Jakob D. Havtorn
- Artificial Intelligence top 10%
- Signal Processing top 10%
- Experimental and Cognitive Psychology
- Computer Vision and Pattern Recognition
- Cognitive Neuroscience
- Co-authors
- Lasse BorgholtLars MaaløeChristian IgelHung-yi LeeKatrin KirchhoffTara N. SainathShinji WatanabeShang-Wen Li
- Topics
- Music and Audio Processing (3 papers)Speech Recognition and Synthesis (3 papers)Machine Learning in Healthcare (2 papers)
- Journals
- IEEE Journal of Selected Topics in Signal Processingnpj Digital MedicineResearch at the University of Copenhagen (University of Copenhagen)
- Partner nations
- DenmarkUnited StatesIreland
In The Last Decade
Jakob D. Havtorn
7 papers receiving 222 citations
Hit Papers
Peers
Comparison fields: 5 of 48
- Artificial Intelligence 170
- Signal Processing 94
- Experimental and Cognitive Psychology 21
- Computer Vision and Pattern Recognition 18
- Cognitive Neuroscience 11
Countries citing papers authored by Jakob D. Havtorn
This map shows the geographic impact of Jakob D. Havtorn'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 Jakob D. Havtorn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jakob D. Havtorn more than expected).
Fields of papers citing papers by Jakob D. Havtorn
This network shows the impact of papers produced by Jakob D. Havtorn. 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 Jakob D. Havtorn. The network helps show where Jakob D. Havtorn may publish in the future.
Co-authorship network of co-authors of Jakob D. Havtorn
This figure shows the co-authorship network connecting the top 25 collaborators of Jakob D. Havtorn. A scholar is included among the top collaborators of Jakob D. Havtorn 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 Jakob D. Havtorn. Jakob D. Havtorn is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 7 | |
| 3 | 15 | |
| 4 | 5 | |
| 5 | Self-Supervised Speech Representation Learning: A Reviewbreakdown → | 194 |
| 6 | 2 | |
| 7 | 4 |
About Jakob D. Havtorn
Jakob D. Havtorn is a scholar working on Signal Processing, Biophysics and Artificial Intelligence, having authored 7 papers that have together received 228 indexed citations. Recurring topics across this work include Music and Audio Processing (3 papers), Speech Recognition and Synthesis (3 papers) and Machine Learning in Healthcare (2 papers). The work is most often cited by research in Signal Processing (94 citations), Artificial Intelligence (170 citations) and Health Informatics (4 citations). Jakob D. Havtorn has collaborated with scholars based in Denmark, United States and Ireland. Frequent co-authors include Lasse Borgholt, Lars Maaløe, Christian Igel, Hung-yi Lee, Katrin Kirchhoff, Tara N. Sainath, Shinji Watanabe, Shang-Wen Li, Karen Livescu and Abdelrahman Mohamed. Their work appears in journals such as IEEE Journal of Selected Topics in Signal Processing, npj Digital Medicine and Research at the University of Copenhagen (University of Copenhagen).
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.