Wai-Tat Fu

698 total citations
10 papers, 415 citations indexed

About

Wai-Tat Fu is a scholar working on Cognitive Neuroscience, Developmental and Educational Psychology and Artificial Intelligence. According to data from OpenAlex, Wai-Tat Fu has authored 10 papers receiving a total of 415 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Cognitive Neuroscience, 5 papers in Developmental and Educational Psychology and 3 papers in Artificial Intelligence. Recurrent topics in Wai-Tat Fu's work include Neural and Behavioral Psychology Studies (4 papers), Behavioral and Psychological Studies (3 papers) and Child and Animal Learning Development (3 papers). Wai-Tat Fu is often cited by papers focused on Neural and Behavioral Psychology Studies (4 papers), Behavioral and Psychological Studies (3 papers) and Child and Animal Learning Development (3 papers). Wai-Tat Fu collaborates with scholars based in United States and China. Wai-Tat Fu's co-authors include John R. Anderson, Wayne D. Gray, Michael J. Schoelles, Chris R. Sims, Daniel Morrow, Xiaomei Liu, Ziang Xiao, Elizabeth A. L. Stine‐Morrow, Sanorita Dey and Jessie Chin and has published in prestigious journals such as Psychological Review, Journal of Experimental Psychology General and Psychology and Aging.

In The Last Decade

Wai-Tat Fu

10 papers receiving 385 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Wai-Tat Fu United States	6	207	97	87	76	74	10	415
Ion Juvina United States	14	253 1.2×	148 1.5×	84 1.0×	125 1.6×	92 1.2×	49	644
Dan Bothell United States	2	214 1.0×	117 1.2×	66 0.8×	93 1.2×	78 1.1×	3	376
Andrea Schankin Germany	14	373 1.8×	62 0.6×	74 0.9×	179 2.4×	48 0.6×	34	642
Doris M. Dehn Germany	6	165 0.8×	191 2.0×	225 2.6×	146 1.9×	156 2.1×	9	588
Mark R. Blair Canada	13	231 1.1×	115 1.2×	63 0.7×	130 1.7×	268 3.6×	38	614
Lydia Tan United Kingdom	11	615 3.0×	165 1.7×	67 0.8×	198 2.6×	156 2.1×	15	723
Amir Mané United States	9	119 0.6×	104 1.1×	95 1.1×	106 1.4×	105 1.4×	13	388
Mackenzie G. Glaholt Canada	14	521 2.5×	80 0.8×	132 1.5×	188 2.5×	169 2.3×	25	810
Dieter Wallach Germany	10	115 0.6×	85 0.9×	64 0.7×	91 1.2×	39 0.5×	30	354
Joseph W. Houpt United States	14	462 2.2×	87 0.9×	176 2.0×	224 2.9×	70 0.9×	64	709

Countries citing papers authored by Wai-Tat Fu

Since Specialization

Citations

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

Fields of papers citing papers by Wai-Tat Fu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wai-Tat Fu. 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 Wai-Tat Fu. The network helps show where Wai-Tat Fu may publish in the future.

Co-authorship network of co-authors of Wai-Tat Fu

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

All Works

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10 of 10 papers shown

Xiao, Ziang, et al.. (2020). Understanding Interrelated Growth Mind-set and Academic Participation & Performance. Papers on Engineering Education Repository (American Society for Engineering Education). 1 indexed citations

Fu, Wai-Tat. (2018). Bridging behavioral and naturalistic decision-making research by computational cognitive models.. Journal of Applied Research in Memory and Cognition. 7(1). 16–18. 1 indexed citations

Xiao, Ziang, et al.. (2018). A Scalable Online Platform for Evaluating and Training Visuospatial Skills of Engineering Students. 5 indexed citations

Liu, Xiaomei, Jessie Chin, Brennan R. Payne, et al.. (2016). Adult age differences in information foraging in an interactive reading environment.. Psychology and Aging. 31(3). 211–223. 8 indexed citations

Kannampallil, Thomas, et al.. (2010). Collaborative Tools in a Simulated Patient-Provider Medication Scheduling Task. Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 54(23). 1936–1940. 3 indexed citations

Fu, Wai-Tat & John R. Anderson. (2008). Dual learning processes in interactive skill acquisition.. Journal of Experimental Psychology Applied. 14(2). 179–191. 16 indexed citations

Fu, Wai-Tat, et al.. (2008). A Situated Cognitive Model of the Routine Evolution of Skills. Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 52(13). 935–939. 2 indexed citations

Fu, Wai-Tat & John R. Anderson. (2007). Solving the credit assignment problem: explicit and implicit learning of action sequences with probabilistic outcomes. Psychological Research. 72(3). 321–330. 39 indexed citations

Fu, Wai-Tat & John R. Anderson. (2006). From recurrent choice to skill learning: A reinforcement-learning model.. Journal of Experimental Psychology General. 135(2). 184–206. 105 indexed citations

10.

Gray, Wayne D., Chris R. Sims, Wai-Tat Fu, & Michael J. Schoelles. (2006). The soft constraints hypothesis: A rational analysis approach to resource allocation for interactive behavior.. Psychological Review. 113(3). 461–482. 235 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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