Jack Xin
Impact in
- Numerical Analysis top 1%
- Differential Equations and Numerical Methods
- Modeling and Simulation top 1%
- Mathematical Biology Tumor Growth
Papers in
-
- Sparse and Compressive Sensing Techniques 30
- Fluid Dynamics and Turbulent Flows 16
-
- Advanced Neural Network Applications 13
- Co-authors
- Yifei Lou (12 shared papers)Penghang Yin (20 shared papers)James Nolen (10 shared papers)Stanley Osher (11 shared papers)Qi He (4 shared papers)Ernie Esser (4 shared papers)Yingyong Qi (30 shared papers)Yifeng Yu (16 shared papers)
- Journals
- Communications in Mathematical Sciences (12 papers)Physica D Nonlinear Phenomena (8 papers)Journal of Scientific Computing (7 papers)Communications in Mathematical Physics (7 papers)SIAM Journal on Imaging Sciences (6 papers)
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
Jack Xin
165 papers receiving 3.1k citations
Jack Xin's Hit Papers
Peers
Comparison fields: 5 of 115
- Numerical Analysis 503
- Modeling and Simulation 332
- Computational Mechanics 1.2k
- Mathematical Physics 437
- Applied Mathematics 387
Countries citing papers authored by Jack Xin
This map shows the geographic impact of Jack Xin'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 Jack Xin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jack Xin more than expected).
Fields of papers citing papers by Jack Xin
This network shows the impact of papers produced by Jack Xin. 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 Jack Xin. The network helps show where Jack Xin may publish in the future.
Co-authors
The 25 scholars most cited alongside Jack Xin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 176 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2000 | 390 | |
| 2 | Minimization of $\ell_{1-2}$ for Compressed Sensing Hit paper breakdown → | 2015 | 301 |
| 3 | 2015 | 145 | |
| 4 | 2014 | 128 | |
| 5 | 2012 | 123 | |
| 6 | 2013 | 118 | |
| 7 | 1992 | 100 | |
| 8 | 1993 | 86 | |
| 9 | 2005 | 77 | |
| 10 | 2018 | 75 | |
| 11 | 2000 | 68 | |
| 12 | 2017 | 66 | |
| 13 | 1999 | 65 | |
| 14 | 2005 | 62 | |
| 15 | 2019 | 58 | |
| 16 | 2009 | 54 | |
| 17 | 2014 | 51 | |
| 18 | 2017 | 48 | |
| 19 | 2015 | 45 | |
| 20 | 2019 | 42 |
About Jack Xin
Jack Xin is a scholar working on Computational Mechanics, Computer Vision and Pattern Recognition, Signal Processing, Mathematical Physics and Artificial Intelligence, having authored 176 papers that have together received 3.4k indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (30 papers), Advanced Mathematical Modeling in Engineering (22 papers), Blind Source Separation Techniques (21 papers), Speech and Audio Processing (21 papers), Fluid Dynamics and Turbulent Flows (16 papers), Advanced Neural Network Applications (13 papers), Mathematical Biology Tumor Growth (13 papers) and Domain Adaptation and Few-Shot Learning (12 papers). The work is most often cited by research in Numerical Analysis (503 citations), Modeling and Simulation (332 citations), Computational Mechanics (1.2k citations), Mathematical Physics (437 citations) and Applied Mathematics (387 citations). Jack Xin has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Yifei Lou, Penghang Yin, James Nolen, Stanley Osher, Qi He, Ernie Esser, Yingyong Qi, Yifeng Yu, Tieyong Zeng and Fen Lin. Their work appears in journals such as Communications in Mathematical Sciences, Physica D Nonlinear Phenomena, Journal of Scientific Computing, Communications in Mathematical Physics and SIAM Journal on Imaging Sciences.
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.