Ming Yan

2.0k citations
71 papers · 1.4k · h-index 22

Impact in

Papers in

Ming Yan

67 papers receiving 1.3k citations

Peers

Ming Yan
Comparison fields: 5 of 61
  • Developmental and Educational Psychology 1.1k
  • Cognitive Neuroscience 945
  • Human-Computer Interaction 217
  • Experimental and Cognitive Psychology 471
  • Statistics and Probability 75
Replace Bernhard Angele with:
Bernhard Angele United Kingdom
Hazel I. Blythe United Kingdom
Chuanli Zang China
Jinmian Yang United States
David Zola United States
Alexander Pollatsek United States
Keith Rayner United States
Stefan Hawelka Austria
Victoria A. McGowan United Kingdom
Wayne S. Murray United Kingdom
Ming Yan relative to Bernhard Angele United Kingdom Bernhard Angele's profile →
Citations per field
00.5×1.7×
Bernhard Angele · 1×
Citations per year

Countries citing papers authored by Ming Yan

Since Specialization
Citations

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

Fields of papers citing papers by Ming Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 71 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009164
2 2009151
3 201274
4 201267
5 201360
6 201457
7 201451
8 201036
9 201231
10 201629
11 201828
12 201428
13 201627
14 200926
15 202025
16 202124
17 201524
18 201624
19 201024
20 201722

About Ming Yan

Ming Yan is a scholar working on Developmental and Educational Psychology, Cognitive Neuroscience, Experimental and Cognitive Psychology, Human-Computer Interaction and Artificial Intelligence, having authored 71 papers that have together received 1.4k indexed citations. Recurring topics across this work include Reading and Literacy Development (52 papers), Neurobiology of Language and Bilingualism (35 papers), Multisensory perception and integration (16 papers), Gaze Tracking and Assistive Technology (11 papers), Visual perception and processing mechanisms (10 papers), Neural and Behavioral Psychology Studies (10 papers), Language, Metaphor, and Cognition (9 papers) and Tactile and Sensory Interactions (8 papers). The work is most often cited by research in Developmental and Educational Psychology (1.1k citations), Cognitive Neuroscience (945 citations), Human-Computer Interaction (217 citations), Experimental and Cognitive Psychology (471 citations) and Statistics and Probability (75 citations). Ming Yan has collaborated with scholars based in China, Germany and Macao. Frequent co-authors include Reinhold Kliegl, Hua Shu, Jinger Pan, Eike M. Richter, Wei Zhou, Jochen Laubrock, Antje Nuthmann, Aiping Wang, Jie-Li Tsai and Sven Hohenstein. Their work appears in journals such as Journal of Experimental Psychology Learning Memory and Cognition, Reading and Writing, Scientific Studies of Reading, Psychonomic Bulletin & Review and Behavior Research Methods.

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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