Juncheng Yang

606 citations
28 papers · 344 · h-index 10

Impact in

Papers in

Juncheng Yang

26 papers receiving 340 citations

Peers

Juncheng Yang
Comparison fields: 5 of 43
  • Computer Networks and Communications 214
  • Hardware and Architecture 54
  • Signal Processing 72
  • Information Systems 121
  • Artificial Intelligence 114
Replace Naser Ezzati‐Jivan with:
Naser Ezzati‐Jivan Canada
Hideyuki Kawashima Japan
Liping Peng United States
Shyh-Kwei Chen United States
Emad Soroush United States
Tobias Mühlbauer Germany
Susanne Englert United States
Boduo Li United States
Michael L. Heytens United States
Sang Kyun South Korea
Juncheng Yang relative to Naser Ezzati‐Jivan Canada Naser Ezzati‐Jivan's profile →
Citations per field
00.5×2.5×
Naser Ezzati‐Jivan · 1×
Citations per year

Countries citing papers authored by Juncheng Yang

Since Specialization
Citations

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

Fields of papers citing papers by Juncheng Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Juncheng Yang, 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 Juncheng Yang Line = papers co-authored together Juncheng Yang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201762
2 202152
3
A large scale analysis of hundreds of in-memory cache clusters at Twitter
202043
4 201832
5 202120
6 201820
7 202317
8 201615
9 201812
10 201711
11 20238
12
Segcache: a memory-efficient and scalable in-memory key-value cache for small objects
20216
13 20196
14 20236
15 20236
16 20215
17 20255
18 20223
19 20243
20 20153

About Juncheng Yang

Juncheng Yang is a scholar working on Computer Networks and Communications, Information Systems, Artificial Intelligence, Computer Vision and Pattern Recognition and Hardware and Architecture, having authored 28 papers that have together received 344 indexed citations. Recurring topics across this work include Advanced Data Storage Technologies (15 papers), Cloud Computing and Resource Management (9 papers), Caching and Content Delivery (9 papers), Parallel Computing and Optimization Techniques (5 papers), Multimodal Machine Learning Applications (3 papers), Advanced Database Systems and Queries (3 papers), Privacy-Preserving Technologies in Data (3 papers) and Domain Adaptation and Few-Shot Learning (3 papers). The work is most often cited by research in Computer Networks and Communications (214 citations), Hardware and Architecture (54 citations), Signal Processing (72 citations), Information Systems (121 citations) and Artificial Intelligence (114 citations). Juncheng Yang has collaborated with scholars based in United States, China and Canada. Frequent co-authors include K. V. Rashmi, Li Xiong, Jinfei Liu, Jian Pei, Ýmir Vigfússon, Jun Luo, Ada Gavrilovska, Daniel S. Berger, Gregory R. Ganger and Nathan Beckmann. Their work appears in journals such as ACM Transactions on Storage, IEEE Transactions on Knowledge and Data Engineering, Electronics, Proceedings of the VLDB Endowment and Advances in Mechanical 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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