David Lenz

17 papers receiving 427 citations

Peers

David Lenz
Comparison fields: 5 of 65
  • Automotive Engineering 243
  • Control and Systems Engineering 158
  • Safety, Risk, Reliability and Quality 57
  • Computer Vision and Pattern Recognition 108
  • General Social Sciences 11
Replace Roland E. Haas with:
Roland E. Haas Germany
Bala Chandran United States
Miguel A. López-Carmona Spain
Jiapeng Yu China
Matthieu Bricogne France
Madeline Cheah United Kingdom
Samir Aknine France
Jens Ohlsson Sweden
Joshua Lubell United States
Simon R. Goerger United States
David Lenz relative to Roland E. Haas Germany Roland E. Haas's profile →
Citations per field
00.5×4.7×
Roland E. Haas · 1×
Citations per year

Countries citing papers authored by David Lenz

Since Specialization
Citations

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

Fields of papers citing papers by David Lenz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1 2017166
2 201658
3 201756
4 202352
5 201522
6 202020
7 202318
8 202213
9 20157
10 20226
11 20235
12 20115
13 20125
14 20184
15 20212
16 20162
17 20241
18 20250

About David Lenz

David Lenz is a scholar working on Management Science and Operations Research, Economics and Econometrics, Automotive Engineering, Sociology and Political Science and Computer Vision and Pattern Recognition, having authored 18 papers that have together received 442 indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (4 papers), Innovation Diffusion and Forecasting (4 papers), Robotics and Sensor-Based Localization (2 papers), COVID-19 epidemiological studies (2 papers), Robotic Path Planning Algorithms (2 papers), Digital Marketing and Social Media (2 papers), COVID-19 Pandemic Impacts (2 papers) and Energy, Environment, Economic Growth (2 papers). The work is most often cited by research in Automotive Engineering (243 citations), Control and Systems Engineering (158 citations), Safety, Risk, Reliability and Quality (57 citations), Computer Vision and Pattern Recognition (108 citations) and General Social Sciences (11 citations). David Lenz has collaborated with scholars based in Germany, United States and Austria. Frequent co-authors include Alois Knoll, Christoph Stiller, Constantin Hubmann, Daniel Althoff, Marvin B. Becker, Jan Kinne, Frederik Diehl, Peter Winker, Bernd Ebersberger and Mathias Beck. Their work appears in journals such as PLoS ONE, The Science of The Total Environment, International Journal of Information Management Data Insights, Journal of Open Innovation Technology Market and Complexity and Research Policy.

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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