Ping Chi

2.2k citations
23 papers · 1.6k indexed · 2 hit papers · h-index 12

Ping Chi

21 papers receiving 1.6k citations

Hit Papers

PRIME9102016202620192022250500750

Peers

Ping Chi
Comparison fields: 5 of 56
  • Hardware and Architecture 357
  • Electrical and Electronic Engineering 1.3k
  • Computer Vision and Pattern Recognition 366
  • Computer Networks and Communications 293
  • Artificial Intelligence 366
Replace Ren-Shuo Liu with:
Ren-Shuo Liu Taiwan
Anirban Nag United States
Win-San Khwa Taiwan
Dimin Niu United States
Linghao Song United States
Yu-Der Chih Taiwan
Peng Gu United States
Swagath Venkataramani United States
Saransh Gupta United States
Kailash Gopalakrishnan United States
Ping Chi relative to Ren-Shuo Liu Taiwan Ren-Shuo Liu's profile →
Citations per field
00.5×4.2×
Ren-Shuo Liu · 1×
Citations per year

Countries citing papers authored by Ping Chi

Since Specialization
Citations

This map shows the geographic impact of Ping Chi'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 Ping Chi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ping Chi more than expected).

Fields of papers citing papers by Ping Chi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ping Chi. 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 Ping Chi. The network helps show where Ping Chi may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Ping Chi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ping Chi Line = papers co-authored together Ping Chi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20245
4 201712
5 20179
6 201714
7 201635
8 201630
9 2016910
10 201659
11 201513
12 20157
13 201510
14 201417
15 201416
16 201427
17 20113
18 20112
19 20104
20 20101

About Ping Chi

Ping Chi is a scholar working on Hardware and Architecture, Gastroenterology and Computer Networks and Communications, having authored 23 papers that have together received 1.6k indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (11 papers), Advanced Memory and Neural Computing (11 papers), Advanced Data Storage Technologies (11 papers), Ferroelectric and Negative Capacitance Devices (4 papers), Gastrointestinal Tumor Research and Treatment (3 papers), Neural Networks and Reservoir Computing (2 papers), Distributed systems and fault tolerance (2 papers) and Machine Learning and ELM (2 papers). The work is most often cited by research in Hardware and Architecture (357 citations), Electrical and Electronic Engineering (1.3k citations) and Computer Vision and Pattern Recognition (366 citations). Ping Chi has collaborated with scholars based in United States, China and France. Frequent co-authors include Yuan Xie, Jishen Zhao, Shuangchen Li, Yu Wang, Tao Zhang, Yongpan Liu, Cong Xu, Shuangchen Li, Wenguang Chen and Peng Qu. Their work appears in journals such as Journal of Clinical Oncology, Journal of Visualized Experiments, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, International Symposium on Microarchitecture and International Conference on Bioinformatics and Biomedical Engineering.

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.

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