Kevin M. Smith

11 papers receiving 497 citations

Hit Papers

Forecasting energy consumption of multi-family residentia...20142026201820222014100200300400

Peers

Kevin M. Smith
Comparison fields: 5 of 72
  • Electrical and Electronic Engineering 330
  • Building and Construction 295
  • Environmental Engineering 120
  • Renewable Energy, Sustainability and the Environment 87
  • Artificial Intelligence 72
Replace Ngoc-Son Truong with:
Ngoc-Son Truong Vietnam
Éric Blanco France
Jason Runge Canada
Alberto Hernandez Neto Brazil
Llorenç Burgas Spain
Mehdi Pazhoohesh United Kingdom
Pandarasamy Arjunan India
Radiša Jovanović Serbia
Razak Olu-Ajayi United Kingdom
Ismail Sulaimon United Kingdom
Kevin M. Smith relative to Ngoc-Son Truong Vietnam Ngoc-Son Truong's profile →
Citations per field
00.5×10×15.3×
Ngoc-Son Truong · 1×
Citations per year

Countries citing papers authored by Kevin M. Smith

Since Specialization
Citations

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

Fields of papers citing papers by Kevin M. Smith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kevin M. Smith

This figure shows the co-authorship network connecting the top 25 collaborators of Kevin M. Smith. A scholar is included among the top collaborators of Kevin M. Smith based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kevin M. Smith. Kevin M. Smith is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
#WorkIndexed citations
1 0
2 1
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4 0
5 6
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7 2
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10
The Sonification and Learning of Human Motion
2
11
Forecasting energy consumption of multi-family residential buildings using support vector regression: Investigating the impact of temporal and spatial monitoring granularity on performance accuracybreakdown →
479
12
An open-source wireless sensor stack: from Arduino to SDI-12 to Water One Flow
2
13 3
14 1

About Kevin M. Smith

Kevin M. Smith is a scholar working on Statistics, Probability and Uncertainty, Management Science and Operations Research and Geometry and Topology, having authored 14 papers that have together received 512 indexed citations. Recurring topics across this work include Risk and Portfolio Optimization (3 papers), Geometry and complex manifolds (2 papers) and Water resources management and optimization (2 papers). The work is most often cited by research in Building and Construction (295 citations), Environmental Engineering (120 citations) and Electrical and Electronic Engineering (330 citations). Kevin M. Smith has collaborated with scholars based in United States and Canada. Frequent co-authors include Patricia J. Culligan, John E. Taylor, Rishee K. Jain, Ramón L. Sandin, Claire J. Tomlin, David L. Freyberg, David W. Seldin, Paul J. Cannon, Tamás Darvas and Lynne L. Johnson. Their work appears in journals such as IEEE Transactions on Automatic Control, Applied Energy and IEEE Transactions on Control Systems 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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