T. K. Aarrestad
- Nuclear and High Energy Physics top 10%
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
- Computer Networks and Communications
- Co-authors
- M. PieriniJ. NgadiubaS. SummersVladimir LončarEkaterina GovorkovaJ. DuarteT. Q. NguyenZ. Wu
- Topics
- Particle physics theoretical and experimental studies (5 papers)Particle Detector Development and Performance (5 papers)Radiation Detection and Scintillator Technologies (3 papers)
- Cited by
- Nuclear and High Energy PhysicsArtificial IntelligenceComputer Vision and Pattern Recognition
- Journals
- SHILAP Revista de lepidopterologíaScientific DataNature Machine Intelligence
- Partner nations
- SwitzerlandUnited StatesSerbia
In The Last Decade
T. K. Aarrestad
8 papers receiving 146 citations
Peers
Comparison fields: 5 of 40
- Nuclear and High Energy Physics 83
- Artificial Intelligence 59
- Computer Vision and Pattern Recognition 22
- Electrical and Electronic Engineering 18
- Computer Networks and Communications 9
Countries citing papers authored by T. K. Aarrestad
This map shows the geographic impact of T. K. Aarrestad'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 T. K. Aarrestad with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. K. Aarrestad more than expected).
Fields of papers citing papers by T. K. Aarrestad
This network shows the impact of papers produced by T. K. Aarrestad. 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 T. K. Aarrestad. The network helps show where T. K. Aarrestad may publish in the future.
Co-authorship network of co-authors of T. K. Aarrestad
This figure shows the co-authorship network connecting the top 25 collaborators of T. K. Aarrestad. A scholar is included among the top collaborators of T. K. Aarrestad 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 T. K. Aarrestad. T. K. Aarrestad is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 25 | |
| 2 | 50 | |
| 3 | 1 | |
| 4 | 20 | |
| 5 | 17 | |
| 6 | 19 | |
| 7 | 1 | |
| 8 | Ultra Low-latency, Low-area Inference Accelerators using Heterogeneous Deep Quantization with QKeras and hls4ml | 15 |
About T. K. Aarrestad
T. K. Aarrestad is a scholar working on Nuclear and High Energy Physics, Radiation and Artificial Intelligence, having authored 8 papers that have together received 148 indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (5 papers), Particle Detector Development and Performance (5 papers) and Radiation Detection and Scintillator Technologies (3 papers). The work is most often cited by research in Nuclear and High Energy Physics (83 citations), Artificial Intelligence (59 citations) and Computer Vision and Pattern Recognition (22 citations). T. K. Aarrestad has collaborated with scholars based in Switzerland, United States and Serbia. Frequent co-authors include M. Pierini, J. Ngadiuba, S. Summers, Vladimir Lončar, Ekaterina Govorkova, J. Duarte, T. Q. Nguyen, Z. Wu, K. A. Wozniak and Hao Zhuang. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Data and Nature Machine Intelligence.
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.