Siying Feng
- Hardware and Architecture top 5%
- Computer Networks and Communications top 10%
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence
- Co-authors
- Ronald DreslinskiSubhankar PalTrevor MudgeAporva AmarnathDong-Hyeon ParkDavid BlaauwHun-Seok KimChaitali Chakrabarti
- Topics
- Parallel Computing and Optimization Techniques (14 papers)Interconnection Networks and Systems (11 papers)Graph Theory and Algorithms (5 papers)
- Journals
- Carbohydrate PolymersIEEE Journal of Solid-State CircuitsMacromolecular Rapid Communications
- Partner nations
- United StatesUnited KingdomChina
In The Last Decade
Siying Feng
19 papers receiving 375 citations
Peers
Comparison fields: 5 of 51
- Hardware and Architecture 226
- Computer Networks and Communications 156
- Electrical and Electronic Engineering 128
- Computer Vision and Pattern Recognition 122
- Artificial Intelligence 90
Countries citing papers authored by Siying Feng
This map shows the geographic impact of Siying Feng'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 Siying Feng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Siying Feng more than expected).
Fields of papers citing papers by Siying Feng
This network shows the impact of papers produced by Siying Feng. 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 Siying Feng. The network helps show where Siying Feng may publish in the future.
Co-authorship network of co-authors of Siying Feng
This figure shows the co-authorship network connecting the top 25 collaborators of Siying Feng. A scholar is included among the top collaborators of Siying Feng 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 Siying Feng. Siying Feng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 16 | |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 8 | |
| 8 | 11 | |
| 9 | 13 | |
| 10 | 14 | |
| 11 | 1 | |
| 12 | 62 | |
| 13 | 14 | |
| 14 | 6 | |
| 15 | 8 | |
| 16 | 10 | |
| 17 | 190 | |
| 18 | 3 | |
| 19 | 4 |
About Siying Feng
Siying Feng is a scholar working on Hardware and Architecture, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 19 papers that have together received 378 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (14 papers), Interconnection Networks and Systems (11 papers) and Graph Theory and Algorithms (5 papers). The work is most often cited by research in Computational Mathematics (22 citations), Hardware and Architecture (226 citations) and Computer Networks and Communications (156 citations). Siying Feng has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Ronald Dreslinski, Subhankar Pal, Trevor Mudge, Aporva Amarnath, Dong-Hyeon Park, David Blaauw, Hun-Seok Kim, Chaitali Chakrabarti, Jonathan Beaumont and Xin He. Their work appears in journals such as Carbohydrate Polymers, IEEE Journal of Solid-State Circuits and Macromolecular Rapid Communications.
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.