Kevin McFall

30 papers receiving 333 citations

Peers

Kevin McFall
Comparison fields: 5 of 72
  • Statistical and Nonlinear Physics 143
  • Modeling and Simulation 40
  • Computational Mechanics 64
  • Statistics, Probability and Uncertainty 18
  • Artificial Intelligence 80
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Citations per year

Countries citing papers authored by Kevin McFall

Since Specialization
Citations

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

Fields of papers citing papers by Kevin McFall

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 23 scholars most cited alongside Kevin McFall, 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 McFall Line = papers co-authored together Kevin McFall links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009143
2 201953
3 201228
4 202020
5 201313
6 201912
7 202110
8 20199
9
LOW-COST PLATFORM FOR AUTONOMOUS GROUND VEHICLE RESEARCH
20148
10
Artificial Intelligence and Autonomous Vehicles
20157
11
An artificial neural network method: for solving boundary value problems - With arbitrary irregular boundary conditions
20087
12 20166
13
Comparison of an Introductory Engineering course with and without LEGO Mindstorms Robots
20114
14
Results of Audio-visual Winter Road Condition Sensor Prototype
20024
15 20203
16
Solving Coupled Systems of Differential Equations Using the Length Factor Artificial Neural Network Method
20103
17
Artificial Neural Network Technologies Applied to Road Condition Classification Using Acoustic Signals
20003
18 20172
19 20192
20
RESULTS OF AV WINTER ROAD CONDITION SENSOR PROTOTYPE
20022

About Kevin McFall

Kevin McFall is a scholar working on Mechanical Engineering, Civil and Structural Engineering, Control and Systems Engineering, Statistical and Nonlinear Physics and Biomedical Engineering, having authored 30 papers that have together received 350 indexed citations. Recurring topics across this work include Piezoelectric Actuators and Control (5 papers), Model Reduction and Neural Networks (5 papers), Mechatronics Education and Applications (3 papers), Iterative Learning Control Systems (3 papers), Infrastructure Maintenance and Monitoring (2 papers), Engineering Education and Pedagogy (2 papers), Smart Materials for Construction (2 papers) and Teaching and Learning Programming (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (143 citations), Modeling and Simulation (40 citations), Computational Mechanics (64 citations), Statistics, Probability and Uncertainty (18 citations) and Artificial Intelligence (80 citations). Kevin McFall has collaborated with scholars based in United States, South Korea and Hong Kong. Frequent co-authors include J. Robert Mahan, W.M. Wang, Zhi Li, Xin Chen, Hanyang Guo, Ali Vatankhah Barenji, Girish H. Subramanian, Neha Yadav, Joong Hoon Kim and Manoj Kumar. Their work appears in journals such as IEEE Transactions on Industrial Informatics, Journal of Heat Transfer, Journal of Dynamic Systems Measurement and Control, Remote Sensing and Neural Computing and Applications.

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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