Junbo Son

437 total citations
19 papers, 332 citations indexed

About

Junbo Son is a scholar working on Safety, Risk, Reliability and Quality, Automotive Engineering and Control and Systems Engineering. According to data from OpenAlex, Junbo Son has authored 19 papers receiving a total of 332 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Safety, Risk, Reliability and Quality, 6 papers in Automotive Engineering and 6 papers in Control and Systems Engineering. Recurrent topics in Junbo Son's work include Reliability and Maintenance Optimization (7 papers), Advanced Battery Technologies Research (4 papers) and Machine Fault Diagnosis Techniques (4 papers). Junbo Son is often cited by papers focused on Reliability and Maintenance Optimization (7 papers), Advanced Battery Technologies Research (4 papers) and Machine Fault Diagnosis Techniques (4 papers). Junbo Son collaborates with scholars based in United States, China and Hong Kong. Junbo Son's co-authors include Shiyu Zhou, Yilu Zhang, Chaitanya Sankavaram, Mutasim Salman, Qiang Zhou, Xiaofeng Mao, Xinyu Du, Patrícia Flatley Brennan, Raed Al Kontar and Guanyi Lu and has published in prestigious journals such as Cancer Research, MIS Quarterly and Statistics in Medicine.

In The Last Decade

Junbo Son

18 papers receiving 324 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Junbo Son United States 8 165 144 74 52 44 19 332
Liudong Gu China 10 170 1.0× 180 1.3× 71 1.0× 95 1.8× 52 1.2× 18 393
Dangbo Du China 10 276 1.7× 243 1.7× 62 0.8× 106 2.0× 81 1.8× 25 455
Fangfang Ding Canada 6 390 2.4× 324 2.3× 37 0.5× 67 1.3× 87 2.0× 7 557
Ingeborg de Pater Netherlands 8 164 1.0× 194 1.3× 21 0.3× 45 0.9× 51 1.2× 11 329
Rajiv Nandan India 10 139 0.8× 96 0.7× 13 0.2× 109 2.1× 67 1.5× 40 370
Xuewen Miao China 5 97 0.6× 146 1.0× 26 0.4× 51 1.0× 37 0.8× 7 308
Nooshin Yousefi United States 8 172 1.0× 76 0.5× 30 0.4× 13 0.3× 87 2.0× 14 262
Gaoyang Li China 6 130 0.8× 137 1.0× 18 0.2× 47 0.9× 43 1.0× 9 346
Ranganath Kothamasu United States 6 181 1.1× 310 2.2× 17 0.2× 113 2.2× 69 1.6× 6 503
Wenbiao Zhao China 10 300 1.8× 98 0.7× 27 0.4× 48 0.9× 171 3.9× 22 464

Countries citing papers authored by Junbo Son

Since Specialization
Citations

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

Fields of papers citing papers by Junbo Son

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junbo Son

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

All Works

19 of 19 papers shown
1.
Zhao, Zihao, et al.. (2025). A Semi-Supervised Nonlinear Approach for Health Assessment with Prognostic Accuracy Integration. Asia Pacific Journal of Operational Research. 42(6).
2.
3.
Son, Junbo, et al.. (2023). A Hybrid Deep Generative Network for Pore Morphology Prediction in Metal Additive Manufacturing. Journal of Manufacturing Science and Engineering. 145(7). 3 indexed citations
4.
5.
Wen, Yuxin, et al.. (2022). A neural-network-based proportional hazard model for IoT signal fusion and failure prediction. IISE Transactions. 55(4). 377–391. 5 indexed citations
6.
Lu, Guanyi, et al.. (2021). Product variety in local grocery stores: Differential effects on stock‐keeping unit level sales. Journal of Operations Management. 68(1). 33–54. 8 indexed citations
7.
Son, Junbo, Yeongin Kim, & Shiyu Zhou. (2021). Alerting patients via health information system considering trust-dependent patient adherence. Information Technology and Management. 23(4). 245–269. 3 indexed citations
8.
Son, Junbo, Yeongin Kim, & Shiyu Zhou. (2020). Recommending Clinical Interventions to Patients Via Iot-Enabled Health Information System Considering Trust-Dependent Patient Adherence. SSRN Electronic Journal. 1 indexed citations
9.
Son, Junbo, Patrícia Flatley Brennan, & Shiyu Zhou. (2020). A Data Analytics Framework for Smart Asthma Management Based on Remote Health Information Systems with Bluetooth-Enabled Personal Inhalers. MIS Quarterly. 44(1). 285–304. 24 indexed citations
10.
Lee, Jaesung, Junbo Son, Shiyu Zhou, & Yong Chen. (2020). Variation Source Identification in Manufacturing Processes Using Bayesian Approach With Sparse Variance Components Prior. IEEE Transactions on Automation Science and Engineering. 1–17. 9 indexed citations
11.
Son, Junbo, Patrícia Flatley Brennan, & Shiyu Zhou. (2017). Correlated gamma‐based hidden Markov model for the smart asthma management based on rescue inhaler usage. Statistics in Medicine. 36(10). 1619–1637. 3 indexed citations
12.
Son, Junbo, Shiyu Zhou, Chaitanya Sankavaram, Xinyu Du, & Yilu Zhang. (2016). Remaining useful life prediction based on noisy condition monitoring signals using constrained Kalman filter. Reliability Engineering & System Safety. 152. 38–50. 73 indexed citations
13.
Leystra, Alyssa A., Junbo Son, Christopher D. Zahm, et al.. (2016). Abstract 2381: A multiancestral model of colorectal cancer: in vivo evidence that early heterogeneity contributes to cancer progression. Cancer Research. 76(14_Supplement). 2381–2381. 1 indexed citations
14.
Kontar, Raed Al, Junbo Son, Shiyu Zhou, et al.. (2016). Remaining useful life prediction based on the mixed effects model with mixture prior distribution. IISE Transactions. 49(7). 682–697. 26 indexed citations
15.
Son, Junbo, Qiang Zhou, Shiyu Zhou, & Mutasim Salman. (2015). Prediction of the failure interval with maximum power based on the remaining useful life distribution. IIE Transactions. 47(10). 1072–1087. 5 indexed citations
16.
Son, Junbo, Patrícia Flatley Brennan, & Shiyu Zhou. (2015). Rescue inhaler usage prediction in smart asthma management systems using joint mixed effects logistic regression model. IIE Transactions. 48(4). 333–346. 2 indexed citations
17.
Zhou, Qiang, Junbo Son, Shiyu Zhou, Xiaofeng Mao, & Mutasim Salman. (2014). Remaining useful life prediction of individual units subject to hard failure. IIE Transactions. 46(10). 1017–1030. 76 indexed citations
18.
Son, Junbo, Yilu Zhang, Chaitanya Sankavaram, & Shiyu Zhou. (2014). RUL Prediction for Individual Units Based on Condition Monitoring Signals With a Change Point. IEEE Transactions on Reliability. 64(1). 182–196. 44 indexed citations
19.
Son, Junbo, Qiang Zhou, Shiyu Zhou, Xiaofeng Mao, & Mutasim Salman. (2013). Evaluation and Comparison of Mixed Effects Model Based Prognosis for Hard Failure. IEEE Transactions on Reliability. 62(2). 379–394. 41 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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