Yanghua Peng

1.4k total citations · 1 hit paper
15 papers, 909 citations indexed

About

Yanghua Peng is a scholar working on Information Systems, Computer Networks and Communications and Computer Vision and Pattern Recognition. According to data from OpenAlex, Yanghua Peng has authored 15 papers receiving a total of 909 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Information Systems, 7 papers in Computer Networks and Communications and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Yanghua Peng's work include Cloud Computing and Resource Management (8 papers), Advanced Neural Network Applications (6 papers) and IoT and Edge/Fog Computing (5 papers). Yanghua Peng is often cited by papers focused on Cloud Computing and Resource Management (8 papers), Advanced Neural Network Applications (6 papers) and IoT and Edge/Fog Computing (5 papers). Yanghua Peng collaborates with scholars based in Hong Kong, China and United States. Yanghua Peng's co-authors include Chuan Wu, Yixin Bao, Chuanxiong Guo, Yangrui Chen, Yibo Zhu, Zongpeng Li, Chang Lan, Bairen Yi, Wei Lin and Chen Meng and has published in prestigious journals such as IEEE Journal on Selected Areas in Communications, Neural Networks and IEEE/ACM Transactions on Networking.

In The Last Decade

Yanghua Peng

14 papers receiving 892 citations

Hit Papers

Optimus 2018 2026 2020 2023 2018 50 100 150 200 250

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yanghua Peng Hong Kong 12 525 421 379 293 146 15 909
Yixin Bao Hong Kong 9 461 0.9× 386 0.9× 361 1.0× 295 1.0× 133 0.9× 14 817
Aaron Harlap United States 5 325 0.6× 219 0.5× 464 1.2× 328 1.1× 122 0.8× 6 796
Deepak Narayanan United States 7 234 0.4× 142 0.3× 335 0.9× 273 0.9× 132 0.9× 16 636
Chang Lan United States 12 873 1.7× 321 0.8× 527 1.4× 147 0.5× 201 1.4× 13 1.1k
Dazhao Cheng China 17 540 1.0× 464 1.1× 140 0.4× 91 0.3× 84 0.6× 67 722
Alexey Tumanov United States 18 1.5k 2.9× 1.4k 3.4× 325 0.9× 207 0.7× 259 1.8× 33 1.8k
Yujuan Tan China 13 455 0.9× 319 0.8× 546 1.4× 55 0.2× 74 0.5× 83 924
Laiping Zhao China 14 529 1.0× 422 1.0× 103 0.3× 70 0.2× 75 0.5× 68 807
Qiang-Sheng Hua China 18 633 1.2× 148 0.4× 206 0.5× 183 0.6× 47 0.3× 61 913
Gauri Joshi United States 15 484 0.9× 148 0.4× 429 1.1× 55 0.2× 46 0.3× 40 804

Countries citing papers authored by Yanghua Peng

Since Specialization
Citations

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

Fields of papers citing papers by Yanghua Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yanghua Peng

This figure shows the co-authorship network connecting the top 25 collaborators of Yanghua Peng. A scholar is included among the top collaborators of Yanghua Peng 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 Yanghua Peng. Yanghua Peng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

15 of 15 papers shown
3.
You, Jiaxuan, Jun He, Yuan Lin, et al.. (2023). SP-GNN: Learning structure and position information from graphs. Neural Networks. 161. 505–514. 18 indexed citations
4.
Bao, Yixin, Yanghua Peng, & Chuan Wu. (2022). Deep Learning-Based Job Placement in Distributed Machine Learning Clusters With Heterogeneous Workloads. IEEE/ACM Transactions on Networking. 31(2). 634–647. 13 indexed citations
5.
Liu, Yuanqiang, et al.. (2022). Multi-resource interleaving for deep learning training. 428–440. 36 indexed citations
6.
Peng, Yanghua, et al.. (2021). DL2: A Deep Learning-Driven Scheduler for Deep Learning Clusters. IEEE Transactions on Parallel and Distributed Systems. 32(8). 1947–1960. 44 indexed citations
7.
Bao, Yixin, et al.. (2020). Preemptive All-reduce Scheduling for Expediting Distributed DNN Training. 626–635. 45 indexed citations
8.
Chen, Yangrui, Yanghua Peng, Yixin Bao, et al.. (2020). Elastic parameter server load distribution in deep learning clusters. 507–521. 24 indexed citations
9.
Peng, Yanghua, Yibo Zhu, Yangrui Chen, et al.. (2019). A generic communication scheduler for distributed DNN training acceleration. 16–29. 208 indexed citations
10.
Bao, Yixin, Yanghua Peng, & Chuan Wu. (2019). Deep Learning-based Job Placement in Distributed Machine Learning Clusters. 505–513. 100 indexed citations
11.
Bao, Yixin, Yanghua Peng, Chuan Wu, & Zongpeng Li. (2018). Online Job Scheduling in Distributed Machine Learning Clusters. 495–503. 90 indexed citations
12.
Peng, Yanghua, Yixin Bao, Yangrui Chen, Chuan Wu, & Chuanxiong Guo. (2018). Optimus. 1–14. 274 indexed citations breakdown →
13.
Peng, Yanghua, et al.. (2017). deTector: a Topology-aware Monitoring System for Data Center Networks. USENIX Annual Technical Conference. 55–68. 28 indexed citations
14.
Duan, Jingpu, Chuan Wu, Franck Le, Alex X. Liu, & Yanghua Peng. (2017). Dynamic Scaling of Virtualized, Distributed Service Chains: A Case Study of IMS. IEEE Journal on Selected Areas in Communications. 35(11). 2501–2511. 25 indexed citations
15.
Liu, Buyun, Jing Jin, Jincheng Mai, et al.. (2014). [Secular trends of overweight and obesity prevalence between 2007 and 2011 in children and adolescents in Guangzhou].. PubMed. 48(4). 312–7. 3 indexed citations

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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