Daniel Bleichenbacher

27 total papers · 1.2k total citations
8 papers, 51 citations indexed

About

Daniel Bleichenbacher is a scholar working on Artificial Intelligence, Computer Networks and Communications and Neurology. According to data from OpenAlex, Daniel Bleichenbacher has authored 8 papers receiving a total of 51 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 2 papers in Computer Networks and Communications and 2 papers in Neurology. Recurrent topics in Daniel Bleichenbacher's work include Botulinum Toxin and Related Neurological Disorders (2 papers), Coding theory and cryptography (2 papers) and Stroke Rehabilitation and Recovery (2 papers). Daniel Bleichenbacher is often cited by papers focused on Botulinum Toxin and Related Neurological Disorders (2 papers), Coding theory and cryptography (2 papers) and Stroke Rehabilitation and Recovery (2 papers). Daniel Bleichenbacher collaborates with scholars based in United States, Switzerland and Israel. Daniel Bleichenbacher's co-authors include Aggelos Kiayias, Moti Yung, S. V. Adamovich, Eran Gabber, Alain Mayer, Yossi Matias, Phillip B. Gibbons, Robert Riener, Mathini Sellathurai and Verena Klamroth-Marganska and has published in prestigious journals such as Theoretical Computer Science, Research Portal (Queen's University Belfast) and Repository for Publications and Research Data (ETH Zurich).

In The Last Decade

Daniel Bleichenbacher

7 papers receiving 43 citations

Author Peers

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

Author						Papers	Cites
Daniel Bleichenbacher	32	11	10	10	10	8	51
Meltem Sönmez Turan	41 1.3×		10 1.0×	9 0.9×	15 1.5×	10	54
Edward Knapp	39 1.2×		4 0.4×	16 1.6×	9 0.9×	6	79
Thomas Prest	37 1.2×		11 1.1×	18 1.8×	3 0.3×	6	43
Isamu Teranishi	40 1.3×		14 1.4×	19 1.9×	5 0.5×	12	49
Seongtaek Chee	44 1.4×		4 0.4×	8 0.8×	24 2.4×	13	56
Boyang Li	34 1.1×		7 0.7×	14 1.4×	6 0.6×	10	56
Miguel E. Andrés	41 1.3×		14 1.4×	6 0.6×	4 0.4×	5	48
Björn Tackmann	34 1.1×		17 1.7×	26 2.6×	6 0.6×	7	45
Matthew Wicker	61 1.9×		5 0.5×	7 0.7×	7 0.7×	8	85
Ngoc Khanh Nguyen	26 0.8×		4 0.4×	9 0.9×	4 0.4×	5	65

Countries citing papers authored by Daniel Bleichenbacher

Since Specialization

Citations

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

Fields of papers citing papers by Daniel Bleichenbacher

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Bleichenbacher

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Bleichenbacher. A scholar is included among the top collaborators of Daniel Bleichenbacher 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 Daniel Bleichenbacher. Daniel Bleichenbacher 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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