Jörg Lampe
Impact in
- Mathematical Physics top 10%
- Numerical methods in inverse problems
- Applied Mathematics top 5%
- Statistical and numerical algorithms
Papers in
-
- Adsorption and Cooling Systems 6
- Thermodynamic and Exergetic Analyses of Power and Cooling Systems 3
- Carbon Dioxide Capture Technologies 3
-
- Numerical methods in inverse problems 9
- Co-authors
- Heinrich Voß (8 shared papers)Rainer Hamann (1 shared paper)Lothar Reichel (1 shared paper)Thomas Seeger (6 shared papers)J. Borgert (1 shared paper)J. Weizenecker (1 shared paper)Jürgen Rahmer (1 shared paper)Bernhard Gleich (1 shared paper)
- Journals
- International Journal of Hydrogen Energy (4 papers)Renewable Energy (2 papers)Energy and AI (1 paper)Linear Algebra and its Applications (1 paper)Journal of Computational and Applied Mathematics (1 paper)
- Partner nations
- GermanySwitzerlandSpain
In The Last Decade
Jörg Lampe
26 papers receiving 350 citations
Peers
Comparison fields: 5 of 68
- Mathematical Physics 75
- Applied Mathematics 84
- Energy Engineering and Power Technology 15
- Catalysis 23
- Computer Vision and Pattern Recognition 65
Countries citing papers authored by Jörg Lampe
This map shows the geographic impact of Jörg Lampe'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 Jörg Lampe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jörg Lampe more than expected).
Fields of papers citing papers by Jörg Lampe
This network shows the impact of papers produced by Jörg Lampe. 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 Jörg Lampe. The network helps show where Jörg Lampe may publish in the future.
Co-authors
The 20 scholars most cited alongside Jörg Lampe, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 63 | |
| 2 | 2011 | 37 | |
| 3 | 2022 | 32 | |
| 4 | 2018 | 30 | |
| 5 | 2007 | 25 | |
| 6 | 2018 | 25 | |
| 7 | 2012 | 24 | |
| 8 | 2008 | 21 | |
| 9 | 2010 | 18 | |
| 10 | 2008 | 15 | |
| 11 | 2022 | 13 | |
| 12 | 2022 | 13 | |
| 13 | 2020 | 8 | |
| 14 | 2010 | 8 | |
| 15 | 2024 | 8 | |
| 16 | 2013 | 6 | |
| 17 | 2023 | 5 | |
| 18 | 2005 | 5 | |
| 19 | 2024 | 5 | |
| 20 | 2023 | 5 |
About Jörg Lampe
Jörg Lampe is a scholar working on Mechanical Engineering, Mathematical Physics, Applied Mathematics, Computational Theory and Mathematics and Biomedical Engineering, having authored 27 papers that have together received 374 indexed citations. Recurring topics across this work include Numerical methods in inverse problems (9 papers), Statistical and numerical algorithms (9 papers), Matrix Theory and Algorithms (7 papers), Chemical Looping and Thermochemical Processes (7 papers), Adsorption and Cooling Systems (6 papers), Image and Signal Denoising Methods (5 papers), Thermodynamic and Exergetic Analyses of Power and Cooling Systems (3 papers) and Carbon Dioxide Capture Technologies (3 papers). The work is most often cited by research in Mathematical Physics (75 citations), Applied Mathematics (84 citations), Energy Engineering and Power Technology (15 citations), Catalysis (23 citations) and Computer Vision and Pattern Recognition (65 citations). Jörg Lampe has collaborated with scholars based in Germany, Switzerland and Spain. Frequent co-authors include Heinrich Voß, Rainer Hamann, Lothar Reichel, Thomas Seeger, J. Borgert, J. Weizenecker, Jürgen Rahmer, Bernhard Gleich, Sohag Kabir and Yiannis Papadopoulos. Their work appears in journals such as International Journal of Hydrogen Energy, Renewable Energy, Energy and AI, Linear Algebra and its Applications and Journal of Computational and Applied Mathematics.
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.