Lorenz Diener
- Cognitive Neuroscience top 10%
- Signal Processing top 5%
- Artificial Intelligence top 10%
- Electrical and Electronic Engineering
- Cellular and Molecular Neuroscience
- Co-authors
- Matthias JankeTanja SchultzChristian HerffDean J. KrusienskiMiguel AngrickRoss CutlerAndo SaabasEmily M. Mugler
- Topics
- Speech and Audio Processing (7 papers)EEG and Brain-Computer Interfaces (7 papers)Speech Recognition and Synthesis (6 papers)
- Journals
- Frontiers in NeuroscienceCommunications BiologyIEEE/ACM Transactions on Audio Speech and Language Processing
- Partner nations
- GermanyUnited StatesNetherlands
In The Last Decade
Lorenz Diener
21 papers receiving 407 citations
Peers
Comparison fields: 5 of 46
- Cognitive Neuroscience 208
- Signal Processing 188
- Artificial Intelligence 175
- Electrical and Electronic Engineering 51
- Cellular and Molecular Neuroscience 43
Countries citing papers authored by Lorenz Diener
This map shows the geographic impact of Lorenz Diener'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 Lorenz Diener with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lorenz Diener more than expected).
Fields of papers citing papers by Lorenz Diener
This network shows the impact of papers produced by Lorenz Diener. 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 Lorenz Diener. The network helps show where Lorenz Diener may publish in the future.
Co-authorship network of co-authors of Lorenz Diener
This figure shows the co-authorship network connecting the top 25 collaborators of Lorenz Diener. A scholar is included among the top collaborators of Lorenz Diener 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 Lorenz Diener. Lorenz Diener is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 5 | |
| 3 | 7 | |
| 4 | 29 | |
| 5 | 10 | |
| 6 | 73 | |
| 7 | 6 | |
| 8 | 4 | |
| 9 | 76 | |
| 10 | 10 | |
| 11 | 1 | |
| 12 | Session-Independent Array-Based EMG-to-Speech Conversion using Convolutional Neural Networks. | 8 |
| 13 | A comparison of EMG-to-Speech Conversion for Isolated and Continuous Speech. | 6 |
| 14 | 6 | |
| 15 | 86 | |
| 16 | 14 | |
| 17 | 32 | |
| 18 | 32 | |
| 19 | 3 | |
| 20 | 4 |
About Lorenz Diener
Lorenz Diener is a scholar working on Human-Computer Interaction, Signal Processing and Occupational Therapy, having authored 21 papers that have together received 421 indexed citations. Recurring topics across this work include Speech and Audio Processing (7 papers), EEG and Brain-Computer Interfaces (7 papers) and Speech Recognition and Synthesis (6 papers). The work is most often cited by research in Signal Processing (188 citations), Cognitive Neuroscience (208 citations) and Human-Computer Interaction (41 citations). Lorenz Diener has collaborated with scholars based in Germany, United States and Netherlands. Frequent co-authors include Matthias Janke, Tanja Schultz, Christian Herff, Dean J. Krusienski, Miguel Angrick, Ross Cutler, Ando Saabas, Emily M. Mugler, Marc W. Slutzky and Matthew Goldrick. Their work appears in journals such as Frontiers in Neuroscience, Communications Biology and IEEE/ACM Transactions on Audio Speech and Language Processing.
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.