Travis Desell

1.2k citations
60 papers · 549 · h-index 14

Impact in

Papers in

Travis Desell

55 papers receiving 528 citations

Peers

Travis Desell
Comparison fields: 5 of 93
  • Hardware and Architecture 90
  • Computer Networks and Communications 188
  • Ecological Modeling 32
  • Artificial Intelligence 157
  • Information Systems 109
Replace Philip M. Papadopoulos with:
Philip M. Papadopoulos United States
Mo Zhou China
Luis Valencia–Cabrera Spain
Hai Liu Hong Kong
Ching-Kuang Shene United States
Qian Ge United States
Beatriz Prieto Spain
Olivier Buffet France
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Citations per field
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Citations per year

Countries citing papers authored by Travis Desell

Since Specialization
Citations

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

Fields of papers citing papers by Travis Desell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201746
2 201641
3 200633
4 200733
5 201426
6
Load Balancing of Autonomous Actors over Dynamic Networks
200423
7 201821
8 202320
9 200720
10 201416
11 200814
12 200814
13 201013
14 201213
15 201713
16 201913
17
Towards a Middleware Framework for Dynamically Reconfigurable Scientific Computing
200512
18 201710
19 201610
20 201710

About Travis Desell

Travis Desell is a scholar working on Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition, Hardware and Architecture and Information Systems, having authored 60 papers that have together received 549 indexed citations. Recurring topics across this work include Distributed and Parallel Computing Systems (14 papers), Neural Networks and Applications (10 papers), Parallel Computing and Optimization Techniques (9 papers), Metaheuristic Optimization Algorithms Research (8 papers), Evolutionary Algorithms and Applications (7 papers), Video Surveillance and Tracking Methods (5 papers), Energy Load and Power Forecasting (5 papers) and Peer-to-Peer Network Technologies (4 papers). The work is most often cited by research in Hardware and Architecture (90 citations), Computer Networks and Communications (188 citations), Ecological Modeling (32 citations), Artificial Intelligence (157 citations) and Information Systems (109 citations). Travis Desell has collaborated with scholars based in United States, Canada and Saudi Arabia. Frequent co-authors include Carlos A. Varela, Kaoutar El Maghraoui, Bolesław K. Szymański, James Higgins, Susan N. Ellis‐Felege, Ali Ashtari, Sima Noghanian, Fatima El Jamiy, Malik Magdon‐Ismail and Marcos Zampieri. Their work appears in journals such as Applied Soft Computing, Scientific Reports, The International Journal of High Performance Computing Applications, Journal of Computational Science and The Astrophysical Journal.

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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