Olga Fink
- Control and Systems Engineering top 0.5%
- Artificial Intelligence top 2%
- Mechanical Engineering top 5%
- Electrical and Electronic Engineering top 10%
- Safety, Risk, Reliability and Quality top 1%
- Co-authors
- Gabriel MichauManuel Arias ChaoChetan S. KulkarniKai GoebelEnrico ZioQin WangLuc Van GoolDengxin Dai
- Topics
- Machine Fault Diagnosis Techniques (29 papers)Fault Detection and Control Systems (22 papers)Anomaly Detection Techniques and Applications (15 papers)
- Cited by
- Control and Systems EngineeringSafety, Risk, Reliability and QualityMedical Laboratory Technology
- Journals
- Proceedings of the National Academy of SciencesNature CommunicationsSHILAP Revista de lepidopterología
- Partner nations
- SwitzerlandUnited StatesFrance
In The Last Decade
Olga Fink
92 papers receiving 3.1k citations
Hit Papers
Peers
Comparison fields: 5 of 139
- Control and Systems Engineering 1.5k
- Artificial Intelligence 801
- Mechanical Engineering 566
- Electrical and Electronic Engineering 532
- Safety, Risk, Reliability and Quality 401
Countries citing papers authored by Olga Fink
This map shows the geographic impact of Olga Fink'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 Olga Fink with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Olga Fink more than expected).
Fields of papers citing papers by Olga Fink
This network shows the impact of papers produced by Olga Fink. 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 Olga Fink. The network helps show where Olga Fink may publish in the future.
Co-authorship network of co-authors of Olga Fink
This figure shows the co-authorship network connecting the top 25 collaborators of Olga Fink. A scholar is included among the top collaborators of Olga Fink 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 Olga Fink. Olga Fink is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 5 | |
| 3 | 0 | |
| 4 | 5 | |
| 5 | 1 | |
| 6 | 6 | |
| 7 | 1 | |
| 8 | 3 | |
| 9 | 1 | |
| 10 | 13 | |
| 11 | 2 | |
| 12 | 11 | |
| 13 | 13 | |
| 14 | 0 | |
| 15 | 15 | |
| 16 | 30 | |
| 17 | 19 | |
| 18 | Battery Model Calibration with Deep Reinforcement Learning | 0 |
| 19 | 10 | |
| 20 | Development and application of deep belief networks for predicting railway operations disruptions | 4 |
About Olga Fink
Olga Fink is a scholar working on Control and Systems Engineering, Safety, Risk, Reliability and Quality and Artificial Intelligence, having authored 105 papers that have together received 3.2k indexed citations. Recurring topics across this work include Machine Fault Diagnosis Techniques (29 papers), Fault Detection and Control Systems (22 papers) and Anomaly Detection Techniques and Applications (15 papers). The work is most often cited by research in Control and Systems Engineering (1.5k citations), Safety, Risk, Reliability and Quality (401 citations) and Medical Laboratory Technology (58 citations). Olga Fink has collaborated with scholars based in Switzerland, United States and France. Frequent co-authors include Gabriel Michau, Manuel Arias Chao, Chetan S. Kulkarni, Kai Goebel, Enrico Zio, Qin Wang, Luc Van Gool, Dengxin Dai, Ulrich Weidmann and Giovanni Sansavini. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and SHILAP Revista de lepidopterología.
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.