Shane T. Mueller

4.0k total citations · 2 hit papers
80 papers, 2.1k citations indexed

About

Shane T. Mueller is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Social Psychology. According to data from OpenAlex, Shane T. Mueller has authored 80 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Artificial Intelligence, 24 papers in Cognitive Neuroscience and 16 papers in Social Psychology. Recurrent topics in Shane T. Mueller's work include Explainable Artificial Intelligence (XAI) (12 papers), Neural and Behavioral Psychology Studies (11 papers) and Human-Automation Interaction and Safety (10 papers). Shane T. Mueller is often cited by papers focused on Explainable Artificial Intelligence (XAI) (12 papers), Neural and Behavioral Psychology Studies (11 papers) and Human-Automation Interaction and Safety (10 papers). Shane T. Mueller collaborates with scholars based in United States, Poland and Colombia. Shane T. Mueller's co-authors include Brian J. Piper, Jun Zhang, Robert R. Hoffman, Christoph T. Weidemann, Gary Klein, David E. Meyer, David E. Kieras, Travis L. Seymour, Alena G. Esposito and Jordan A. Litman and has published in prestigious journals such as PLoS ONE, Journal of Experimental Psychology Learning Memory and Cognition and Frontiers in Psychology.

In The Last Decade

Shane T. Mueller

74 papers receiving 2.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

The Psychology Experiment Building Language (PEBL) and PEBL Test Battery

2013 733 citations Shane T. Mueller, Brian J. Piper profile →
Measures for explainable AI: Explanation goodness, user satisfaction, mental models, curiosity, trust, and human-AI performance

2023 89 citations Robert R. Hoffman, Shane T. Mueller et al. Frontiers in Computer Science profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shane T. Mueller United States	18	956	451	441	377	291	80	2.1k
Diego Fernández Slezak Argentina	18	745 0.8×	352 0.8×	172 0.4×	260 0.7×	227 0.8×	59	1.8k
Miguel A. Vadillo Spain	29	1.4k 1.4×	568 1.3×	647 1.5×	270 0.7×	606 2.1×	137	3.0k
Phillip Wolff United States	23	821 0.9×	1.0k 2.3×	555 1.3×	414 1.1×	533 1.8×	47	2.6k
Manuel Ninaus Germany	25	593 0.6×	333 0.7×	1.2k 2.7×	253 0.7×	168 0.6×	78	2.4k
Matthew S. Goodwin United States	33	1.9k 2.0×	458 1.0×	460 1.0×	152 0.4×	463 1.6×	103	3.2k
Daniel C. Krawczyk United States	29	1.6k 1.7×	575 1.3×	556 1.3×	169 0.4×	407 1.4×	70	3.0k
Emilia Barakova Netherlands	23	739 0.8×	159 0.4×	219 0.5×	518 1.4×	790 2.7×	140	1.9k
Pamela Ventola United States	27	2.4k 2.5×	159 0.4×	283 0.6×	441 1.2×	226 0.8×	69	3.2k
Santo Di Nuovo Italy	27	446 0.5×	171 0.4×	211 0.5×	224 0.6×	441 1.5×	166	2.0k
Maria Wolters United Kingdom	22	262 0.3×	474 1.1×	120 0.3×	681 1.8×	168 0.6×	130	1.8k

Countries citing papers authored by Shane T. Mueller

Since Specialization

Citations

This map shows the geographic impact of Shane T. Mueller'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 Shane T. Mueller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shane T. Mueller more than expected).

Fields of papers citing papers by Shane T. Mueller

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shane T. Mueller. 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 Shane T. Mueller. The network helps show where Shane T. Mueller may publish in the future.

Co-authorship network of co-authors of Shane T. Mueller

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

All Works

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20 of 20 papers shown

Xiao, Bo, et al.. (2025). Generative artificial intelligence for construction: Use cases, trends, challenges, and opportunities. Journal of Building Engineering. 112. 113802–113802.

