Daniel L. Ewert

761 citations
81 papers · 564 · h-index 12

Impact in

Papers in

Daniel L. Ewert

72 papers receiving 544 citations

Peers

Daniel L. Ewert
Comparison fields: 5 of 85
  • Industrial and Manufacturing Engineering 128
  • Biomedical Engineering 217
  • Management of Technology and Innovation 21
  • Aerospace Engineering 69
  • Geology 15
Replace Kyungho Lee with:
Kyungho Lee South Korea
Milan Adámek Czechia
James Cunningham United States
Der‐Baau Perng Taiwan
Runxiao Wang China
Debasish Mishra India
Jianguo Hu China
Anna Kochan South Korea
Richard Bloss South Korea
Aitor Ibarguren Spain
Daniel L. Ewert relative to Kyungho Lee South Korea Kyungho Lee's profile →
Citations per field
00.5×2×4×5.3×
Kyungho Lee · 1×
Citations per year

Countries citing papers authored by Daniel L. Ewert

Since Specialization
Citations

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

Fields of papers citing papers by Daniel L. Ewert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel L. Ewert. 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 Daniel L. Ewert. The network helps show where Daniel L. Ewert may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 81 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201953
2 201547
3 200344
4 201836
5 201430
6 201124
7 202019
8 201319
9 201116
10 201416
11 201613
12 199912
13 201912
14 201210
15 20139
16 20139
17 20109
18 20119
19 20158
20 20128

About Daniel L. Ewert

Daniel L. Ewert is a scholar working on Industrial and Manufacturing Engineering, Cardiology and Cardiovascular Medicine, Biomedical Engineering, Computer Vision and Pattern Recognition and Management of Technology and Innovation, having authored 81 papers that have together received 564 indexed citations. Recurring topics across this work include Flexible and Reconfigurable Manufacturing Systems (18 papers), Manufacturing Process and Optimization (14 papers), Advanced Manufacturing and Logistics Optimization (7 papers), Cardiovascular Function and Risk Factors (6 papers), Wireless Body Area Networks (6 papers), Robot Manipulation and Learning (6 papers), AI-based Problem Solving and Planning (6 papers) and Digital Transformation in Industry (6 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (128 citations), Biomedical Engineering (217 citations), Management of Technology and Innovation (21 citations), Aerospace Engineering (69 citations) and Geology (15 citations). Daniel L. Ewert has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Sabina Jeschke, Sajid Mehmood Asif, Benjamin Davis Braaten, Daniel Schilberg, Adnan Iftikhar, Steven C. Koenig, Muhammad Saeed Khan, Mark J. Schroeder, Gerhard Lakemeyer and Alexander Ferrein. Their work appears in journals such as IEEE Access, ASAIO Journal, IET Microwaves Antennas & Propagation, Computers in Biology and Medicine and IEEE Reviews in Biomedical Engineering.

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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