Mariah Schrum

416 total citations
15 papers, 235 citations indexed

About

Mariah Schrum is a scholar working on Artificial Intelligence, Social Psychology and Control and Systems Engineering. According to data from OpenAlex, Mariah Schrum has authored 15 papers receiving a total of 235 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 5 papers in Social Psychology and 3 papers in Control and Systems Engineering. Recurrent topics in Mariah Schrum's work include Social Robot Interaction and HRI (4 papers), Behavioral Health and Interventions (3 papers) and Explainable Artificial Intelligence (XAI) (3 papers). Mariah Schrum is often cited by papers focused on Social Robot Interaction and HRI (4 papers), Behavioral Health and Interventions (3 papers) and Explainable Artificial Intelligence (XAI) (3 papers). Mariah Schrum collaborates with scholars based in United States, Singapore and Germany. Mariah Schrum's co-authors include Matthew Gombolay, Michael Johnson, Andrew Silva, Nakul Gopalan, Ayanna M. Howard, Chung Hyuk Park, Andrew Best, Sonia Chernova, S. Tim Yoon and Pradyumna Tambwekar and has published in prestigious journals such as IEEE Transactions on Robotics, International Journal of Human-Computer Interaction and World Neurosurgery.

In The Last Decade

Mariah Schrum

15 papers receiving 226 citations

Peers

Mariah Schrum
Benedikt Leichtmann Germany
Nathan L. Tenhundfeld United States
Alessandra Rossi Italy
Shanee Honig Israel
Serena Booth United States
Robert H. Wortham United Kingdom
Alexander Mois Aroyo Italy
Scott Ososky United States
Jinchao Lin United States
Ana Pinto Portugal
Benedikt Leichtmann Germany
Mariah Schrum
Citations per year, relative to Mariah Schrum Mariah Schrum (= 1×) peers Benedikt Leichtmann

Countries citing papers authored by Mariah Schrum

Since Specialization
Citations

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

Fields of papers citing papers by Mariah Schrum

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mariah Schrum

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

All Works

15 of 15 papers shown
1.
Silva, Andrew, Pradyumna Tambwekar, Mariah Schrum, & Matthew Gombolay. (2024). Towards Balancing Preference and Performance through Adaptive Personalized Explainability. ArXiv.org. 658–668. 5 indexed citations
2.
Schrum, Mariah, et al.. (2024). MAVERIC: A Data-Driven Approach to Personalized Autonomous Driving. IEEE Transactions on Robotics. 40. 1952–1965. 15 indexed citations
3.
Gombolay, Grace, et al.. (2024). Effects of explainable artificial intelligence in neurology decision support. Annals of Clinical and Translational Neurology. 11(5). 1224–1235. 6 indexed citations
4.
5.
Schrum, Mariah, et al.. (2023). Impacts of Robot Learning on User Attitude and Behavior. 534–543. 5 indexed citations
6.
Schrum, Mariah, et al.. (2022). Improving Surgical Triage in Spine Clinic: Predicting Likelihood of Surgery Using Machine Learning. World Neurosurgery. 163. e192–e198. 17 indexed citations
7.
Schrum, Mariah, et al.. (2022). Concerning Trends in Likert Scale Usage in Human-robot Interaction: Towards Improving Best Practices. ACM Transactions on Human-Robot Interaction. 12(3). 1–32. 18 indexed citations
8.
Schrum, Mariah, et al.. (2022). Personalized Meta-Learning for Domain Agnostic Learning from Demonstration. 2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI). 1179–1181. 2 indexed citations
9.
Silva, Andrew, et al.. (2022). Explainable Artificial Intelligence: Evaluating the Objective and Subjective Impacts of xAI on Human-Agent Interaction. International Journal of Human-Computer Interaction. 39(7). 1390–1404. 50 indexed citations
10.
Schrum, Mariah, et al.. (2022). MIND MELD: Personalized Meta-Learning for Robot-Centric Imitation Learning. 2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI). 157–165. 16 indexed citations
11.
Schrum, Mariah, et al.. (2021). Effects of Social Factors and Team Dynamics on Adoption of Collaborative Robot Autonomy. 149–157. 7 indexed citations
12.
Vagdargi, Prasad, Mariah Schrum, Sumana Chakravarty, et al.. (2020). A Mosquito Pick-and-Place System for PfSPZ-based Malaria Vaccine Production. arXiv (Cornell University). 6 indexed citations
13.
Schrum, Mariah, et al.. (2020). Four Years in Review. 43–52. 46 indexed citations
14.
15.
Schrum, Mariah, Chung Hyuk Park, & Ayanna M. Howard. (2019). Humanoid Therapy Robot for Encouraging Exercise in Dementia Patients. 564–565. 19 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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