Bong Jun Ko

924 total citations · 1 hit paper
31 papers, 524 citations indexed

About

Bong Jun Ko is a scholar working on Computer Networks and Communications, Artificial Intelligence and Information Systems. According to data from OpenAlex, Bong Jun Ko has authored 31 papers receiving a total of 524 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computer Networks and Communications, 12 papers in Artificial Intelligence and 7 papers in Information Systems. Recurrent topics in Bong Jun Ko's work include Software System Performance and Reliability (7 papers), Caching and Content Delivery (4 papers) and Mobile Ad Hoc Networks (4 papers). Bong Jun Ko is often cited by papers focused on Software System Performance and Reliability (7 papers), Caching and Content Delivery (4 papers) and Mobile Ad Hoc Networks (4 papers). Bong Jun Ko collaborates with scholars based in United States, United Kingdom and Switzerland. Bong Jun Ko's co-authors include Kin K. Leung, Shiqiang Wang, Wei‐Han Lee, Víctor Valls, Yuang Jiang, Leandros Tassiulas, Murtaza Zafer, Theodoros Salonidis, Alexander L. Wolf and Petr Novotný and has published in prestigious journals such as IEEE Transactions on Neural Networks and Learning Systems, IEEE/ACM Transactions on Networking and IEEE Transactions on Parallel and Distributed Systems.

In The Last Decade

Bong Jun Ko

31 papers receiving 514 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Model Pruning Enables Efficient Federated Learning on Edge Devices

2022 288 citations Yuang Jiang, Shiqiang Wang et al. IEEE Transactions on Neural Networks and Learning Systems profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Bong Jun Ko United States	10	272	255	119	72	51	31	524
Urmish Thakker United States	5	397 1.5×	180 0.7×	99 0.8×	75 1.0×	44 0.9×	8	511
Zeyi Tao United States	9	276 1.0×	197 0.8×	82 0.7×	106 1.5×	63 1.2×	17	471
Dian Shi China	11	256 0.9×	200 0.8×	148 1.2×	53 0.7×	49 1.0×	15	477
Inshil Doh South Korea	11	197 0.7×	296 1.2×	139 1.2×	141 2.0×	56 1.1×	59	535
Huahong Ma China	12	138 0.5×	339 1.3×	161 1.4×	81 1.1×	47 0.9×	67	575
Guosheng Huang China	13	139 0.5×	340 1.3×	179 1.5×	83 1.2×	71 1.4×	27	533
Bimal Ghimire United States	6	255 0.9×	167 0.7×	88 0.7×	112 1.6×	21 0.4×	9	377
Abdullatif Albaseer Qatar	13	224 0.8×	219 0.9×	168 1.4×	59 0.8×	40 0.8×	47	481
Xiaoping Xue China	10	158 0.6×	177 0.7×	288 2.4×	46 0.6×	49 1.0×	38	431

Countries citing papers authored by Bong Jun Ko

Since Specialization

Citations

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

Fields of papers citing papers by Bong Jun Ko

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bong Jun Ko. 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 Bong Jun Ko. The network helps show where Bong Jun Ko may publish in the future.

Co-authorship network of co-authors of Bong Jun Ko

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Jiang, Yuang, Shiqiang Wang, Víctor Valls, et al.. (2022). Model Pruning Enables Efficient Federated Learning on Edge Devices. IEEE Transactions on Neural Networks and Learning Systems. 34(12). 10374–10386. 288 indexed citations breakdown →

2.

Inoue, Tadanobu, et al.. (2019). Shuffling and Mixing Data Augmentation for Environmental Sound Classification. Faculty Digital Archive (New York University Florence). 109–113. 13 indexed citations

3.

Ko, Bong Jun, et al.. (2019). On Data Summarization for Machine Learning in Multi-organization Federations. 63–68. 1 indexed citations

4.

Ahn, Jae‐wook, Bong Jun Ko, Wei‐Han Lee, et al.. (2019). Acoustic anomaly detection system. 378–379. 2 indexed citations

5.

Verma, Dinesh, et al.. (2018). Generation and management of training data for AI-based algorithms targeted at coalition operations. 28–28. 1 indexed citations

6.

Silvestri, Simone, Rahul Urgaonkar, Murtaza Zafer, & Bong Jun Ko. (2018). A Framework for the Inference of Sensing Measurements Based on Correlation. ACM Transactions on Sensor Networks. 15(1). 1–28. 14 indexed citations

7.

Leung, Kin K., Theodoros Salonidis, & Bong Jun Ko. (2018). Machine learning for dynamic resource allocation at network edge. Spiral (Imperial College London). 18–18. 2 indexed citations

8.

Ma, Liang, et al.. (2018). Resource management in distributed SDN using reinforcement learning. Spiral (Imperial College London). 103. 21–21. 5 indexed citations

9.

Novotný, Petr, Bong Jun Ko, & Alexander L. Wolf. (2016). Locating Faults in MANET-Hosted Software Systems. IEEE Transactions on Dependable and Secure Computing. 15(3). 452–465. 5 indexed citations

10.

Ko, Bong Jun, Jorge Ortiz, Theodoros Salonidis, et al.. (2016). Acoustic Signal Processing for Anomaly Detection in Machine Room Environments. 213–214. 10 indexed citations

11.

Novotný, Petr, Bong Jun Ko, & Alexander L. Wolf. (2015). Delay Tolerant Harvesting of Monitoring Data for MANET-Hosted Service-Based Systems. 9–16. 1 indexed citations

12.

Ko, Bong Jun, et al.. (2014). Adaptive Algorithms for Diagnosing Large-Scale Failures in Computer Networks. IEEE Transactions on Parallel and Distributed Systems. 26(3). 646–656. 1 indexed citations

13.

Ko, Bong Jun, et al.. (2013). Gateway selection in hybrid wireless networks through cooperative probing. Integrated Network Management. 352–360. 5 indexed citations

14.

Novotný, Petr, Alexander L. Wolf, & Bong Jun Ko. (2012). Fault Localization in MANET-Hosted Service-Based Systems. 68. 243–248. 6 indexed citations

15.

Ko, Bong Jun, et al.. (2012). Adaptive algorithms for diagnosing large-scale failures in computer networks. 1–12. 9 indexed citations

16.

Sheng, Zhengguo, Bong Jun Ko, & Kin K. Leung. (2012). Power Efficient Decode-and-Forward Cooperative Relaying. IEEE Wireless Communications Letters. 1(5). 444–447. 9 indexed citations

17.

Ko, Bong Jun, et al.. (2011). netCSI: A Generic Fault Diagnosis Algorithm for Large-Scale Failures in Computer Networks. 167–176. 5 indexed citations

18.

Zafer, Murtaza, Bong Jun Ko, & Ivan Wang‐Hei Ho. (2010). Transmit Power Estimation Using Spatially Diverse Measurements Under Wireless Fading. IEEE/ACM Transactions on Networking. 18(4). 1171–1180. 19 indexed citations

19.

Ho, Ivan Wang‐Hei, Bong Jun Ko, Murtaza Zafer, Chatschik Bisdikian, & Kin K. Leung. (2008). Cooperative Transmit-Power Estimation in MANETs. 2241–2246. 10 indexed citations

20.

He, Ting, et al.. (2008). Accuracy analysis of data aggregation for network monitoring. 1–7. 4 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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