Hyon‐Jung Kim
- Computational Mathematics top 10%
- Tensor decomposition and applications 5
- Statistics and Probability top 5%
- Statistical Methods and Inference 3
- Advanced Statistical Methods and Models 2
- Economics and Econometrics top 5%
- Housing Market and Economics 2
- Spatial and Panel Data Analysis 2
- Environmental Engineering top 10%
- Soil Geostatistics and Mapping 3
- Transportation top 10%
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- Sparse and Compressive Sensing Techniques 6
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- Blind Source Separation Techniques 5
- Co-authors
- Alan E. GelfandSudipto BanerjeeC. F. SirmansJohn M. ClappEsa OllilaErkki TomppoVisa KoivunenV. Koivunen
- Journals
- Journal of the American Statistical Association (1 paper)Remote Sensing of Environment (1 paper)IEEE Transactions on Signal Processing (1 paper)
- Partner nations
- FinlandUnited StatesBelgium
In The Last Decade
Hyon‐Jung Kim
14 papers receiving 559 citations
Peers
Comparison fields: 5 of 95
- Computational Mathematics 12
- Statistics and Probability 102
- Economics and Econometrics 289
- Environmental Engineering 136
- Transportation 31
Countries citing papers authored by Hyon‐Jung Kim
This map shows the geographic impact of Hyon‐Jung 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 Hyon‐Jung Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hyon‐Jung Kim more than expected).
Fields of papers citing papers by Hyon‐Jung Kim
This network shows the impact of papers produced by Hyon‐Jung 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 Hyon‐Jung Kim. The network helps show where Hyon‐Jung Kim may publish in the future.
Co-authorship network
The 15 scholars most cited alongside Hyon‐Jung Kim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 0 | |
| 2 | 2015 | 9 | |
| 3 | 2014 | 3 | |
| 4 | 2014 | 10 | |
| 5 | Robust iteratively reweighted LASSO estimation for sparse tensor factorizations | 2014 | 1 |
| 6 | 2013 | 7 | |
| 7 | 2013 | 7 | |
| 8 | 2011 | 4 | |
| 9 | 2010 | 17 | |
| 10 | 2008 | 24 | |
| 11 | 2006 | 35 | |
| 12 | Dynamic Analysis of Tunnel Structures Considering Soil-Structure Interaction | 2005 | 0 |
| 13 | 2004 | 6 | |
| 14 | 2003 | 403 | |
| 15 | 2002 | 59 | |
| 16 | 2001 | 7 |
About Hyon‐Jung Kim
Hyon‐Jung Kim is a scholar working on Computational Mathematics, General Engineering and Signal Processing, having authored 16 papers that have together received 592 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (6 papers), Tensor decomposition and applications (5 papers), Blind Source Separation Techniques (5 papers), Statistical Methods and Inference (3 papers), Soil Geostatistics and Mapping (3 papers), Advanced Statistical Methods and Models (2 papers), Housing Market and Economics (2 papers) and Spatial and Panel Data Analysis (2 papers). The work is most often cited by research in Computational Mathematics (12 citations), Statistics and Probability (102 citations) and Economics and Econometrics (289 citations). Hyon‐Jung Kim has collaborated with scholars based in Finland, United States and Belgium. Frequent co-authors include Alan E. Gelfand, Sudipto Banerjee, C. F. Sirmans, John M. Clapp, Esa Ollila, Erkki Tomppo, Visa Koivunen, V. Koivunen, Karri Seppä and Timo Hakulinen. Their work appears in journals such as Journal of the American Statistical Association, Remote Sensing of Environment and IEEE Transactions on Signal Processing.
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.