Gene Cooperman

37.5k citations
88 papers · 1.1k · h-index 16

Impact in

Papers in

Gene Cooperman

86 papers receiving 1.0k citations

Peers

Gene Cooperman
Comparison fields: 5 of 79
  • Discrete Mathematics and Combinatorics 167
  • Hardware and Architecture 257
  • Computer Networks and Communications 476
  • Software 34
  • Artificial Intelligence 284
Replace Virginia Vassilevska Williams with:
Virginia Vassilevska Williams United States
Jonathan Rosenberg United States
Gilles Zémor France
Steven Rudich United States
D.K. Ray-Chaudhuri United States
Adolfo Piperno Italy
Ömer Eğeci̇oğlu United States
Nicholas J. A. Harvey United States
Arnold Schönhage Germany
Carla D. Savage United States
Gene Cooperman relative to Virginia Vassilevska Williams United States Virginia Vassilevska Williams's profile →
Citations per field
00.5×2.6×
Virginia Vassilevska Williams · 1×
Citations per year

Countries citing papers authored by Gene Cooperman

Since Specialization
Citations

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

Fields of papers citing papers by Gene Cooperman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 88 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009182
2 1982131
3 198161
4 199149
5 199235
6 200532
7 198431
8 198431
9 199527
10
Transparent User-Level Checkpointing for the Native Posix Thread Library for Linux.
200625
11 200722
12 199121
13 201821
14 199518
15 199617
16 201616
17 199614
18 201113
19 201413
20 199712

About Gene Cooperman

Gene Cooperman is a scholar working on Computer Networks and Communications, Artificial Intelligence, Hardware and Architecture, Discrete Mathematics and Combinatorics and Electrical and Electronic Engineering, having authored 88 papers that have together received 1.1k indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (31 papers), Finite Group Theory Research (19 papers), Distributed and Parallel Computing Systems (18 papers), Distributed systems and fault tolerance (17 papers), Coding theory and cryptography (15 papers), Advanced Data Storage Technologies (13 papers), Cloud Computing and Resource Management (10 papers) and Algorithms and Data Compression (8 papers). The work is most often cited by research in Discrete Mathematics and Combinatorics (167 citations), Hardware and Architecture (257 citations), Computer Networks and Communications (476 citations), Software (34 citations) and Artificial Intelligence (284 citations). Gene Cooperman has collaborated with scholars based in United States, Mexico and France. Frequent co-authors include Kapil Arya, Jason Ansel, Herbert G. Winful, Larry Finkelstein, László Babai, Ákos Seress, Eugene M. Luks, Leonard H. Finkelstein, L. Friedman and Walter L. Bloss. Their work appears in journals such as Applied Physics Letters, Lecture notes in control and information sciences, Superlattices and Microstructures, Experimental Mathematics and Protein Science.

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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