Yinqi Tang
- Electrical and Electronic Engineering top 10%
- Artificial Intelligence top 10%
- Hardware and Architecture top 5%
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications top 10%
- Co-authors
- Naveen VermaHossein ValaviHongyang JiaJintao ZhangPeter DeavilleBonan ZhangRakshit PathakJinseok Lee
- Topics
- Advanced Memory and Neural Computing (6 papers)Ferroelectric and Negative Capacitance Devices (5 papers)CCD and CMOS Imaging Sensors (3 papers)
- Journals
- IEEE Journal of Solid-State CircuitsIEEE Transactions on Circuits and Systems I Regular PapersIEEE Transactions on Very Large Scale Integration (VLSI) Systems
- Partner nations
- United StatesChina
In The Last Decade
Yinqi Tang
12 papers receiving 717 citations
Hit Papers
Peers
Comparison fields: 5 of 41
- Electrical and Electronic Engineering 614
- Artificial Intelligence 195
- Hardware and Architecture 118
- Computer Vision and Pattern Recognition 112
- Computer Networks and Communications 71
Countries citing papers authored by Yinqi Tang
This map shows the geographic impact of Yinqi Tang'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 Yinqi Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yinqi Tang more than expected).
Fields of papers citing papers by Yinqi Tang
This network shows the impact of papers produced by Yinqi Tang. 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 Yinqi Tang. The network helps show where Yinqi Tang may publish in the future.
Co-authorship network of co-authors of Yinqi Tang
This figure shows the co-authorship network connecting the top 25 collaborators of Yinqi Tang. A scholar is included among the top collaborators of Yinqi Tang 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 Yinqi Tang. Yinqi Tang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 117 | |
| 2 | 58 | |
| 3 | 61 | |
| 4 | 6 | |
| 5 | 154 | |
| 6 | 6 | |
| 7 | In-Memory Computing: Advances and Prospectsbreakdown → | 269 |
| 8 | 9 | |
| 9 | 8 | |
| 10 | 13 | |
| 11 | 28 | |
| 12 | 3 |
About Yinqi Tang
Yinqi Tang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Hardware and Architecture, having authored 12 papers that have together received 732 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (6 papers), Ferroelectric and Negative Capacitance Devices (5 papers) and CCD and CMOS Imaging Sensors (3 papers). The work is most often cited by research in Hardware and Architecture (118 citations), Electrical and Electronic Engineering (614 citations) and Artificial Intelligence (195 citations). Yinqi Tang has collaborated with scholars based in United States and China. Frequent co-authors include Naveen Verma, Hossein Valavi, Hongyang Jia, Jintao Zhang, Peter Deaville, Bonan Zhang, Rakshit Pathak, Jinseok Lee, Jinseok Lee and Dawu Gu. Their work appears in journals such as IEEE Journal of Solid-State Circuits, IEEE Transactions on Circuits and Systems I Regular Papers and IEEE Transactions on Very Large Scale Integration (VLSI) Systems.
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.