Mariah Schrum
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
Papers in
-
- Reinforcement Learning in Robotics 3
- Explainable Artificial Intelligence (XAI) 3
- Domain Adaptation and Few-Shot Learning 2
-
- Social Robot Interaction and HRI 4
- Human-Automation Interaction and Safety 2
- Co-authors
- Matthew Gombolay (13 shared papers)Michael Johnson (3 shared papers)Andrew Silva (3 shared papers)Nakul Gopalan (3 shared papers)Ayanna M. Howard (2 shared papers)Chung Hyuk Park (1 shared paper)Andrew Best (1 shared paper)Sonia Chernova (1 shared paper)
- Journals
- World Neurosurgery (1 paper)International Journal of Human-Computer Interaction (1 paper)IEEE Transactions on Robotics (1 paper)Annals of Clinical and Translational Neurology (1 paper)ACM Transactions on Human-Robot Interaction (1 paper)
- Partner nations
- United StatesSingaporeGermany
In The Last Decade
Mariah Schrum
15 papers receiving 226 citations
Peers
Comparison fields: 5 of 75
- Health Informatics 19
- Human-Computer Interaction 24
- Social Psychology 88
- Safety Research 32
- Artificial Intelligence 97
Countries citing papers authored by Mariah Schrum
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
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-authors
The 19 scholars most cited alongside Mariah Schrum, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 50 | |
| 2 | 2020 | 46 | |
| 3 | 2019 | 19 | |
| 4 | 2019 | 19 | |
| 5 | 2022 | 18 | |
| 6 | 2022 | 17 | |
| 7 | 2022 | 16 | |
| 8 | 2024 | 15 | |
| 9 | 2021 | 7 | |
| 10 | 2020 | 6 | |
| 11 | 2024 | 6 | |
| 12 | 2024 | 5 | |
| 13 | 2023 | 5 | |
| 14 | 2023 | 4 | |
| 15 | 2022 | 2 |
About Mariah Schrum
Mariah Schrum is a scholar working on Artificial Intelligence, Social Psychology, Control and Systems Engineering, Safety Research and Applied Psychology, having authored 15 papers that have together received 235 indexed citations. Recurring topics across this work include Social Robot Interaction and HRI (4 papers), Ethics and Social Impacts of AI (3 papers), Behavioral Health and Interventions (3 papers), Reinforcement Learning in Robotics (3 papers), Explainable Artificial Intelligence (XAI) (3 papers), Domain Adaptation and Few-Shot Learning (2 papers), Robot Manipulation and Learning (2 papers) and Human-Automation Interaction and Safety (2 papers). The work is most often cited by research in Health Informatics (19 citations), Human-Computer Interaction (24 citations), Social Psychology (88 citations), Safety Research (32 citations) and Artificial Intelligence (97 citations). Mariah Schrum has collaborated with scholars based in United States, Singapore and Germany. Frequent 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. Their work appears in journals such as World Neurosurgery, International Journal of Human-Computer Interaction, IEEE Transactions on Robotics, Annals of Clinical and Translational Neurology and ACM Transactions on Human-Robot Interaction.
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.