Nina Wiedemann

582 total citations
24 papers, 234 citations indexed

About

Nina Wiedemann is a scholar working on Transportation, Automotive Engineering and Artificial Intelligence. According to data from OpenAlex, Nina Wiedemann has authored 24 papers receiving a total of 234 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Transportation, 5 papers in Automotive Engineering and 5 papers in Artificial Intelligence. Recurrent topics in Nina Wiedemann's work include Human Mobility and Location-Based Analysis (7 papers), Urban Transport and Accessibility (5 papers) and Transportation and Mobility Innovations (4 papers). Nina Wiedemann is often cited by papers focused on Human Mobility and Location-Based Analysis (7 papers), Urban Transport and Accessibility (5 papers) and Transportation and Mobility Innovations (4 papers). Nina Wiedemann collaborates with scholars based in Switzerland, Austria and United Kingdom. Nina Wiedemann's co-authors include Martin Raubal, Jannis Born, Avinash Aujayeb, Henry Martin, Michael Moor, Karsten Borgwardt, Julie Goulet, Bastian Rieck, Dominik Bucher and Ye Hong and has published in prestigious journals such as Scientific Reports, Applied Energy and IEEE Transactions on Intelligent Transportation Systems.

In The Last Decade

Nina Wiedemann

21 papers receiving 229 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Nina Wiedemann Switzerland 7 92 55 54 42 39 24 234
Lun-Chi Chen Taiwan 10 28 0.3× 59 1.1× 3 0.1× 6 0.1× 11 0.3× 28 238
Kai-Chih Pai Taiwan 11 26 0.3× 81 1.5× 17 0.3× 22 0.6× 26 262
Sekar Kidambi Raju India 8 65 0.7× 53 1.0× 1 0.0× 19 0.5× 17 0.4× 19 201
Sharut Gupta India 4 97 1.1× 75 1.4× 2 0.0× 4 0.1× 15 0.4× 5 214
Jiewen Deng China 8 6 0.1× 66 1.2× 4 0.1× 80 1.9× 6 0.2× 14 250
David A. Mong United States 5 58 0.6× 89 1.6× 3 0.1× 2 0.0× 19 0.5× 11 232
Ahmad Abuashour Jordan 9 53 0.6× 42 0.8× 6 0.1× 13 0.3× 12 309
N Moradzadeh United States 3 121 1.3× 165 3.0× 2 0.0× 4 0.1× 13 0.3× 6 341
Fatema Tuj Johora Bangladesh 9 28 0.3× 39 0.7× 1 0.0× 18 0.4× 10 0.3× 25 205
Leandro Miranda Brazil 8 8 0.1× 42 0.8× 7 0.1× 10 0.2× 6 0.2× 18 263

Countries citing papers authored by Nina Wiedemann

Since Specialization
Citations

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

Fields of papers citing papers by Nina Wiedemann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nina Wiedemann

This figure shows the co-authorship network connecting the top 25 collaborators of Nina Wiedemann. A scholar is included among the top collaborators of Nina Wiedemann 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 Nina Wiedemann. Nina Wiedemann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wiedemann, Nina, Dianne de Korte‐de Boer, Michael Richter, et al.. (2025). COVID-BLUeS - a Prospective Study on the Value of AI in Lung Ultrasound Analysis. IEEE Journal of Biomedical and Health Informatics. 29(9). 6301–6310.
2.
Wiedemann, Nina, et al.. (2025). GeOT: a spatially explicit framework for evaluating spatio-temporal predictions. International Journal of Geographical Information Systems. 39(10). 2236–2266. 1 indexed citations
3.
Wiedemann, Nina, et al.. (2025). AI-augmented pathology: the experience of transfer learning and intra-domain data diversity in breast cancer metastasis detection. Frontiers in Oncology. 15. 1598289–1598289. 1 indexed citations
4.
Wiedemann, Nina, et al.. (2024). An ontology-based approach for harmonizing metrics in bike network evaluations. Computers Environment and Urban Systems. 113. 102178–102178. 2 indexed citations
5.
Wiedemann, Nina, et al.. (2024). Vehicle-to-grid for car sharing - A simulation study for 2030. Applied Energy. 372. 123731–123731. 5 indexed citations
6.
Wiedemann, Nina, et al.. (2024). Bike network planning in limited urban space. Transportation Research Part B Methodological. 192. 103135–103135. 4 indexed citations
7.
Wiedemann, Nina, et al.. (2024). Quantifying the dynamic predictability of train delay with uncertainty-aware neural networks. Transportation Research Part C Emerging Technologies. 162. 104563–104563. 4 indexed citations
8.
Wiedemann, Nina, Krzysztof Janowicz, Martin Raubal, & Ourania Kounadi. (2024). Where you go is who you are: a study on machine learning based semantic privacy attacks. Journal Of Big Data. 11(1). 2 indexed citations
9.
Wiedemann, Nina, Henry Martin, Esra Süel, Ye Hong, & Yanan Xin. (2023). Influence of tracking duration on the privacy of individual mobility graphs. Journal of Location Based Services. 17(4). 370–388. 1 indexed citations
10.
Xin, Yanan, Cheng Fu, Nina Wiedemann, et al.. (2023). Metropolitan Segment Traffic Speeds From Massive Floating Car Data in 10 Cities. IEEE Transactions on Intelligent Transportation Systems. 24(11). 12821–12830. 5 indexed citations
11.
Martin, Henry, Ye Hong, Nina Wiedemann, Dominik Bucher, & Martin Raubal. (2023). Trackintel: An open-source Python library for human mobility analysis. Computers Environment and Urban Systems. 101. 101938–101938. 23 indexed citations
12.
Süel, Esra, et al.. (2023). Vehicle-to-grid and car sharing: Willingness for flexibility in reservation times in Switzerland. Transportation Research Part D Transport and Environment. 126. 104014–104014. 14 indexed citations
13.
Wiedemann, Nina, et al.. (2023). National-scale bi-directional EV fleet control for ancillary service provision. Energy Informatics. 6(S1). 3 indexed citations
14.
Wiedemann, Nina, et al.. (2023). Training Efficient Controllers via Analytic Policy Gradient. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 1349–1356. 4 indexed citations
15.
Shi, Meilin, Zilong Liu, Krzysztof Janowicz, et al.. (2023). Thinking Geographically about AI Sustainability. Repository for Publications and Research Data (ETH Zurich). 4. 1–7. 14 indexed citations
16.
Wiedemann, Nina, Henry Martin, & Martin Raubal. (2022). Unlocking social network analysis methods for studying human mobility. Repository for Publications and Research Data (ETH Zurich). 3. 1–12. 5 indexed citations
17.
18.
Born, Jannis, Nina Wiedemann, Julie Goulet, et al.. (2021). Accelerating Detection of Lung Pathologies with Explainable Ultrasound Image Analysis. Applied Sciences. 11(2). 672–672. 96 indexed citations
19.
Wiedemann, Nina, et al.. (2019). Towards a Framework for Predictive Maintenance Strategies in Mechanical Engineering – A Method-Oriented Literature Analysis. Journal of the Association for Information Systems. 72–76.
20.
May, Elisabeth S., Laura Tiemann, Paul J. Schmidt, et al.. (2017). Behavioral responses to noxious stimuli shape the perception of pain. Scientific Reports. 7(1). 44083–44083. 15 indexed citations

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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