Jasmin D. Haslbauer

38 total papers · 2.1k total citations
24 papers, 1.3k citations indexed

About

Jasmin D. Haslbauer is a scholar working on Infectious Diseases, Neurology and Oncology. According to data from OpenAlex, Jasmin D. Haslbauer has authored 24 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Infectious Diseases, 10 papers in Neurology and 7 papers in Oncology. Recurrent topics in Jasmin D. Haslbauer's work include COVID-19 Clinical Research Studies (16 papers), Long-Term Effects of COVID-19 (9 papers) and SARS-CoV-2 and COVID-19 Research (8 papers). Jasmin D. Haslbauer is often cited by papers focused on COVID-19 Clinical Research Studies (16 papers), Long-Term Effects of COVID-19 (9 papers) and SARS-CoV-2 and COVID-19 Research (8 papers). Jasmin D. Haslbauer collaborates with scholars based in Switzerland, Austria and United States. Jasmin D. Haslbauer's co-authors include Alexandar Tzankov, Kirsten D. Mertz, Ronny Nienhold, Thomas Menter, Gieri Cathomas, Markus Tolnay, Niels Willi, Stefano Bassetti, Nikolaus Deigendesch and Jörg D. Leuppi and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Frontiers in Immunology.

In The Last Decade

Jasmin D. Haslbauer

21 papers receiving 1.2k citations

Hit Papers

Postmortem examination of... 2020 2026 2022 2024 2020 250 500 750

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Jasmin D. Haslbauer 919 492 272 170 136 24 1.3k
Roberto Rech 775 0.8× 393 0.8× 170 0.6× 285 1.7× 92 0.7× 26 1.3k
Luca Carsana 981 1.1× 481 1.0× 269 1.0× 286 1.7× 91 0.7× 23 1.6k
Ronny Nienhold 863 0.9× 525 1.1× 249 0.9× 180 1.1× 92 0.7× 19 1.8k
Zhenlu Zhang 949 1.0× 473 1.0× 330 1.2× 108 0.6× 74 0.5× 29 1.3k
Edana Stroberg 689 0.7× 392 0.8× 197 0.7× 128 0.8× 124 0.9× 13 1.1k
Huan Liu 768 0.8× 377 0.8× 266 1.0× 244 1.4× 171 1.3× 36 1.6k
Hui-xia Han 1.1k 1.2× 593 1.2× 188 0.7× 172 1.0× 205 1.5× 17 1.8k
Antonia Fitzek 808 0.9× 582 1.2× 247 0.9× 59 0.3× 225 1.7× 31 1.4k
Lan Yang 815 0.9× 432 0.9× 284 1.0× 98 0.6× 24 0.2× 22 1.3k
Jean‐François Llitjos 717 0.8× 319 0.6× 359 1.3× 108 0.6× 48 0.4× 31 1.2k

Countries citing papers authored by Jasmin D. Haslbauer

Since Specialization
Citations

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

Fields of papers citing papers by Jasmin D. Haslbauer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jasmin D. Haslbauer. 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 Jasmin D. Haslbauer. The network helps show where Jasmin D. Haslbauer may publish in the future.

Co-authorship network of co-authors of Jasmin D. Haslbauer

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

All Works

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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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