Timo Speith
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
- Safety Research top 2%
- Ethics and Social Impacts of AI
Papers in
-
- Explainable Artificial Intelligence (XAI) 13
- Adversarial Robustness in Machine Learning 6
- Machine Learning in Healthcare 2
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- Ethics and Social Impacts of AI 8
- Co-authors
- Kevin Baum (5 shared papers)Markus Langer (5 shared papers)Daniel Oster (3 shared papers)Eva Schmidt (2 shared papers)Holger Hermanns (2 shared papers)Lena Kästner (2 shared papers)Andreas Sesing-Wagenpfeil (1 shared paper)Francisco Herrera (1 shared paper)
In The Last Decade
Timo Speith
17 papers receiving 945 citations
Timo Speith's Hit Papers
Peers
Comparison fields: 5 of 113
- Health Informatics 174
- Safety Research 242
- Artificial Intelligence 608
- Information Systems and Management 61
- Management Information Systems 48
Countries citing papers authored by Timo Speith
This map shows the geographic impact of Timo Speith'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 Timo Speith with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Timo Speith more than expected).
Fields of papers citing papers by Timo Speith
This network shows the impact of papers produced by Timo Speith. 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 Timo Speith. The network helps show where Timo Speith may publish in the future.
Co-authors
The 25 scholars most cited alongside Timo Speith, 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 | What do we want from Explainable Artificial Intelligence (XAI)? – A stakeholder perspective on XAI and a conceptual model guiding interdisciplinary XAI research Hit paper breakdown → | 2021 | 336 |
| 2 | Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions Hit paper breakdown → | 2024 | 215 |
| 3 | A Review of Taxonomies of Explainable Artificial Intelligence (XAI) Methods Hit paper breakdown → | 2022 | 181 |
| 4 | 2019 | 66 | |
| 5 | 2022 | 58 | |
| 6 | 2021 | 30 | |
| 7 | 2023 | 16 | |
| 8 | 2022 | 15 | |
| 9 | 2023 | 9 | |
| 10 | 2024 | 8 | |
| 11 | 2022 | 7 | |
| 12 | 2024 | 6 | |
| 13 | 2023 | 6 | |
| 14 | From Machine Ethics To Machine Explainability and Back. | 2018 | 5 |
| 15 | 2024 | 3 | |
| 16 | 2021 | 2 | |
| 17 | 2023 | 1 |
About Timo Speith
Timo Speith is a scholar working on Artificial Intelligence, Safety Research, Information Systems, Health Informatics and Computer Networks and Communications, having authored 17 papers that have together received 964 indexed citations. Recurring topics across this work include Explainable Artificial Intelligence (XAI) (13 papers), Ethics and Social Impacts of AI (8 papers), Adversarial Robustness in Machine Learning (6 papers), Software Engineering Research (6 papers), Artificial Intelligence in Healthcare and Education (4 papers), Software System Performance and Reliability (2 papers), Machine Learning in Healthcare (2 papers) and Scientific Computing and Data Management (2 papers). The work is most often cited by research in Health Informatics (174 citations), Safety Research (242 citations), Artificial Intelligence (608 citations), Information Systems and Management (61 citations) and Management Information Systems (48 citations). Timo Speith has collaborated with scholars based in Germany, Ireland and Spain. Frequent co-authors include Kevin Baum, Markus Langer, Daniel Oster, Eva Schmidt, Holger Hermanns, Lena Kästner, Andreas Sesing-Wagenpfeil, Francisco Herrera, Johannes Schneider and Simone Stumpf. Their work appears in journals such as Ethics and Information Technology, Information Fusion, Artificial Intelligence, International Journal of Selection and Assessment and Philosophy & Technology.
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.