personalized Decision-Making of Autonomous Driving
Hit paper breakdown →
202516
12 202114
13 202414
14 202111
15 20249
16 20218
17 20208
18 20187
19 20185
20 20215

About Lie Yang

Lie Yang is a scholar working on Control and Systems Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition, Cognitive Neuroscience and Automotive Engineering, having authored 32 papers that have together received 449 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (7 papers), Neuroscience and Neural Engineering (5 papers), Autonomous Vehicle Technology and Safety (5 papers), Machine Fault Diagnosis Techniques (4 papers), Gaze Tracking and Assistive Technology (3 papers), Inertial Sensor and Navigation (3 papers), Emotion and Mood Recognition (3 papers) and Video Surveillance and Tracking Methods (3 papers). The work is most often cited by research in Human-Computer Interaction (49 citations), Cognitive Neuroscience (159 citations), Automotive Engineering (60 citations), Control and Systems Engineering (103 citations) and Experimental and Cognitive Psychology (58 citations). Lie Yang has collaborated with scholars based in China, Singapore and Hong Kong. Frequent co-authors include Longhan Xie, Yonghao Song, Ke Ma, Chen Lv, Ruxu Du, Yong Zhong, Guo Yang, Haohan Yang, Bin-Bin Hu and Jianying Li. Their work appears in journals such as IEEE Transactions on Intelligent Transportation Systems, Knowledge-Based Systems, IEEE Transactions on Instrumentation and Measurement, Review of Scientific Instruments and Journal of Neural Engineering.

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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