Niangjun Chen

1.3k total citations
24 papers, 757 citations indexed

About

Niangjun Chen is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Information Systems. According to data from OpenAlex, Niangjun Chen has authored 24 papers receiving a total of 757 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Networks and Communications, 13 papers in Electrical and Electronic Engineering and 9 papers in Information Systems. Recurrent topics in Niangjun Chen's work include Cloud Computing and Resource Management (9 papers), Smart Grid Energy Management (7 papers) and Optimization and Search Problems (5 papers). Niangjun Chen is often cited by papers focused on Cloud Computing and Resource Management (9 papers), Smart Grid Energy Management (7 papers) and Optimization and Search Problems (5 papers). Niangjun Chen collaborates with scholars based in United States, Singapore and Australia. Niangjun Chen's co-authors include Adam Wierman, Zhenhua Liu, Chee Wei Tan, Tony Q. S. Quek, Yuan Chen, Steven H. Low, Xiaoqi Ren, Shaolei Ren, Ufuk Topcu and Lingwen Gan and has published in prestigious journals such as IEEE Transactions on Smart Grid, IEEE Transactions on Neural Networks and Learning Systems and IEEE Journal of Selected Topics in Signal Processing.

In The Last Decade

Niangjun Chen

24 papers receiving 741 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Niangjun Chen United States 15 517 317 225 185 124 24 757
Arobinda Gupta India 14 626 1.2× 427 1.3× 55 0.2× 413 2.2× 12 0.1× 56 916
Dhaou Said Canada 15 466 0.9× 99 0.3× 109 0.5× 255 1.4× 9 0.1× 36 643
Lazaros Gkatzikis Greece 13 700 1.4× 520 1.6× 112 0.5× 39 0.2× 18 0.1× 22 1.1k
Gyung-Leen Park South Korea 11 196 0.4× 155 0.5× 85 0.4× 116 0.6× 9 0.1× 58 459
Shuoyao Wang China 10 554 1.1× 171 0.5× 33 0.1× 282 1.5× 16 0.1× 44 806
Ayan Mondal India 14 350 0.7× 333 1.1× 81 0.4× 31 0.2× 8 0.1× 48 612
Manuel Garcia United States 8 421 0.8× 186 0.6× 36 0.2× 77 0.4× 9 0.1× 20 591
Mais Nijim United States 13 330 0.6× 305 1.0× 164 0.7× 226 1.2× 5 0.0× 50 699
Qunzhi Zhou United States 10 160 0.3× 146 0.5× 113 0.5× 55 0.3× 21 0.2× 21 427
Yeongjin Kim South Korea 9 404 0.8× 644 2.0× 173 0.8× 76 0.4× 13 0.1× 26 779

Countries citing papers authored by Niangjun Chen

Since Specialization
Citations

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

Fields of papers citing papers by Niangjun Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Niangjun Chen

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

All Works

20 of 20 papers shown
1.
Wang, Zhehui, et al.. (2025). RBFleX-NAS: Training-Free Neural Architecture Search Using Radial Basis Function Kernel and Hyperparameter Detection. IEEE Transactions on Neural Networks and Learning Systems. 36(6). 10057–10071. 1 indexed citations
2.
Tuan, Anh, et al.. (2023). LAXOR: A Bit-Accurate BNN Accelerator with Latch-XOR Logic for Local Computing. 1–6. 1 indexed citations
3.
Liu, Yu, Niangjun Chen, Zhenhua Liu, & Yuanyuan Yang. (2021). Online Cloud Resource Provisioning Under Cost Budget for QoS Maximization. 1–6. 2 indexed citations
4.
Chen, Niangjun, et al.. (2021). Smoothed Least-Laxity-First Algorithm for Electric Vehicle Charging: Online Decision and Performance Analysis With Resource Augmentation. IEEE Transactions on Smart Grid. 13(3). 2209–2217. 23 indexed citations
5.
Chen, Niangjun, et al.. (2019). Online Optimization in Cloud Resource Provisioning. ACM SIGMETRICS Performance Evaluation Review. 47(1). 47–48. 1 indexed citations
6.
Chen, Niangjun, et al.. (2019). Online Optimization in Cloud Resource Provisioning. 75. 47–48. 22 indexed citations
7.
Chen, Niangjun, et al.. (2019). Online Optimization in Cloud Resource Provisioning. Proceedings of the ACM on Measurement and Analysis of Computing Systems. 3(1). 1–30. 24 indexed citations
8.
Azizan, Navid, Krishnamurthy Dvijotham, Niangjun Chen, & Adam Wierman. (2018). Opportunities for Price Manipulation by Aggregators in Electricity Markets. CaltechAUTHORS (California Institute of Technology). 48 indexed citations
9.
Goel, Gautam, Niangjun Chen, & Adam Wierman. (2017). Thinking fast and slow: Optimization decomposition across timescales. 1291–1298. 15 indexed citations
10.
Goel, Gautam, Niangjun Chen, & Adam Wierman. (2017). Thinking Fast and Slow. ACM SIGMETRICS Performance Evaluation Review. 45(2). 27–29. 8 indexed citations
11.
Azizan, Navid, Niangjun Chen, Krishnamurthy Dvijotham, & Adam Wierman. (2016). Opportunities for Price Manipulation by Aggregators in Electricity Markets. CaltechAUTHORS (California Institute of Technology). 2 indexed citations
12.
Chen, Niangjun, et al.. (2016). Using Predictions in Online Optimization. ACM SIGMETRICS Performance Evaluation Review. 44(1). 193–206. 29 indexed citations
13.
Chen, Niangjun, Xiaoqi Ren, Shaolei Ren, & Adam Wierman. (2015). Greening Multi-Tenant Data Center Demand Response. ACM SIGMETRICS Performance Evaluation Review. 43(2). 36–38. 19 indexed citations
14.
Chen, Niangjun, Anish Agarwal, Adam Wierman, Siddharth Barman, & Lachlan L. H. Andrew. (2015). Online Convex Optimization Using Predictions. ACM SIGMETRICS Performance Evaluation Review. 43(1). 191–204. 22 indexed citations
15.
Chen, Niangjun, Xiaoqi Ren, Shaolei Ren, & Adam Wierman. (2015). Greening multi-tenant data center demand response. Performance Evaluation. 91. 229–254. 55 indexed citations
16.
Chen, Niangjun, Chee Wei Tan, & Tony Q. S. Quek. (2014). Electric Vehicle Charging in Smart Grid: Optimality and Valley-Filling Algorithms. IEEE Journal of Selected Topics in Signal Processing. 8(6). 1073–1083. 123 indexed citations
17.
Gan, Lingwen, Adam Wierman, Ufuk Topcu, Niangjun Chen, & Steven H. Low. (2014). Real-time deferrable load control. ACM SIGMETRICS Performance Evaluation Review. 41(3). 77–79. 7 indexed citations
18.
Gan, Lingwen, Adam Wierman, Ufuk Topcu, Niangjun Chen, & Steven H. Low. (2013). Real-time deferrable load control. 113–124. 73 indexed citations
19.
Liu, Zhenhua, et al.. (2013). Data center demand response. ACM SIGMETRICS Performance Evaluation Review. 41(1). 341–342. 11 indexed citations
20.
Liu, Zhenhua, et al.. (2013). Data center demand response: Avoiding the coincident peak via workload shifting and local generation. Performance Evaluation. 70(10). 770–791. 150 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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