Michael Siebers
- Co-authors
- Ute SchmidJohannes FußSarah V. BiedermannBeat LutzFernando Martínez‐PlumedLaura BîndilăJosé Hernández‐OralloDavid L. Dowe
- Topics
- AI-based Problem Solving and Planning (4 papers)Explainable Artificial Intelligence (XAI) (3 papers)Face and Expression Recognition (3 papers)
- Partner nations
- GermanyUnited StatesAustralia
In The Last Decade
Michael Siebers
21 papers receiving 186 citations
Peers
Comparison fields: 5 of 84
- Artificial Intelligence 48
- Health 30
- Pharmacology 29
- Physiology 29
- Clinical Psychology 22
Countries citing papers authored by Michael Siebers
This map shows the geographic impact of Michael Siebers'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 Michael Siebers with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Siebers more than expected).
Fields of papers citing papers by Michael Siebers
This network shows the impact of papers produced by Michael Siebers. 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 Michael Siebers. The network helps show where Michael Siebers may publish in the future.
Co-authorship network of co-authors of Michael Siebers
This figure shows the co-authorship network connecting the top 25 collaborators of Michael Siebers. A scholar is included among the top collaborators of Michael Siebers 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 Michael Siebers. Michael Siebers is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 20 | |
| 2 | 38 | |
| 3 | 7 | |
| 4 | 3 | |
| 5 | Forgetting in future work systems: System characteristics and user-related psychological consequences on emotion, cognition, and behaviors | 1 |
| 6 | Computer models solving intelligence test problems: progress and implications | 0 |
| 7 | Intentionales Vergessen im Arbeitsalltag : Eine Critical Incident Untersuchung | 1 |
| 8 | 4 | |
| 9 | 37 | |
| 10 | 4 | |
| 11 | Analogical Problem Solving: Insights from Verbal Reports | 3 |
| 12 | Applying Grammar Inference To Identify Generalized Patterns of Facial Expressions of Pain | 2 |
| 13 | 1 | |
| 14 | 1 | |
| 15 | 14 | |
| 16 | 8 | |
| 17 | 5 | |
| 18 | Planning in advance for critical care. | 1 |
| 19 | 1 | |
| 20 | 27 |
About Michael Siebers
Michael Siebers is a scholar working on Experimental and Cognitive Psychology, Information Systems and Management and Computer Science Applications, having authored 25 papers that have together received 194 indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (4 papers), Explainable Artificial Intelligence (XAI) (3 papers) and Face and Expression Recognition (3 papers). The work is most often cited by research in Health (30 citations), Health Informatics (3 citations) and Applied Psychology (10 citations). Michael Siebers has collaborated with scholars based in Germany, United States and Australia. Frequent co-authors include Ute Schmid, Johannes Fuß, Sarah V. Biedermann, Beat Lutz, Fernando Martínez‐Plumed, Laura Bîndilă, José Hernández‐Orallo, David L. Dowe, Cornelia Niessen and Noelle K. LoConte. Their work appears in journals such as Journal of the American Geriatrics Society, Information Sciences and Artificial Intelligence.
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.