Scott D. Poll

44 papers receiving 1.5k citations

Scott D. Poll's Hit Papers

Prognostics Methods for Battery Health Monitoring Using a Bayesian Framework 2008 · 709 citations
7090+6+12Years since publication200400600

Peers

Scott D. Poll
Comparison fields: 5 of 68
  • Automotive Engineering 636
  • Safety, Risk, Reliability and Quality 283
  • Control and Systems Engineering 582
  • Artificial Intelligence 125
  • Aerospace Engineering 66
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Arda Kurt United States
H. Peng United States
Nan Li China
Erik Coelingh Sweden
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Edward Balaban United States
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Countries citing papers authored by Scott D. Poll

Since Specialization
Citations

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

Fields of papers citing papers by Scott D. Poll

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Scott D. Poll. 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 Scott D. Poll. The network helps show where Scott D. Poll may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Prognostics Methods for Battery Health Monitoring Using a Bayesian Framework
Hit paper breakdown →
2008709
2 2007164
3 201795
4 201075
5 201075
6
Advanced Diagnostics and Prognostics Testbed
200774
7 200942
8 200740
9 200535
10 201631
11
First International Diagnosis Competition - DXC'09
200928
12 200924
13 200722
14 200820
15
Diagnostic Technology Evaluation Report For On-Board Crew Launch Vehicle
200616
16
A Bayesian Framework for Remaining Useful Life Estimation
200714
17 201614
18
Towards a Framework for Evaluating and Comparing Diagnosis Algorithms
200913
19 201212
20 201511

About Scott D. Poll

Scott D. Poll is a scholar working on Control and Systems Engineering, Automotive Engineering, Building and Construction, Artificial Intelligence and Aerospace Engineering, having authored 45 papers that have together received 1.6k indexed citations. Recurring topics across this work include Engineering and Test Systems (22 papers), Fault Detection and Control Systems (16 papers), Machine Fault Diagnosis Techniques (5 papers), Air Traffic Management and Optimization (4 papers), Advanced Battery Technologies Research (4 papers), Bayesian Modeling and Causal Inference (4 papers), Building Energy and Comfort Optimization (4 papers) and Reliability and Maintenance Optimization (2 papers). The work is most often cited by research in Automotive Engineering (636 citations), Safety, Risk, Reliability and Quality (283 citations), Control and Systems Engineering (582 citations), Artificial Intelligence (125 citations) and Aerospace Engineering (66 citations). Scott D. Poll has collaborated with scholars based in United States, Netherlands and Italy. Frequent co-authors include Kai Goebel, Bhaskar Saha, Jon P. Christophersen, Indranil Roychoudhury, Ole J. Mengshoel, Ann Patterson‐Hine, Tolga Kurtoglu, Enrico Zio, Marco Rigamonti and Matthew J. Daigle. Their work appears in journals such as International Journal of Prognostics and Health Management, IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans, IEEE Transactions on Instrumentation and Measurement, AI Magazine and Neurocomputing.

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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