Mueller, Shane T., et al.. (2024). Application of Cognitive Empathy Elements Into AI Chatbots: An Interview Study Exploring Patient-Physician Interaction. Journal of Cognitive Engineering and Decision Making. 19(2). 135–153. 1 indexed citations

Klein, Gary, et al.. (2023). The plausibility transition model for sensemaking. Frontiers in Psychology. 14. 1160132–1160132. 2 indexed citations

Bielecki, Maksymilian, Ernest Tyburski, Monika Mak, et al.. (2023). Executive Functions and Psychopathology Dimensions in Deficit and Non-Deficit Schizophrenia. Journal of Clinical Medicine. 12(5). 1998–1998. 5 indexed citations

Hoffman, Robert R., et al.. (2023). Evaluating machine-generated explanations: a “Scorecard” method for XAI measurement science. Frontiers in Computer Science. 5. 6 indexed citations

Hoffman, Robert R., et al.. (2023). Explainable AI: roles and stakeholders, desirements and challenges. Frontiers in Computer Science. 5. 14 indexed citations

Mueller, Shane T., et al.. (2021). Examining the effect of explanation on satisfaction and trust in AI diagnostic systems. BMC Medical Informatics and Decision Making. 21(1). 178–178. 42 indexed citations

Confalonieri, Roberto, Tarek R. Besold, Tillman Weyde, et al.. (2019). What makes a good explanation? Cognitive dimensions of explaining intelligent machines.. Digital Commons - Michigan Tech (Michigan Technological University). 25–26. 8 indexed citations

Dewey, John & Shane T. Mueller. (2019). Individual Differences in Sensitivity to Visuomotor Discrepancies. Frontiers in Psychology. 10. 144–144. 1 indexed citations

10.

Mueller, Shane T., et al.. (2015). Identifying Mental Models of Search in a Simulated Flight Task Using a Pathmapping Approach. Journal of Bioresource Management. 398. 4 indexed citations

11.

Mueller, Shane T., et al.. (2015). Adapting cultural mixture modeling for continuous measures of knowledge and memory fluency. Behavior Research Methods. 48(3). 843–856. 4 indexed citations

12.

Piper, Brian J., et al.. (2015). Reliability and validity of neurobehavioral function on the Psychology Experimental Building Language test battery in young adults. PeerJ. 3. e1460–e1460. 58 indexed citations

13.

Mueller, Shane T. & Alena G. Esposito. (2014). Computerized Testing Software for Assessing Interference Suppression in Children and Adults: The Bivalent Shape Task (BST). Journal of Open Research Software. 2(1). e3–e3. 15 indexed citations

14.

Mueller, Shane T., et al.. (2013). Examining Memory for Search Using a Simulated Aerial Search and Rescue Task. Journal of Bioresource Management. 412. 3 indexed citations

15.

Tümkaya, Selim, Filiz Karadağ, Shane T. Mueller, et al.. (2013). Situation awareness in obsessive-compulsive disorder. Psychiatry Research. 209(3). 579–588. 13 indexed citations

16.

Mueller, Shane T.. (2011). Tutorial on using the Psychology Experiment Building Language (PEBL) in the laboratory, the field, and the classroom. Cognitive Science. 33(33). 1 indexed citations

17.

Piper, Brian J., et al.. (2011). Executive function on the Psychology Experiment Building Language tests. Behavior Research Methods. 44(1). 110–123. 103 indexed citations

18.

Mueller, Shane T. & Elizabeth S. Veinott. (2008). Cultural Mixture Modeling: Identifying Cultural Consensus Using Finite Mixture Modeling. eScholarship (California Digital Library). 30(30). 1 indexed citations

19.

Mueller, Shane T. & Richard M. Shiffrin. (2007). Incorporating Connotation of Meaning into Models of Semantic Representation: An Application in Text Corpus Analysis. eScholarship (California Digital Library). 29(29). 1 indexed citations

20.

Mueller, Shane T., Travis L. Seymour, David E. Kieras, & David E. Meyer. (2003). Theoretical Implications of Articulatory Duration, Phonological Similarity, and Phonological Complexity in Verbal Working Memory.. Journal of Experimental Psychology Learning Memory and Cognition. 29(6). 1353–1380. 108 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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