David Liu

2.0k total citations
22 papers, 1.3k citations indexed

About

David Liu is a scholar working on Developmental and Educational Psychology, Cognitive Neuroscience and Social Psychology. According to data from OpenAlex, David Liu has authored 22 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Developmental and Educational Psychology, 6 papers in Cognitive Neuroscience and 4 papers in Social Psychology. Recurrent topics in David Liu's work include Child and Animal Learning Development (10 papers), Memory and Neural Mechanisms (4 papers) and Educational Strategies and Epistemologies (2 papers). David Liu is often cited by papers focused on Child and Animal Learning Development (10 papers), Memory and Neural Mechanisms (4 papers) and Educational Strategies and Epistemologies (2 papers). David Liu collaborates with scholars based in United States, Australia and Canada. David Liu's co-authors include Henry M. Wellman, Mark A. Sabbagh, Candida C. Peterson, Twila Tardif, William J. Gehring, Gail D. Heyman, Kimberly E. Vanderbilt, Susan A. Gelman, John E. Morley and Margaret‐Mary G. Wilson and has published in prestigious journals such as Journal of Biological Chemistry, PLoS ONE and Child Development.

In The Last Decade

David Liu

22 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Liu United States 14 777 480 371 146 142 22 1.3k
Carmen Flores-Mendoza Brazil 16 286 0.4× 311 0.6× 136 0.4× 152 1.0× 93 0.7× 59 1.3k
Yoon Joo Hong South Korea 6 634 0.8× 403 0.8× 149 0.4× 344 2.4× 40 0.3× 7 1.3k
Tova Most Israel 24 1.0k 1.3× 922 1.9× 86 0.2× 369 2.5× 237 1.7× 82 1.9k
Elsje van Bergen Netherlands 24 1.1k 1.4× 430 0.9× 107 0.3× 157 1.1× 87 0.6× 51 1.7k
Anne Watson O'Reilly United States 17 409 0.5× 131 0.3× 210 0.6× 194 1.3× 72 0.5× 19 950
Helena Viholainen Finland 16 598 0.8× 145 0.3× 128 0.3× 109 0.7× 46 0.3× 33 985
Marianne E. Lloyd United States 12 261 0.3× 436 0.9× 128 0.3× 154 1.1× 71 0.5× 24 822
Craig R. Barclay United States 13 646 0.8× 526 1.1× 175 0.5× 81 0.6× 95 0.7× 25 1.3k
Rosie Perkins United Kingdom 25 94 0.1× 395 0.8× 748 2.0× 215 1.5× 115 0.8× 67 1.6k
Tiffany Hutchins United States 17 547 0.7× 601 1.3× 227 0.6× 584 4.0× 80 0.6× 40 1.3k

Countries citing papers authored by David Liu

Since Specialization
Citations

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

Fields of papers citing papers by David Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Liu

