Gabriel Weisz
- Hardware and Architecture top 2%
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Computer Networks and Communications top 5%
- Artificial Intelligence top 10%
- Co-authors
- James C. HoeMichael PapamichaelEric S. ChungSitaram LankaSteven K. ReinhardtTodd MassengillAdrian M. CaulfieldKalin Ovtcharov
- Topics
- Parallel Computing and Optimization Techniques (8 papers)Interconnection Networks and Systems (7 papers)Advanced Memory and Neural Computing (3 papers)
- Cited by
- Hardware and ArchitectureComputer Vision and Pattern RecognitionComputer Networks and Communications
- Journals
- IEEE MicroNASA STI Repository (National Aeronautics and Space Administration)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Gabriel Weisz
11 papers receiving 490 citations
Hit Papers
Peers
Comparison fields: 5 of 44
- Hardware and Architecture 249
- Computer Vision and Pattern Recognition 206
- Electrical and Electronic Engineering 189
- Computer Networks and Communications 185
- Artificial Intelligence 154
Countries citing papers authored by Gabriel Weisz
This map shows the geographic impact of Gabriel Weisz'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 Gabriel Weisz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gabriel Weisz more than expected).
Fields of papers citing papers by Gabriel Weisz
This network shows the impact of papers produced by Gabriel Weisz. 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 Gabriel Weisz. The network helps show where Gabriel Weisz may publish in the future.
Co-authorship network of co-authors of Gabriel Weisz
This figure shows the co-authorship network connecting the top 25 collaborators of Gabriel Weisz. A scholar is included among the top collaborators of Gabriel Weisz 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 Gabriel Weisz. Gabriel Weisz 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 | 9 | |
| 3 | A Configurable Cloud-Scale DNN Processor for Real-Time AIbreakdown → | 363 |
| 4 | 13 | |
| 5 | 24 | |
| 6 | 8 | |
| 7 | 18 | |
| 8 | 54 | |
| 9 | 1 | |
| 10 | 3 | |
| 11 | 7 |
About Gabriel Weisz
Gabriel Weisz is a scholar working on Hardware and Architecture, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 11 papers that have together received 503 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (8 papers), Interconnection Networks and Systems (7 papers) and Advanced Memory and Neural Computing (3 papers). The work is most often cited by research in Hardware and Architecture (249 citations), Computer Vision and Pattern Recognition (206 citations) and Computer Networks and Communications (185 citations). Gabriel Weisz has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include James C. Hoe, Michael Papamichael, Eric S. Chung, Sitaram Lanka, Steven K. Reinhardt, Todd Massengill, Adrian M. Caulfield, Kalin Ovtcharov, Michael Haselman and Doug Burger. Their work appears in journals such as IEEE Micro and NASA STI Repository (National Aeronautics and Space Administration).
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.