L. Jeff Hong
- Management Science and Operations Research top 0.2%
- Computational Theory and Mathematics top 1%
- Statistics, Probability and Uncertainty top 0.5%
- Statistics and Probability top 1%
- Artificial Intelligence top 5%
- Co-authors
- Barry L. NelsonZhaolin HuGuangwu LiuJie XuLiwei ZhangJun LuoYi YangKuo-Hao Chang
- Topics
- Simulation Techniques and Applications (53 papers)Advanced Multi-Objective Optimization Algorithms (26 papers)Risk and Portfolio Optimization (20 papers)
- Partner nations
- Hong KongChinaUnited States
In The Last Decade
L. Jeff Hong
93 papers receiving 2.2k citations
Peers
Comparison fields: 5 of 98
- Management Science and Operations Research 1.5k
- Computational Theory and Mathematics 543
- Statistics, Probability and Uncertainty 400
- Statistics and Probability 319
- Artificial Intelligence 297
Countries citing papers authored by L. Jeff Hong
This map shows the geographic impact of L. Jeff Hong'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 L. Jeff Hong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites L. Jeff Hong more than expected).
Fields of papers citing papers by L. Jeff Hong
This network shows the impact of papers produced by L. Jeff Hong. 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 L. Jeff Hong. The network helps show where L. Jeff Hong may publish in the future.
Co-authorship network of co-authors of L. Jeff Hong
This figure shows the co-authorship network connecting the top 25 collaborators of L. Jeff Hong. A scholar is included among the top collaborators of L. Jeff Hong 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 L. Jeff Hong. L. Jeff Hong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 12 | |
| 4 | 14 | |
| 5 | 2 | |
| 6 | 6 | |
| 7 | 12 | |
| 8 | 3 | |
| 9 | 29 | |
| 10 | 0 | |
| 11 | 1 | |
| 12 | 1 | |
| 13 | 0 | |
| 14 | 10 | |
| 15 | 6 | |
| 16 | Fighting Strategies in a Market with Counterfeits | 2 |
| 17 | 9 | |
| 18 | 13 | |
| 19 | 1 | |
| 20 | 5 |
About L. Jeff Hong
L. Jeff Hong is a scholar working on Management Science and Operations Research, Statistics, Probability and Uncertainty and Statistics and Probability, having authored 103 papers that have together received 2.3k indexed citations. Recurring topics across this work include Simulation Techniques and Applications (53 papers), Advanced Multi-Objective Optimization Algorithms (26 papers) and Risk and Portfolio Optimization (20 papers). The work is most often cited by research in Management Science and Operations Research (1.5k citations), Statistics, Probability and Uncertainty (400 citations) and Software (149 citations). L. Jeff Hong has collaborated with scholars based in Hong Kong, China and United States. Frequent co-authors include Barry L. Nelson, Zhaolin Hu, Guangwu Liu, Jie Xu, Liwei Zhang, Jun Luo, Yi Yang, Kuo-Hao Chang, Weiwei Fan and Hong Wan. Their work appears in journals such as Management Science, European Journal of Operational Research and Operations Research.
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.