Suzanne Rivoire
- Computer Networks and Communications top 2%
- Information Systems top 1%
- Hardware and Architecture top 2%
- Electrical and Electronic Engineering
- Artificial Intelligence
- Co-authors
- Christos KozyrakisParthasarathy RanganathanDaphne EconomouMehul A. ShahJustin MezaJohn D. DavisMoisés GoldszmidtEhsan K. Ardestani
- Topics
- Cloud Computing and Resource Management (14 papers)Parallel Computing and Optimization Techniques (13 papers)Advanced Data Storage Technologies (10 papers)
- Partner nations
- United StatesIndiaGermany
In The Last Decade
Suzanne Rivoire
17 papers receiving 774 citations
Peers
Comparison fields: 5 of 42
- Computer Networks and Communications 672
- Information Systems 571
- Hardware and Architecture 375
- Electrical and Electronic Engineering 272
- Artificial Intelligence 33
Countries citing papers authored by Suzanne Rivoire
This map shows the geographic impact of Suzanne Rivoire'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 Suzanne Rivoire with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Suzanne Rivoire more than expected).
Fields of papers citing papers by Suzanne Rivoire
This network shows the impact of papers produced by Suzanne Rivoire. 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 Suzanne Rivoire. The network helps show where Suzanne Rivoire may publish in the future.
Co-authorship network of co-authors of Suzanne Rivoire
This figure shows the co-authorship network connecting the top 25 collaborators of Suzanne Rivoire. A scholar is included among the top collaborators of Suzanne Rivoire 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 Suzanne Rivoire. Suzanne Rivoire is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 15 | |
| 3 | 5 | |
| 4 | 11 | |
| 5 | 6 | |
| 6 | 10 | |
| 7 | Accounting for Variability in Large-Scale Cluster Power Models | 18 |
| 8 | 6 | |
| 9 | 3 | |
| 10 | 18 | |
| 11 | 1 | |
| 12 | Building Energy-Efficient Systems for Sequential I/O Workloads | 3 |
| 13 | A comparison of high-level full-system power models | 200 |
| 14 | Models and metrics for energy-efficient computer systems | 29 |
| 15 | 159 | |
| 16 | 64 | |
| 17 | Full-System Power Analysis and Modeling for Server Environments | 244 |
| 18 | 29 |
About Suzanne Rivoire
Suzanne Rivoire is a scholar working on Hardware and Architecture, Information Systems and Computer Networks and Communications, having authored 18 papers that have together received 821 indexed citations. Recurring topics across this work include Cloud Computing and Resource Management (14 papers), Parallel Computing and Optimization Techniques (13 papers) and Advanced Data Storage Technologies (10 papers). The work is most often cited by research in Hardware and Architecture (375 citations), Computer Networks and Communications (672 citations) and Information Systems (571 citations). Suzanne Rivoire has collaborated with scholars based in United States, India and Germany. Frequent co-authors include Christos Kozyrakis, Parthasarathy Ranganathan, Daphne Economou, Mehul A. Shah, Justin Meza, John D. Davis, Moisés Goldszmidt, Ehsan K. Ardestani, Rebecca Schultz and Daniel Hackenberg. Their work appears in journals such as Kidney International, Computer and IEEE Computer Architecture Letters.
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.