Eric V. Strobl
Impact in
- Statistics and Probability top 10%
- Statistical Methods and Inference
Papers in
-
- Machine Learning in Healthcare 4
- Bayesian Modeling and Causal Inference 2
- Explainable Artificial Intelligence (XAI) 1
-
- Statistical Methods and Inference 3
- Co-authors
- Thomas A. Lasko (4 shared papers)Shyam Visweswaran (2 shared papers)Toshihiro Okubo (1 shared paper)Matt Cole (1 shared paper)Robert Elliott (1 shared paper)Luisito Bertinelli (1 shared paper)Peter Spirtes (1 shared paper)Bruce L. Miller (2 shared papers)
- Journals
- Biological Psychiatry (1 paper)Early Intervention in Psychiatry (1 paper)Current Alzheimer Research (1 paper)Journal of Economic Geography (1 paper)World Development (1 paper)
- Partner nations
- United StatesSwitzerlandUnited Kingdom
In The Last Decade
Eric V. Strobl
14 papers receiving 260 citations
Peers
Comparison fields: 5 of 90
- Statistics and Probability 26
- Health Informatics 4
- Developmental Neuroscience 10
- Artificial Intelligence 83
- Psychiatry and Mental health 31
Countries citing papers authored by Eric V. Strobl
This map shows the geographic impact of Eric V. Strobl'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 Eric V. Strobl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric V. Strobl more than expected).
Fields of papers citing papers by Eric V. Strobl
This network shows the impact of papers produced by Eric V. Strobl. 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 Eric V. Strobl. The network helps show where Eric V. Strobl may publish in the future.
Co-authors
The 23 scholars most cited alongside Eric V. Strobl, 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 | 2019 | 88 | |
| 2 | 2015 | 33 | |
| 3 | 2017 | 33 | |
| 4 | 2023 | 20 | |
| 5 | 2012 | 19 | |
| 6 | 2012 | 19 | |
| 7 | 2018 | 18 | |
| 8 | 2023 | 8 | |
| 9 | 2022 | 8 | |
| 10 | 2024 | 7 | |
| 11 | 2024 | 4 | |
| 12 | 2024 | 3 | |
| 13 | 2024 | 2 | |
| 14 | 2025 | 1 |
About Eric V. Strobl
Eric V. Strobl is a scholar working on Artificial Intelligence, Statistics and Probability, Genetics, Economics and Econometrics and Pharmacology, having authored 14 papers that have together received 263 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (4 papers), Statistical Methods and Inference (3 papers), Bayesian Modeling and Causal Inference (2 papers), Genetic Associations and Epidemiology (2 papers), Explainable Artificial Intelligence (XAI) (1 paper), Alzheimer's disease research and treatments (1 paper), Housing Market and Economics (1 paper) and Tropical and Extratropical Cyclones Research (1 paper). The work is most often cited by research in Statistics and Probability (26 citations), Health Informatics (4 citations), Developmental Neuroscience (10 citations), Artificial Intelligence (83 citations) and Psychiatry and Mental health (31 citations). Eric V. Strobl has collaborated with scholars based in United States, Switzerland and United Kingdom. Frequent co-authors include Thomas A. Lasko, Shyam Visweswaran, Toshihiro Okubo, Matt Cole, Robert Elliott, Luisito Bertinelli, Peter Spirtes, Bruce L. Miller, Shaun M. Eack and Josh Woolley. Their work appears in journals such as Biological Psychiatry, Early Intervention in Psychiatry, Current Alzheimer Research, Journal of Economic Geography and World Development.
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.