David Halpern

2.7k citations
67 papers · 2.2k · h-index 25

Impact in

Papers in

David Halpern

66 papers receiving 2.1k citations

Peers

David Halpern
Comparison fields: 5 of 119
  • Computational Mechanics 1.0k
  • Fluid Flow and Transfer Processes 230
  • Cognitive Neuroscience 439
  • Surfaces, Coatings and Films 128
  • Pulmonary and Respiratory Medicine 552
Replace Masahiro Takei with:
Masahiro Takei Japan
Peter M. Pinsky United States
Jeffrey J. Heys United States
Hiroharu Kato Japan
Francesco Panerai United States
Julien Bert France
Wim Verkruysse United States
Mohsen Jadidi Iran
C.A. Grimbergen Netherlands
Gilwon Yoon South Korea
David Halpern relative to Masahiro Takei Japan Masahiro Takei's profile →
Citations per field
00.5×10×20×25.6×
Masahiro Takei · 1×
Citations per year

Countries citing papers authored by David Halpern

Since Specialization
Citations

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

Fields of papers citing papers by David Halpern

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside David Halpern, 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 David Halpern Line = papers co-authored together David Halpern links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 67 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1998156
2 1988148
3 1993139
4 1992113
5 1996104
6 198689
7 200286
8 199381
9 200381
10 199481
11 199973
12 199266
13 199157
14 199551
15 200251
16 199551
17 200847
18 200341
19 199435
20 200231

About David Halpern

David Halpern is a scholar working on Computational Mechanics, Pulmonary and Respiratory Medicine, Cognitive Neuroscience, Fluid Flow and Transfer Processes and Biomedical Engineering, having authored 67 papers that have together received 2.2k indexed citations. Recurring topics across this work include Fluid Dynamics and Thin Films (23 papers), Inhalation and Respiratory Drug Delivery (15 papers), Rheology and Fluid Dynamics Studies (12 papers), Fluid Dynamics and Heat Transfer (11 papers), Visual perception and processing mechanisms (10 papers), Lattice Boltzmann Simulation Studies (10 papers), Ophthalmology and Visual Impairment Studies (7 papers) and Fluid Dynamics and Mixing (7 papers). The work is most often cited by research in Computational Mechanics (1.0k citations), Fluid Flow and Transfer Processes (230 citations), Cognitive Neuroscience (439 citations), Surfaces, Coatings and Films (128 citations) and Pulmonary and Respiratory Medicine (552 citations). David Halpern has collaborated with scholars based in United States, United Kingdom and Taiwan. Frequent co-authors include James B. Grotberg, Oliver E. Jensen, Randolph Blake, Donald P. Gaver, Alexander Frenkel, J. B. Grotberg, Hideki Fujioka, James Hillenbrand, Timothy W. Secomb and Aries Arditi. Their work appears in journals such as Journal of Fluid Mechanics, Journal of Biomechanical Engineering, Physics of Fluids, Journal of Applied Physiology and Perception.

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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