Lu Cheng

77 papers receiving 1.4k citations

Lu Cheng's Hit Papers

MPED: A Multi-Modal Physiological Emotion Database for Discrete Emotion Recognition 2019 · 275 citations
2750+2+4Years since publication50100150200250

Peers

Lu Cheng
Comparison fields: 5 of 115
  • Health Informatics 45
  • Experimental and Cognitive Psychology 246
  • Artificial Intelligence 621
  • Signal Processing 165
  • Social Psychology 265
Replace Kasia Müldner with:
Kasia Müldner Canada
Albert Gatt Malta
Andrew McGregor Olney United States
Kenneth M. Ford United States
Christopher A. Brooks United States
Ute Schmid Germany
Jesús González Boticario Spain
Zoraida Callejas Spain
Daniel Graziotin Germany
Jonathan Rowe United States
Lu Cheng relative to Kasia Müldner Canada Kasia Müldner's profile →
Citations per field
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Kasia Müldner · 1×
Citations per year

Countries citing papers authored by Lu Cheng

Since Specialization
Citations

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

Fields of papers citing papers by Lu Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 83 papers — load more, or switch the sort, to bring in the rest.

#Work
1
MPED: A Multi-Modal Physiological Emotion Database for Discrete Emotion Recognition
Hit paper breakdown →
2019275
2 2021169
3 201996
4 201968
5 202152
6 201750
7 202250
8
Concrete-Pictorial-Abstract: Surveying its origins and charting its future
201548
9 202046
10 202133
11 202130
12 202029
13 201929
14 202024
15 201921
16 202119
17 201917
18 202417
19 202217
20 201516

About Lu Cheng

Lu Cheng is a scholar working on Artificial Intelligence, Statistics and Probability, Education, Information Systems and Developmental and Educational Psychology, having authored 83 papers that have together received 1.4k indexed citations. Recurring topics across this work include Mathematics Education and Teaching Techniques (14 papers), Hate Speech and Cyberbullying Detection (11 papers), Bullying, Victimization, and Aggression (8 papers), Education and Technology Integration (8 papers), Topic Modeling (7 papers), Cognitive and developmental aspects of mathematical skills (6 papers), Educational Games and Gamification (6 papers) and Ethics and Social Impacts of AI (6 papers). The work is most often cited by research in Health Informatics (45 citations), Experimental and Cognitive Psychology (246 citations), Artificial Intelligence (621 citations), Signal Processing (165 citations) and Social Psychology (265 citations). Lu Cheng has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Huan Liu, Ruocheng Guo, Deborah L. Hall, Kush R. Varshney, Zhen Cui, Wenming Zheng, Tengfei Song, Yuan Zong, Xilei Zhang and Yasin N. Silva. Their work appears in journals such as ACM Transactions on Knowledge Discovery from Data, Mathematics Education Research Journal, ACM Computing Surveys, International Journal of Bullying Prevention and IEEE Internet Computing.

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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