Jan Kulveit

1.6k total citations · 1 hit paper
5 papers, 674 citations indexed

About

Jan Kulveit is a scholar working on Modeling and Simulation, Infectious Diseases and Economics and Econometrics. According to data from OpenAlex, Jan Kulveit has authored 5 papers receiving a total of 674 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Modeling and Simulation, 2 papers in Infectious Diseases and 2 papers in Economics and Econometrics. Recurrent topics in Jan Kulveit's work include COVID-19 epidemiological studies (3 papers), COVID-19 Pandemic Impacts (2 papers) and COVID-19 and Mental Health (1 paper). Jan Kulveit is often cited by papers focused on COVID-19 epidemiological studies (3 papers), COVID-19 Pandemic Impacts (2 papers) and COVID-19 and Mental Health (1 paper). Jan Kulveit collaborates with scholars based in United Kingdom, Czechia and Australia. Jan Kulveit's co-authors include Sören Mindermann, Gavin Leech, Jan Brauner, Tomáš Gavenčiak, Joshua Teperowski Monrad, Mrinank Sharma, Alexander John Norman, Yarin Gal, George Altman and John Salvatier and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and The Journal of Chemical Physics.

In The Last Decade

Jan Kulveit

5 papers receiving 657 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Inferring the effectiveness of government interventions against COVID-19

2020 630 citations Jan Brauner, Sören Mindermann et al. Science profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Jan Kulveit United Kingdom	3	470	211	187	133	110	5	674
Alexander John Norman United Kingdom	3	453 1.0×	210 1.0×	183 1.0×	130 1.0×	108 1.0×	3	658
Gavin Leech United Kingdom	4	499 1.1×	226 1.1×	196 1.0×	142 1.1×	114 1.0×	5	728
David Johnston Australia	2	443 0.9×	204 1.0×	168 0.9×	128 1.0×	103 0.9×	3	634
Joshua Teperowski Monrad United States	9	508 1.1×	230 1.1×	229 1.2×	153 1.2×	120 1.1×	11	884
Mrinank Sharma United Kingdom	6	541 1.2×	241 1.1×	221 1.2×	165 1.2×	123 1.1×	6	816
Sören Mindermann United Kingdom	7	541 1.2×	243 1.2×	221 1.2×	165 1.2×	123 1.1×	9	834
Joel Ruihan Koo Singapore	9	459 1.0×	204 1.0×	260 1.4×	141 1.1×	91 0.8×	20	852
Wongyeong Choi South Korea	7	410 0.9×	169 0.8×	272 1.5×	91 0.7×	85 0.8×	11	672
Yiseul Lee United States	5	553 1.2×	265 1.3×	331 1.8×	105 0.8×	102 0.9×	6	804
Yuxia Liang China	7	673 1.4×	238 1.1×	378 2.0×	228 1.7×	221 2.0×	13	1.1k

Countries citing papers authored by Jan Kulveit

Since Specialization

Citations

This map shows the geographic impact of Jan Kulveit'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 Jan Kulveit with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan Kulveit more than expected).

Fields of papers citing papers by Jan Kulveit

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jan Kulveit. 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 Jan Kulveit. The network helps show where Jan Kulveit may publish in the future.

Co-authorship network of co-authors of Jan Kulveit

This figure shows the co-authorship network connecting the top 25 collaborators of Jan Kulveit. A scholar is included among the top collaborators of Jan Kulveit 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 Jan Kulveit. Jan Kulveit is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

5 of 5 papers shown

1.

Gavenčiak, Tomáš, et al.. (2025). AI–AI bias: Large language models favor communications generated by large language models. Proceedings of the National Academy of Sciences. 122(31). e2415697122–e2415697122. 2 indexed citations

2.

Altman, George, Janvi Ahuja, Joshua Teperowski Monrad, et al.. (2022). A dataset of non-pharmaceutical interventions on SARS-CoV-2 in Europe. Scientific Data. 9(1). 145–145. 8 indexed citations

3.

Gavenčiak, Tomáš, Joshua Teperowski Monrad, Gavin Leech, et al.. (2022). Seasonal variation in SARS-CoV-2 transmission in temperate climates: A Bayesian modelling study in 143 European regions. PLoS Computational Biology. 18(8). e1010435–e1010435. 33 indexed citations

4.

Brauner, Jan, Sören Mindermann, Mrinank Sharma, et al.. (2020). Inferring the effectiveness of government interventions against COVID-19. Science. 371(6531). 630 indexed citations breakdown →

5.

Kulveit, Jan, et al.. (2011). Formation of structured nanophases in halide crystals. The Journal of Chemical Physics. 134(14). 144504–144504. 1 indexed citations

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.

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