Kevin Weekly

817 citations
15 papers · 606 · h-index 9

Impact in

Papers in

Kevin Weekly

15 papers receiving 581 citations

Peers

Kevin Weekly
Comparison fields: 5 of 67
  • Computer Networks and Communications 316
  • Building and Construction 107
  • Environmental Engineering 89
  • Signal Processing 49
  • Computer Vision and Pattern Recognition 90
Replace Xuerong Cui with:
Xuerong Cui China
Raúl Aquino-Santos Mexico
Nipun Batra India
Sujoy Saha India
Kishore Kulat India
Adnan Saeed China
Jiangfeng Xian China
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Junyi Zhou United States
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Citations per field
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Citations per year

Countries citing papers authored by Kevin Weekly

Since Specialization
Citations

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

Fields of papers citing papers by Kevin Weekly

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Kevin Weekly, 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 Kevin Weekly Line = papers co-authored together Kevin Weekly links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 2012225
2 2016109
3 201278
4 201338
5 201536
6 201433
7 201827
8 201420
9 201413
10 20158
11 20127
12 20156
13 20142
14 20112
15
Applied Estimation of Mobile Environments
20142

About Kevin Weekly

Kevin Weekly is a scholar working on Computer Vision and Pattern Recognition, Environmental Engineering, Building and Construction, Computer Networks and Communications and Ocean Engineering, having authored 15 papers that have together received 606 indexed citations. Recurring topics across this work include Building Energy and Comfort Optimization (4 papers), Indoor and Outdoor Localization Technologies (3 papers), Air Quality Monitoring and Forecasting (3 papers), Flood Risk Assessment and Management (2 papers), Context-Aware Activity Recognition Systems (2 papers), Underwater Vehicles and Communication Systems (2 papers), Heart Rate Variability and Autonomic Control (2 papers) and Robotic Path Planning Algorithms (2 papers). The work is most often cited by research in Computer Networks and Communications (316 citations), Building and Construction (107 citations), Environmental Engineering (89 citations), Signal Processing (49 citations) and Computer Vision and Pattern Recognition (90 citations). Kevin Weekly has collaborated with scholars based in United States, China and Greece. Frequent co-authors include Kristofer S. J. Pister, Alexandre M. Bayen, Ming Jin, Costas J. Spanos, Nikolaos Bekiaris‐Liberis, Branko Kerkez, Thomas Watteyne, Steven D. Glaser, Xavier Vilajosana and Qin Wang. Their work appears in journals such as Transactions on Emerging Telecommunications Technologies, IEEE Transactions on Control Systems Technology, Sensors, Journal of Field Robotics and Water Resources Research.

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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