Daniel Reichman

942 citations
33 papers · 393 · h-index 8

Impact in

Papers in

Daniel Reichman

29 papers receiving 379 citations

Peers

Daniel Reichman
Comparison fields: 5 of 111
  • General Decision Sciences 25
  • Computer Vision and Pattern Recognition 137
  • Statistical and Nonlinear Physics 35
  • Media Technology 24
  • Management Science and Operations Research 33
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Reichman

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Reichman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel Reichman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Reichman Line = papers co-authored together Daniel Reichman links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021115
2 2013113
3 201635
4 200834
5 201222
6 201512
7 201912
8 201812
9 20156
10 20175
11 20133
12 20182
13 20132
14 20052
15 19832
16 20162
17 20242
18 20191
19 20231
20 20121

About Daniel Reichman

Daniel Reichman is a scholar working on Computational Theory and Mathematics, Artificial Intelligence, Reproductive Medicine, Public Health, Environmental and Occupational Health and Pediatrics, Perinatology and Child Health, having authored 33 papers that have together received 393 indexed citations. Recurring topics across this work include Advanced Graph Theory Research (5 papers), Reproductive Biology and Fertility (5 papers), Complexity and Algorithms in Graphs (5 papers), Assisted Reproductive Technology and Twin Pregnancy (5 papers), Ovarian function and disorders (4 papers), Decision-Making and Behavioral Economics (3 papers), Machine Learning and Algorithms (3 papers) and Limits and Structures in Graph Theory (3 papers). The work is most often cited by research in General Decision Sciences (25 citations), Computer Vision and Pattern Recognition (137 citations), Statistical and Nonlinear Physics (35 citations), Media Technology (24 citations) and Management Science and Operations Research (33 citations). Daniel Reichman has collaborated with scholars based in United States, Israel and Canada. Frequent co-authors include Shai Avidan, Simon Korman, David Bourgin, Joshua C. Peterson, Thomas L. Griffiths, Mayank Agrawal, Daniel Heller, W. Q. Elaine Perunovic, Uriel Feige and Michael Krivelevich. Their work appears in journals such as Fertility and Sterility, Random Structures and Algorithms, SIAM Journal on Discrete Mathematics, Cognitive Science and Tetrahedron.

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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