A. David Ing

1.2k total citations
17 papers, 890 citations indexed

About

A. David Ing is a scholar working on Developmental and Educational Psychology, Cognitive Neuroscience and Experimental and Cognitive Psychology. According to data from OpenAlex, A. David Ing has authored 17 papers receiving a total of 890 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Developmental and Educational Psychology, 9 papers in Cognitive Neuroscience and 4 papers in Experimental and Cognitive Psychology. Recurrent topics in A. David Ing's work include Child and Animal Learning Development (11 papers), Reading and Literacy Development (4 papers) and Visual perception and processing mechanisms (3 papers). A. David Ing is often cited by papers focused on Child and Animal Learning Development (11 papers), Reading and Literacy Development (4 papers) and Visual perception and processing mechanisms (3 papers). A. David Ing collaborates with scholars based in United States and United Kingdom. A. David Ing's co-authors include W. Todd Maddox, J. Vincent Filoteo, Corey J. Bohil, F. Gregory Ashby, Alan D. Pickering, Darren R. Gitelman, Emi Nomura, Paul J. Reber, Todd B. Parrish and Wilson S. Geisler and has published in prestigious journals such as Cerebral Cortex, Neuropsychologia and Journal of Experimental Psychology Learning Memory and Cognition.

In The Last Decade

A. David Ing

15 papers receiving 860 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
A. David Ing United States	13	586	483	161	142	96	17	890
Shawn W. Ell United States	15	623 1.1×	496 1.0×	199 1.2×	137 1.0×	130 1.4×	29	1.0k
Leola A. Alfonso-Reese United States	6	595 1.0×	670 1.4×	265 1.6×	173 1.2×	222 2.3×	8	1.1k
Christian Forkstam Netherlands	15	739 1.3×	415 0.9×	138 0.9×	94 0.7×	92 1.0×	22	967
Billi Randall United Kingdom	20	1.4k 2.4×	776 1.6×	286 1.8×	177 1.2×	154 1.6×	25	1.6k
Elliott M. Waldron United States	10	957 1.6×	1.0k 2.1×	364 2.3×	271 1.9×	256 2.7×	12	1.6k
Po‐Jang Hsieh Singapore	14	939 1.6×	165 0.3×	182 1.1×	148 1.0×	38 0.4×	42	1.1k
Brian J. Spiering United States	8	396 0.7×	243 0.5×	86 0.5×	123 0.9×	58 0.6×	9	629
Felipe Pegado France	12	1.1k 1.9×	813 1.7×	315 2.0×	121 0.9×	35 0.4×	27	1.5k
Douglas Saddy United Kingdom	15	904 1.5×	530 1.1×	176 1.1×	71 0.5×	104 1.1×	46	1.1k
Sam S. Rakover Israel	12	609 1.0×	178 0.4×	274 1.7×	176 1.2×	41 0.4×	49	908

Countries citing papers authored by A. David Ing

Since Specialization

Citations

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

Fields of papers citing papers by A. David Ing

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of A. David Ing

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

All Works

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17 of 17 papers shown

Rellini, Alessandra H., A. David Ing, & Cindy M. Meston. (2011). Implicit and Explicit Cognitive Sexual Processes in Survivors of Childhood Sexual Abuse. The Journal of Sexual Medicine. 8(11). 3098–3107. 17 indexed citations

Ing, A. David. (2010). Region grouping in natural foliage scenes: Image statistics and human performance. Journal of Vision. 10(4). 1–19. 58 indexed citations

Ing, A. David & Wilson S. Geisler. (2010). Ribbon analysis of contours in natural images. Journal of Vision. 6(6). 103–103.

Wilson, J. A., A. David Ing, & Wilson S. Geisler. (2010). Chromatic differences within surfaces and across surface boundaries. Journal of Vision. 6(6). 559–559.

Ell, Shawn W., A. David Ing, & W. Todd Maddox. (2009). Critrial noise effects on rule-based category learning: The impact of delayed feedback. Attention Perception & Psychophysics. 71(6). 1263–1275. 21 indexed citations

Geisler, Wilson S., J. Najemnik, & A. David Ing. (2009). Optimal stimulus encoders for natural tasks. Journal of Vision. 9(13). 17–17. 42 indexed citations

Geisler, Wilson S., Jeffrey S. Perry, & A. David Ing. (2008). Natural systems analysis. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6806. 68060M–68060M. 11 indexed citations

Maddox, W. Todd, J. Scott Lauritzen, & A. David Ing. (2007). Cognitive complexity effects in perceptual classification are dissociable. Memory & Cognition. 35(5). 885–894. 11 indexed citations

Maddox, W. Todd, A. David Ing, & J. Scott Lauritzen. (2006). Stimulus modality interacts with category structure in perceptual category learning. Perception & Psychophysics. 68(7). 1176–1190. 20 indexed citations

10.

Nomura, Emi, W. Todd Maddox, J. Vincent Filoteo, et al.. (2006). Neural Correlates of Rule-Based and Information-Integration Visual Category Learning. Cerebral Cortex. 17(1). 37–43. 166 indexed citations

11.

Filoteo, J. Vincent, W. Todd Maddox, A. David Ing, & David Song. (2006). Characterizing rule-based category learning deficits in patients with Parkinson's disease. Neuropsychologia. 45(2). 305–320. 35 indexed citations

12.

Maddox, W. Todd & A. David Ing. (2005). Delayed Feedback Disrupts the Procedural-Learning System but Not the Hypothesis-Testing System in Perceptual Category Learning.. Journal of Experimental Psychology Learning Memory and Cognition. 31(1). 100–107. 118 indexed citations

13.

Filoteo, J. Vincent, W. Todd Maddox, Alan N. Simmons, et al.. (2005). Cortical and subcortical brain regions involved in rule-based category learning. Neuroreport. 16(2). 111–115. 65 indexed citations

14.

Filoteo, J. Vincent, et al.. (2005). The impact of irrelevant dimensional variation on rule-based category learning in patients with Parkinson's disease. Journal of the International Neuropsychological Society. 11(5). 503–513. 31 indexed citations

15.

Maddox, W. Todd, Corey J. Bohil, & A. David Ing. (2004). Evidence for a procedural-learning-based system in perceptual category learning. Psychonomic Bulletin & Review. 11(5). 945–952. 97 indexed citations

16.

Maddox, W. Todd, et al.. (2004). Category Number Impacts Rule-Based but Not Information-Integration Category Learning: Further Evidence for Dissociable Category-Learning Systems.. Journal of Experimental Psychology Learning Memory and Cognition. 30(1). 227–245. 74 indexed citations

17.

Maddox, W. Todd, F. Gregory Ashby, A. David Ing, & Alan D. Pickering. (2004). Disrupting feedback processing interferes with rule-based but not information-integration category learning. Memory & Cognition. 32(4). 582–591. 124 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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