Jason Haberman

3.5k total citations · 1 hit paper
25 papers, 2.3k citations indexed

About

Jason Haberman is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Experimental and Cognitive Psychology. According to data from OpenAlex, Jason Haberman has authored 25 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Cognitive Neuroscience, 10 papers in Computer Vision and Pattern Recognition and 3 papers in Experimental and Cognitive Psychology. Recurrent topics in Jason Haberman's work include Visual perception and processing mechanisms (13 papers), Face Recognition and Perception (12 papers) and Visual Attention and Saliency Detection (5 papers). Jason Haberman is often cited by papers focused on Visual perception and processing mechanisms (13 papers), Face Recognition and Perception (12 papers) and Visual Attention and Saliency Detection (5 papers). Jason Haberman collaborates with scholars based in United States, Canada and Philippines. Jason Haberman's co-authors include David Whitney, Petr Janata, Mark Beeman, Jennifer L. Frymiare, R.E. Greenblatt, Paul J. Reber, Edward M. Bowden, John Kounios, George A. Alvarez and Timothy F. Brady and has published in prestigious journals such as PLoS ONE, Current Biology and Brain Research.

In The Last Decade

Jason Haberman

25 papers receiving 2.2k citations

Hit Papers

Neural Activity When People Solve Verbal Problems with In... 2004 2026 2011 2018 2004 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jason Haberman United States 11 1.9k 901 467 294 148 25 2.3k
Timothy L. Hubbard United States 30 2.3k 1.2× 1.0k 1.1× 1.1k 2.4× 194 0.7× 572 3.9× 107 3.0k
Robert D. Melara United States 30 1.9k 1.0× 1.2k 1.4× 448 1.0× 80 0.3× 286 1.9× 78 2.7k
Dirk Vorberg Germany 22 1.8k 0.9× 445 0.5× 349 0.7× 117 0.4× 525 3.5× 42 2.1k
Nori Jacoby United States 21 963 0.5× 300 0.3× 305 0.7× 147 0.5× 121 0.8× 58 1.5k
Daniel Müllensiefen United Kingdom 27 2.1k 1.1× 654 0.7× 633 1.4× 355 1.2× 209 1.4× 119 2.7k
Annekathrin Schacht Germany 35 3.1k 1.6× 1.7k 1.9× 877 1.9× 201 0.7× 473 3.2× 84 3.9k
Erin E. Hannon United States 22 1.8k 0.9× 624 0.7× 342 0.7× 145 0.5× 493 3.3× 45 2.2k
Jefferson Provost United States 6 2.0k 1.0× 929 1.0× 333 0.7× 91 0.3× 986 6.7× 7 2.7k
Alex O. Holcombe Australia 27 2.0k 1.0× 628 0.7× 372 0.8× 292 1.0× 125 0.8× 104 2.7k
Daniël Schreij Netherlands 8 1.5k 0.8× 666 0.7× 375 0.8× 141 0.5× 369 2.5× 15 2.2k

Countries citing papers authored by Jason Haberman

Since Specialization
Citations

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

Fields of papers citing papers by Jason Haberman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jason Haberman

This figure shows the co-authorship network connecting the top 25 collaborators of Jason Haberman. A scholar is included among the top collaborators of Jason Haberman 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 Jason Haberman. Jason Haberman 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.
Won, Bo-Yeong, Jason Haberman, Eliza Bliss‐Moreau, & Joy J. Geng. (2020). Flexible target templates improve visual search accuracy for faces depicting emotion. Attention Perception & Psychophysics. 82(6). 2909–2923. 6 indexed citations
2.
Haberman, Jason, et al.. (2020). Ensemble size judgments account for size constancy. Attention Perception & Psychophysics. 83(3). 925–933. 4 indexed citations
3.
Haberman, Jason, et al.. (2020). Emotional judgments of scenes are influenced by unintentional averaging. Cognitive Research Principles and Implications. 5(1). 6 indexed citations
4.
Haberman, Jason, et al.. (2019). The Frozen Effect: Objects in motion are more aesthetically appealing than objects frozen in time. PLoS ONE. 14(5). e0215813–e0215813. 1 indexed citations
5.
Haberman, Jason, et al.. (2019). Precise Ensemble Face Representation Given Incomplete Visual Input. i-Perception. 10(1). 980090566–980090566. 9 indexed citations
6.
Haberman, Jason, et al.. (2018). Correcting “confusability regions” in face morphs. Behavior Research Methods. 50(4). 1686–1693. 4 indexed citations
7.
Haberman, Jason, Timothy F. Brady, & George A. Alvarez. (2015). Individual differences in ensemble perception reveal multiple, independent levels of ensemble representation.. Journal of Experimental Psychology General. 144(2). 432–446. 107 indexed citations
8.
Haberman, Jason, et al.. (2015). Mixed emotions: Sensitivity to facial variance in a crowd of faces. Journal of Vision. 15(4). 16–16. 54 indexed citations
9.
Caruso, Alessandra, et al.. (2014). Butalbital and Pediatric Headache: Stay off the Downward Path. Headache The Journal of Head and Face Pain. 55(2). 327–330. 3 indexed citations
10.
Post, Robert B., et al.. (2012). The Frozen Face Effect: Why Static Photographs May Not Do You Justice. Frontiers in Psychology. 3. 22–22. 19 indexed citations
11.
Janata, Petr, et al.. (2011). Sensorimotor coupling in music and the psychology of the groove.. Journal of Experimental Psychology General. 141(1). 54–75. 348 indexed citations
12.
Haberman, Jason & David Whitney. (2011). Efficient summary statistical representation when change localization fails. Psychonomic Bulletin & Review. 18(5). 855–859. 69 indexed citations
13.
Haberman, Jason & David Whitney. (2010). The visual system discounts emotional deviants when extracting average expression. Attention Perception & Psychophysics. 72(7). 1825–1838. 124 indexed citations
14.
Sanders, Kate, Jason Haberman, & David Whitney. (2010). Mean representation beyond a shadow of a doubt: Summary statistical representation of shadows and lighting direction. Journal of Vision. 8(6). 334–334. 2 indexed citations
15.
Puri, Amrita, Saul S. Morris, Jason Haberman, Jason Fischer, & David Whitney. (2010). Effects of high-level ensemble representations on visual search. Journal of Vision. 10(7). 1305–1305. 1 indexed citations
16.
Haberman, Jason, et al.. (2009). Averaging facial expression over time. Journal of Vision. 9(11). 1–1. 153 indexed citations
17.
Haberman, Jason & David Whitney. (2009). Seeing the mean: Ensemble coding for sets of faces.. Journal of Experimental Psychology Human Perception & Performance. 35(3). 718–734. 271 indexed citations
18.
Haberman, Jason & David Whitney. (2007). Rapid extraction of mean emotion and gender from sets of faces. Current Biology. 17(17). R751–R753. 328 indexed citations
19.
Virtue, Sandra, et al.. (2006). Neural activity of inferences during story comprehension. Brain Research. 1084(1). 104–114. 107 indexed citations
20.
Beeman, Mark, Edward M. Bowden, Jason Haberman, et al.. (2004). Neural Activity When People Solve Verbal Problems with Insight. PLoS Biology. 2(4). e97–e97. 677 indexed citations breakdown →

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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