Sören Mindermann
- Modeling and Simulation top 0.5%
- COVID-19 epidemiological studies 5
- Infectious Diseases top 10%
- SARS-CoV-2 and COVID-19 Research 1
- Viral Infections and Outbreaks Research 1
- Health top 10%
- Economics and Econometrics top 5%
- COVID-19 Pandemic Impacts 2
- Clinical Psychology top 10%
- COVID-19 and Mental Health 2
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- Bayesian Modeling and Causal Inference 1
- Explainable Artificial Intelligence (XAI) 1
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- Advanced Causal Inference Techniques 1
- Co-authors
- Jan BraunerMrinank SharmaGavin LeechJoshua Teperowski MonradYarin GalJan KulveitTomáš GavenčiakAlexander John Norman
- Partner nations
- United KingdomDenmarkUnited States
In The Last Decade
Sören Mindermann
9 papers receiving 815 citations
Hit Papers
Peers
Comparison fields: 5 of 100
- Modeling and Simulation 541
- Infectious Diseases 221
- Health 96
- Economics and Econometrics 243
- Clinical Psychology 165
Countries citing papers authored by Sören Mindermann
This map shows the geographic impact of Sören Mindermann'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 Sören Mindermann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sören Mindermann more than expected).
Fields of papers citing papers by Sören Mindermann
This network shows the impact of papers produced by Sören Mindermann. 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 Sören Mindermann. The network helps show where Sören Mindermann may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Sören Mindermann, 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 | 2025 | 1 | |
| 2 | 2023 | 34 | |
| 3 | 2022 | 57 | |
| 4 | 2022 | 8 | |
| 5 | 2022 | 33 | |
| 6 | 2021 | 54 | |
| 7 | Inferring the effectiveness of government interventions against COVID-19breakdown → | 2020 | 630 |
| 8 | Identifying Causal-Effect Inference Failure with Uncertainty-Aware Models | 2020 | 3 |
| 9 | 2017 | 14 |
About Sören Mindermann
Sören Mindermann is a scholar working on Modeling and Simulation, General Decision Sciences, Obstetrics and Gynecology, Statistics and Probability and Infectious Diseases, having authored 9 papers that have together received 834 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (5 papers), COVID-19 and Mental Health (2 papers), COVID-19 Pandemic Impacts (2 papers), SARS-CoV-2 and COVID-19 Research (1 paper), Bayesian Modeling and Causal Inference (1 paper), Viral Infections and Outbreaks Research (1 paper), Advanced Causal Inference Techniques (1 paper) and Explainable Artificial Intelligence (XAI) (1 paper). The work is most often cited by research in Modeling and Simulation (541 citations), Infectious Diseases (221 citations), Health (96 citations), Economics and Econometrics (243 citations) and Clinical Psychology (165 citations). Sören Mindermann has collaborated with scholars based in United Kingdom, Denmark and United States. Frequent co-authors include Jan Brauner, Mrinank Sharma, Gavin Leech, Joshua Teperowski Monrad, Yarin Gal, Jan Kulveit, Tomáš Gavenčiak, Alexander John Norman, George Altman and John Salvatier. Their work appears in journals such as PLoS Computational Biology, Science, BMJ Global Health, Scientific Data and Proceedings of the National Academy of Sciences.
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.