Keisha Novak

21 total papers · 448 total citations
9 papers, 297 citations indexed

About

Keisha Novak is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Keisha Novak has authored 9 papers receiving a total of 297 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Cognitive Neuroscience, 4 papers in Experimental and Cognitive Psychology and 1 paper in Cellular and Molecular Neuroscience. Recurrent topics in Keisha Novak's work include Neural and Behavioral Psychology Studies (6 papers), Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes (3 papers) and Mental Health Research Topics (2 papers). Keisha Novak is often cited by papers focused on Neural and Behavioral Psychology Studies (6 papers), Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes (3 papers) and Mental Health Research Topics (2 papers). Keisha Novak collaborates with scholars based in United States. Keisha Novak's co-authors include Dan Foti, Donald R. Lynam, Belel Ait Oumeziane, Sébastien Hélie, David Rollock, Kaylin E. Hill, Douglas B. Samuel, Greg Perlman, Aprajita Mohanty and Takakuni Suzuki and has published in prestigious journals such as SHILAP Revista de lepidopterología, Annals of the New York Academy of Sciences and Journal of Abnormal Psychology.

In The Last Decade

Keisha Novak

8 papers receiving 297 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Keisha Novak	237	104	57	42	39	9	297
M. Meredith Gillis	197 0.8×	83 0.8×	82 1.4×	33 0.8×	42 1.1×	8	317
A. Hunter Threadgill	236 1.0×	90 0.9×	26 0.5×	26 0.6×	45 1.2×	17	307
Jessica I. Määttä	195 0.8×	78 0.8×	35 0.6×	64 1.5×	24 0.6×	11	312
Tanja Müller	226 1.0×	68 0.7×	41 0.7×	35 0.8×	12 0.3×	12	356
Belel Ait Oumeziane	177 0.7×	135 1.3×	35 0.6×	19 0.5×	67 1.7×	10	262
Davide Francesco Stramaccia	244 1.0×	117 1.1×	42 0.7×	19 0.5×	40 1.0×	9	332
Kainan S. Wang	158 0.7×	79 0.8×	24 0.4×	26 0.6×	31 0.8×	12	236
Kristine M. McGlennen	200 0.8×	95 0.9×	22 0.4×	31 0.7×	53 1.4×	6	322
Paula Lopez-Gamundi	107 0.5×	68 0.7×	29 0.5×	52 1.2×	45 1.2×	12	237
Ziya V. Dikman	190 0.8×	117 1.1×	83 1.5×	13 0.3×	63 1.6×	8	329

Countries citing papers authored by Keisha Novak

Since Specialization

Citations

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

Fields of papers citing papers by Keisha Novak

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Keisha Novak

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

All Works

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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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