Daniel Coore

1.0k citations
18 papers · 548 · h-index 8

Impact in

Papers in

Daniel Coore

17 papers receiving 503 citations

Peers

Daniel Coore
Comparison fields: 5 of 83
  • Computer Networks and Communications 141
  • Mechanical Engineering 148
  • Computational Theory and Mathematics 61
  • Cardiology and Cardiovascular Medicine 84
  • Surgery 161
Replace Koichiro Ishibashi with:
Koichiro Ishibashi Japan
Tobore Igbe China
Xiao Sun Japan
Adam Bujnowski Poland
Steven Senger United States
Dipti D. Patil India
Richa Sharma India
P. M. Gopal United States
Michael J. Sinclair United States
Giuliano Grossi Italy
Daniel Coore relative to Koichiro Ishibashi Japan Koichiro Ishibashi's profile →
Citations per field
00.5×4.4×
Koichiro Ishibashi · 1×
Citations per year

Countries citing papers authored by Daniel Coore

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Coore

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1 2000285
2 201682
3 200565
4
Paradigms for Structure in an Amorphous Computer
199732
5 201626
6 201913
7
An Algorithm for Group Formation and Maximal Independent Set in an Amorphous Computer
199810
8 20198
9 20037
10 20145
11 20164
12 20132
13 20082
14 20152
15 20042
16 20121
17 20101
18 20131

About Daniel Coore

Daniel Coore is a scholar working on Surgery, Cardiology and Cardiovascular Medicine, Mechanical Engineering, Computer Networks and Communications and Computer Science Applications, having authored 18 papers that have together received 548 indexed citations. Recurring topics across this work include Surgical Simulation and Training (5 papers), Modular Robots and Swarm Intelligence (5 papers), Energy Efficient Wireless Sensor Networks (4 papers), Cardiac and Coronary Surgery Techniques (4 papers), Cardiac, Anesthesia and Surgical Outcomes (4 papers), Advanced Materials and Mechanics (3 papers), Teaching and Learning Programming (3 papers) and Face and Expression Recognition (2 papers). The work is most often cited by research in Computer Networks and Communications (141 citations), Mechanical Engineering (148 citations), Computational Theory and Mathematics (61 citations), Cardiology and Cardiovascular Medicine (84 citations) and Surgery (161 citations). Daniel Coore has collaborated with scholars based in Jamaica, United States and United Kingdom. Frequent co-authors include Radhika Nagpal, Ron Weiss, Don Allen, Thomas F. Knight, Erik Rauch, Gerald Jay Sussman, Harold Abelson, Chris Hanson, George E. Homsy and Paul S. Ramphal. Their work appears in journals such as The Annals of Thoracic Surgery, Communications of the ACM, European Journal of Cardio-Thoracic Surgery, Repository@Nottingham (University of Nottingham) and DSpace@MIT (Massachusetts Institute of Technology).

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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