Michael Jong Kim

567 total citations
23 papers, 337 citations indexed

About

Michael Jong Kim is a scholar working on Safety, Risk, Reliability and Quality, Management Science and Operations Research and Statistics, Probability and Uncertainty. According to data from OpenAlex, Michael Jong Kim has authored 23 papers receiving a total of 337 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Safety, Risk, Reliability and Quality, 11 papers in Management Science and Operations Research and 8 papers in Statistics, Probability and Uncertainty. Recurrent topics in Michael Jong Kim's work include Reliability and Maintenance Optimization (10 papers), Advanced Bandit Algorithms Research (6 papers) and Software Reliability and Analysis Research (5 papers). Michael Jong Kim is often cited by papers focused on Reliability and Maintenance Optimization (10 papers), Advanced Bandit Algorithms Research (6 papers) and Software Reliability and Analysis Research (5 papers). Michael Jong Kim collaborates with scholars based in Canada, Singapore and Japan. Michael Jong Kim's co-authors include Viliam Makiš, Andrew E. B. Lim, Rui Jiang, Chi-Guhn Lee, Jun‐ya Gotoh, Rui Jiang, Dragan Banjević, Roy H. Kwon, Jussi Keppo and Lin Chen and has published in prestigious journals such as IEEE Transactions on Automatic Control, Management Science and European Journal of Operational Research.

In The Last Decade

Michael Jong Kim

21 papers receiving 317 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael Jong Kim Canada 11 180 113 86 78 59 23 337
Ruey-Huei Yeh Taiwan 11 109 0.6× 105 0.9× 44 0.5× 114 1.5× 50 0.8× 18 371
Hamid Reza Golmakani Iran 11 224 1.2× 79 0.7× 251 2.9× 90 1.2× 101 1.7× 23 562
Kyungmee O. Kim South Korea 12 259 1.4× 188 1.7× 54 0.6× 51 0.7× 97 1.6× 30 425
Nasser Fard United States 12 234 1.3× 143 1.3× 41 0.5× 35 0.4× 86 1.5× 36 403
Monica Rani India 10 227 1.3× 128 1.1× 163 1.9× 126 1.6× 97 1.6× 16 444
Karim Atashgar Iran 9 182 1.0× 153 1.4× 27 0.3× 153 2.0× 27 0.5× 28 363
Martin Wortman United States 11 221 1.2× 120 1.1× 41 0.5× 52 0.7× 81 1.4× 29 481
F. G. Badía Spain 11 321 1.8× 159 1.4× 74 0.9× 24 0.3× 157 2.7× 45 491
Cai Wen Zhang China 12 110 0.6× 235 2.1× 65 0.8× 77 1.0× 24 0.4× 16 452
Jalal Safari Iran 5 300 1.7× 172 1.5× 39 0.5× 29 0.4× 184 3.1× 8 414

Countries citing papers authored by Michael Jong Kim

Since Specialization
Citations

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

Fields of papers citing papers by Michael Jong Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Jong Kim. 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 Michael Jong Kim. The network helps show where Michael Jong Kim may publish in the future.

Co-authorship network of co-authors of Michael Jong Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Jong Kim. A scholar is included among the top collaborators of Michael Jong Kim 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 Michael Jong Kim. Michael Jong Kim 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.
Kim, Michael Jong, et al.. (2023). Bayesian Inventory Control: Accelerated Demand Learning via Exploration Boosts. Operations Research. 71(5). 1515–1529.
2.
Gotoh, Jun‐ya, Michael Jong Kim, & Andrew E. B. Lim. (2023). Technical Note—A Data-Driven Approach to Beating SAA Out of Sample. Operations Research. 73(2). 829–841. 4 indexed citations
3.
Keppo, Jussi, et al.. (2022). Learning Manipulation Through Information Dissemination. Operations Research. 70(6). 3490–3510. 4 indexed citations
4.
Kim, Michael Jong, et al.. (2021). Optimal Control of Partially Observable Semi-Markovian Failing Systems: An Analysis Using a Phase Methodology. Operations Research. 69(4). 1282–1304. 10 indexed citations
5.
Kim, Michael Jong. (2020). Variance Regularization in Sequential Bayesian Optimization. Mathematics of Operations Research. 45(3). 966–992. 6 indexed citations
6.
Huh, Woonghee Tim, et al.. (2019). Dithering for Learning: Computationally Efficient Policies for Dynamic Pricing in High Dimensions. SSRN Electronic Journal. 1 indexed citations
7.
Banjević, Dragan & Michael Jong Kim. (2019). Thompson Sampling for Stochastic Control: The Continuous Parameter Case. IEEE Transactions on Automatic Control. 64(10). 4137–4152. 5 indexed citations
8.
Gotoh, Jun‐ya, Michael Jong Kim, & Andrew E. B. Lim. (2018). Robust empirical optimization is almost the same as mean–variance optimization. Operations Research Letters. 46(4). 448–452. 42 indexed citations
9.
Kim, Michael Jong. (2017). Thompson Sampling for Stochastic Control: The Finite Parameter Case. IEEE Transactions on Automatic Control. 62(12). 6415–6422. 12 indexed citations
10.
Gotoh, Jun‐ya, Michael Jong Kim, & Andrew E. B. Lim. (2017). Robust Empirical Optimization is Almost the Same as Mean-Variance Optimization. SSRN Electronic Journal. 8 indexed citations
11.
Kim, Michael Jong. (2016). Robust Control of Partially Observable Failing Systems. Operations Research. 64(4). 999–1014. 15 indexed citations
12.
Kim, Michael Jong & Andrew E. B. Lim. (2015). Robust Multiarmed Bandit Problems. Management Science. 62(1). 264–285. 30 indexed citations
13.
Kim, Michael Jong & Viliam Makiš. (2013). Joint Optimization of Sampling and Control of Partially Observable Failing Systems. Operations Research. 61(3). 777–790. 1 indexed citations
14.
Chen, Lin, et al.. (2013). A Stochastic Model for Highway Accident Predictions with Winter Data. 5(1). 6–13. 1 indexed citations
15.
Kim, Michael Jong, et al.. (2012). ‘Golomb-like’ nested recursions with Beatty function solutions. The Journal of Difference Equations and Applications. 19(3). 372–383. 1 indexed citations
16.
Jiang, Rui, Michael Jong Kim, & Viliam Makiš. (2012). Maximum Likelihood Estimation for a Hidden Semi‐Markov Model with Multivariate Observations. Quality and Reliability Engineering International. 28(7). 783–791. 15 indexed citations
17.
Kim, Michael Jong, et al.. (2012). A moment approach to bounding exotic options under regime switching. Optimization. 61(10). 1253–1269. 4 indexed citations
18.
Kim, Michael Jong, Rui Jiang, Viliam Makiš, & Chi-Guhn Lee. (2011). Optimal Bayesian fault prediction scheme for a partially observable system subject to random failure. European Journal of Operational Research. 214(2). 331–339. 71 indexed citations
19.
Jiang, Rui, Michael Jong Kim, & Viliam Makiš. (2011). A Bayesian model and numerical algorithm for CBM availability maximization. Annals of Operations Research. 196(1). 333–348. 10 indexed citations
20.
Kim, Michael Jong, Viliam Makiš, & Rui Jiang. (2010). Parameter estimation in a condition-based maintenance model. Statistics & Probability Letters. 80(21-22). 1633–1639. 14 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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