Jiecao Yu
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Electrical and Electronic Engineering
- Hardware and Architecture top 5%
- Computer Networks and Communications
- Co-authors
- Reetuparna DasAndrew LukefahrScott MahlkeDavid J. PalframanGanesh DasikaRavi IyerCharles AugustineXiaowei Wang
- Topics
- Advanced Neural Network Applications (5 papers)Advanced Memory and Neural Computing (5 papers)Ferroelectric and Negative Capacitance Devices (3 papers)
- Journals
- ACM Transactions on Embedded Computing SystemsACM SIGARCH Computer Architecture News2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Jiecao Yu
7 papers receiving 360 citations
Peers
Comparison fields: 5 of 38
- Computer Vision and Pattern Recognition 250
- Artificial Intelligence 183
- Electrical and Electronic Engineering 163
- Hardware and Architecture 88
- Computer Networks and Communications 52
Countries citing papers authored by Jiecao Yu
This map shows the geographic impact of Jiecao Yu'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 Jiecao Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jiecao Yu more than expected).
Fields of papers citing papers by Jiecao Yu
This network shows the impact of papers produced by Jiecao Yu. 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 Jiecao Yu. The network helps show where Jiecao Yu may publish in the future.
Co-authorship network of co-authors of Jiecao Yu
This figure shows the co-authorship network connecting the top 25 collaborators of Jiecao Yu. A scholar is included among the top collaborators of Jiecao Yu 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 Jiecao Yu. Jiecao Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 2 | |
| 3 | 17 | |
| 4 | 34 | |
| 5 | 12 | |
| 6 | 181 | |
| 7 | 113 |
About Jiecao Yu
Jiecao Yu is a scholar working on Computer Vision and Pattern Recognition, Hardware and Architecture and Artificial Intelligence, having authored 7 papers that have together received 365 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (5 papers), Advanced Memory and Neural Computing (5 papers) and Ferroelectric and Negative Capacitance Devices (3 papers). The work is most often cited by research in Computational Mathematics (15 citations), Hardware and Architecture (88 citations) and Computer Vision and Pattern Recognition (250 citations). Jiecao Yu has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Reetuparna Das, Andrew Lukefahr, Scott Mahlke, David J. Palframan, Ganesh Dasika, Ravi Iyer, Charles Augustine, Xiaowei Wang, Eriko Nurvitadhi and Valeria Bertacco. Their work appears in journals such as ACM Transactions on Embedded Computing Systems, ACM SIGARCH Computer Architecture News and 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA).
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.