Daniel Jung

887 citations
61 papers · 666 · h-index 13

Impact in

Papers in

Daniel Jung

58 papers receiving 652 citations

Peers

Daniel Jung
Comparison fields: 5 of 72
  • Control and Systems Engineering 452
  • Statistics, Probability and Uncertainty 78
  • Automotive Engineering 82
  • Safety, Risk, Reliability and Quality 37
  • Artificial Intelligence 137
Replace Setu Madhavi Namburu with:
Setu Madhavi Namburu United States
Jianhui Luo United States
Manuel Arias Chao Switzerland
Kihoon Choi United States
James R. Ottewill Poland
Arslan Ahmed Amin Pakistan
Shunsuke Chigusa United States
Mohand Djeziri France
Vasso Reppa Netherlands
Daniel Jung relative to Setu Madhavi Namburu United States Setu Madhavi Namburu's profile →
Citations per field
00.5×7.6×
Setu Madhavi Namburu · 1×
Citations per year

Countries citing papers authored by Daniel Jung

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Jung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201766
2 202163
3 201757
4 201857
5 201747
6 202032
7 201825
8 201818
9 201418
10 201416
11 201616
12 201515
13 202014
14 201812
15 201312
16 201912
17 201911
18 201710
19 20199
20 20159

About Daniel Jung

Daniel Jung is a scholar working on Control and Systems Engineering, Artificial Intelligence, Automotive Engineering, Mechanical Engineering and Electrical and Electronic Engineering, having authored 61 papers that have together received 666 indexed citations. Recurring topics across this work include Fault Detection and Control Systems (39 papers), Machine Fault Diagnosis Techniques (20 papers), Anomaly Detection Techniques and Applications (9 papers), Advanced Battery Technologies Research (8 papers), Risk and Safety Analysis (5 papers), Electric and Hybrid Vehicle Technologies (5 papers), Mineral Processing and Grinding (5 papers) and Advanced Control Systems Optimization (4 papers). The work is most often cited by research in Control and Systems Engineering (452 citations), Statistics, Probability and Uncertainty (78 citations), Automotive Engineering (82 citations), Safety, Risk, Reliability and Quality (37 citations) and Artificial Intelligence (137 citations). Daniel Jung has collaborated with scholars based in Sweden, United States and Germany. Frequent co-authors include Erik Frisk, Mattias Krysander, Kok Yew Ng, Gautam Biswas, Hamed Khorasgani, Qadeer Ahmed, Pierpaolo Polverino, Cesare Pianese, Reinhard Koch and Lars Eriksson. Their work appears in journals such as Control Engineering Practice, SAE technical papers on CD-ROM/SAE technical paper series, Energies, IEEE Transactions on Control Systems Technology and Automatica.

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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