This figure shows the co-authorship network connecting the top 25 collaborators of David Liu. A scholar is included among the top collaborators of David Liu 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 David Liu. David Liu 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.
Kulkarni, Vishnutheertha, et al.. (2024). Risk Factors Associated With Burden of Disease of Psoriasis From 1990 to 2019: Epidemiological Analysis. JMIR Dermatology. 7. e48749–e48749. 2 indexed citations
2.
Lee, Sam, Cindi Chen, David Liu, et al.. (2023). Case Series: Unbiased Deep Sequencing Analysis of Acute Infectious Conjunctivitis in an Ambulatory Eye Center in Berkeley, California. Optometry and Vision Science. 100(4). 276–280. 2 indexed citations
3.
Liu, David, et al.. (2023). Changes in Radiology Due to Artificial Intelligence That Can Attract Medical Students to the Specialty. JMIR Medical Education. 9. e43415–e43415. 6 indexed citations
4.
Kulkarni, Vishnutheertha, et al.. (2023). Integrative Approaches to Sleep Management in Skin Disease: Systematic Review. JMIR Dermatology. 6. e48713–e48713. 1 indexed citations
5.
Liu, David, et al.. (2022). Perceptions of US Medical Students on Artificial Intelligence in Medicine: Mixed Methods Survey Study. JMIR Medical Education. 8(4). e38325–e38325. 39 indexed citations
6.
Kulkarni, Vishnutheertha, et al.. (2022). Global epidemiology of itch from 1990 to 2017: gender, age, sanitation, and air pollution as risk factors. 7(1). e60–e60. 2 indexed citations
7.
8.
Liu, David, Peng Shi, Po‐Hsin Chou, et al.. (2017). Annulus fibrosus cells express and utilize C-C chemokine receptor 5 (CCR5) for migration. The Spine Journal. 17(5). 720–726. 22 indexed citations
9.
Mao, Yurong, Zhenzhu Tang, Julio Montaner, et al.. (2016). Loss to Follow-Up from HIV Screening to ART Initiation in Rural China. PLoS ONE. 11(10). e0164346–e0164346. 9 indexed citations
10.
Liu, David, Kimberly E. Vanderbilt, & Gail D. Heyman. (2013). Selective trust: Children's use of intention and outcome of past testimony.. Developmental Psychology. 49(3). 439–445. 48 indexed citations
11.
Bowman, Lindsay C., David Liu, Andrew N. Meltzoff, & Henry M. Wellman. (2012). Neural correlates of belief‐ and desire‐reasoning in 7‐ and 8‐year‐old children: an event‐related potential study. Developmental Science. 15(5). 618–632. 25 indexed citations
12.
Liu, David, Andrew N. Meltzoff, & Henry M. Wellman. (2009). Neural Correlates of Belief- and Desire-Reasoning. Child Development. 80(4). 1163–1171. 49 indexed citations
13.
Liu, David, Mark A. Sabbagh, William J. Gehring, & Henry M. Wellman. (2009). Neural Correlates of Children’s Theory of Mind Development. Child Development. 80(2). 318–326. 88 indexed citations
14.
Liu, David, Henry M. Wellman, Twila Tardif, & Mark A. Sabbagh. (2008). Theory of mind development in Chinese children: A meta-analysis of false-belief understanding across cultures and languages.. Developmental Psychology. 44(2). 523–531. 273 indexed citations
15.
Liu, David, Susan A. Gelman, & Henry M. Wellman. (2007). Components of Young Children’s Trait Understanding: Behavior-to-Trait Inferences and Trait-to-Behavior Predictions. Child Development. 78(5). 1543–1558. 102 indexed citations
16.
Peterson, Candida C., Henry M. Wellman, & David Liu. (2005). Steps in Theory-of-Mind Development for Children With Deafness or Autism. Child Development. 76(2). 502–517. 308 indexed citations
17.
Tardif, Twila, et al.. (2005). Preschoolers' Understanding of Knowing-That and Knowing-How in the United States and Hong Kong.. Developmental Psychology. 41(3). 562–573. 18 indexed citations
18.
Liu, David, Mark A. Sabbagh, William J. Gehring, & Henry M. Wellman. (2004). Decoupling beliefs from reality in the brain: an ERP study of theory of mind. Neuroreport. 15(6). 991–995. 63 indexed citations
19.
Wilson, Margaret‐Mary G., Surender K. Vaswani, David Liu, John E. Morley, & Douglas K. Miller. (1998). Prevalence and Causes of Undernutrition in Medical Outpatients. The American Journal of Medicine. 104(1). 56–63. 135 indexed citations
20.
Feng, Yingqing, Lisa J. Garrard, Glenn McEnroe, et al.. (1998). Peptides Derived from the Complementarity-determining Regions of Anti-Mac-1 Antibodies Block Intercellular Adhesion Molecule-1 Interaction with Mac-1. Journal of Biological Chemistry. 273(10). 5625–5630. 25 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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