Chris Bryan

788 citations
38 papers · 508 · h-index 14

Impact in

Papers in

Chris Bryan

34 papers receiving 492 citations

Peers

Chris Bryan
Comparison fields: 5 of 107
  • Computer Vision and Pattern Recognition 249
  • Human-Computer Interaction 30
  • Artificial Intelligence 142
  • Information Systems and Management 29
  • Computer Science Applications 17
Replace Irfan Ullah with:
Irfan Ullah Pakistan
Souneil Park South Korea
Theresa O'Connell United States
Kostiantyn Kucher Sweden
Shunan Guo United States
Bingquan Liu China
Patrick Riehmann Germany
Ting Liu China
Мириам Реди United Kingdom
Evanthia Dimara France
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Citations per field
00.5×4.3×
Irfan Ullah · 1×
Citations per year

Countries citing papers authored by Chris Bryan

Since Specialization
Citations

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

Fields of papers citing papers by Chris Bryan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201672
2 201841
3 201936
4 201935
5 202129
6 201829
7 202227
8 201826
9 202025
10 202021
11 201717
12 202215
13 202215
14 201513
15
A Systemic Approach to Elevating Teacher Leadership.
201612
16 20209
17 20108
18
Towards a Hybrid Agent-based Model for Mosquito Borne Disease.
20148
19 20227
20 20177

About Chris Bryan

Chris Bryan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Molecular Biology, Statistical and Nonlinear Physics and Human-Computer Interaction, having authored 38 papers that have together received 508 indexed citations. Recurring topics across this work include Data Visualization and Analytics (17 papers), Complex Network Analysis Techniques (4 papers), Virtual Reality Applications and Impacts (3 papers), Data Analysis with R (3 papers), Multimedia Communication and Technology (2 papers), Privacy-Preserving Technologies in Data (2 papers), Natural Language Processing Techniques (2 papers) and Multimodal Machine Learning Applications (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (249 citations), Human-Computer Interaction (30 citations), Artificial Intelligence (142 citations), Information Systems and Management (29 citations) and Computer Science Applications (17 citations). Chris Bryan has collaborated with scholars based in United States, China and Colombia. Frequent co-authors include Kwan‐Liu Ma, Kwan-Liu Ma, Jonathan Woodring, Li Lin, Oscar F. Sánchez, Jennifer L. Freeman, Chris Yuan, Senthil Chandrasegaran, Jian Zhao and Bum Chul Kwon. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum, Environmental Pollution, Chemosphere and Professional Development in Education.

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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