Jack Xin

5.2k total citations
162 papers, 3.1k citations indexed

About

Jack Xin is a scholar working on Computational Mechanics, Signal Processing and Mathematical Physics. According to data from OpenAlex, Jack Xin has authored 162 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Computational Mechanics, 31 papers in Signal Processing and 30 papers in Mathematical Physics. Recurrent topics in Jack Xin's work include Sparse and Compressive Sensing Techniques (28 papers), Blind Source Separation Techniques (20 papers) and Advanced Mathematical Modeling in Engineering (20 papers). Jack Xin is often cited by papers focused on Sparse and Compressive Sensing Techniques (28 papers), Blind Source Separation Techniques (20 papers) and Advanced Mathematical Modeling in Engineering (20 papers). Jack Xin collaborates with scholars based in United States, China and Hong Kong. Jack Xin's co-authors include Yifei Lou, Penghang Yin, James Nolen, Qi He, Stanley Osher, Ernie Esser, Yingyong Qi, Yifeng Yu, Tieyong Zeng and Fen Lin and has published in prestigious journals such as Physical Review Letters, Journal of Computational Physics and IEEE Transactions on Image Processing.

In The Last Decade

Jack Xin

146 papers receiving 2.8k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jack Xin United States	28	1.1k	581	579	490	414	162	3.1k
Felipe Cucker Hong Kong	25	919 0.8×	663 1.1×	414 0.7×	418 0.9×	583 1.4×	109	5.2k
Massimo Fornasier Germany	27	1.4k 1.2×	872 1.5×	160 0.3×	139 0.3×	370 0.9×	74	3.2k
Konstantin Mischaikow United States	38	571 0.5×	482 0.8×	1.1k 1.9×	255 0.5×	1.1k 2.6×	138	4.9k
Chris Budd United Kingdom	30	717 0.6×	105 0.2×	221 0.4×	537 1.1×	403 1.0×	138	4.4k
Lokenath Debnath United States	32	586 0.5×	554 1.0×	100 0.2×	906 1.8×	404 1.0×	226	5.8k
George Psihoyios Germany	20	756 0.7×	112 0.2×	116 0.2×	1.1k 2.2×	160 0.4×	866	3.3k
Yong Xu China	38	355 0.3×	119 0.2×	362 0.6×	160 0.3×	206 0.5×	262	5.0k
Tryphon T. Georgiou United States	42	464 0.4×	301 0.5×	40 0.1×	492 1.0×	266 0.6×	225	5.3k
Ch. Tsitouras Greece	33	1.1k 1.0×	116 0.2×	136 0.2×	2.3k 4.7×	175 0.4×	933	4.8k
Ting‐Zhu Huang China	51	2.6k 2.3×	4.7k 8.1×	144 0.2×	1.0k 2.1×	213 0.5×	568	9.6k

Countries citing papers authored by Jack Xin

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Jack Xin

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Xin, Jack, et al.. (2024). Existence of an Effective Burning Velocity in a Cellular Flow for the Curvature G-Equation Proved Using a Game Analysis. Journal of Geometric Analysis. 34(3). 4 indexed citations

Lou, Yifei, et al.. (2023). Difference of anisotropic and isotropic TV for segmentation under blur and Poisson noise. Frontiers in Computer Science. 5. 1 indexed citations

Yue, Meng, et al.. (2022). Post-Fault Power Grid Voltage Prediction via 1D-CNN with Spatial Coupling. 35–37. 1 indexed citations

Zhang, Shuai, et al.. (2021). Structured Sparsity of Convolutional Neural Networks via Nonconvex Sparse Group Regularization. Frontiers in Applied Mathematics and Statistics. 6. 10 indexed citations

Wang, Zhongjian, Jack Xin, & Zhiwen Zhang. (2021). Sharp Error Estimates on a Stochastic Structure-Preserving Scheme in Computing Effective Diffusivity of 3D Chaotic Flows. Multiscale Modeling and Simulation. 19(3). 1167–1189. 7 indexed citations

Wang, Zhongjian, Jack Xin, & Zhiwen Zhang. (2021). DeepParticle: Learning Invariant Measure by a Deep Neural Network Minimizing Wasserstein Distance on Data Generated from an Interacting Particle Method. SSRN Electronic Journal.

Yin, Penghang, et al.. (2021). Learning quantized neural nets by coarse gradient method for nonlinear classification. Research in the Mathematical Sciences. 8(3). 1 indexed citations

Wang, Zhongjian, Jack Xin, & Zhiwen Zhang. (2018). Sharp uniform in time error estimate on a stochastic structure-preserving Lagrangian method and computation of effective diffusivity in 3D chaotic flows. arXiv (Cornell University). 1 indexed citations

Zhang, Shuai & Jack Xin. (2017). Minimization of transformed $l_1$ penalty: Closed form representation and iterative thresholding algorithms. Communications in Mathematical Sciences. 15(2). 511–537. 44 indexed citations

10.

Yin, Penghang, et al.. (2016). Training Ternary Neural Networks with Exact Proximal Operator.. arXiv (Cornell University). 1 indexed citations

11.

Warren, Steve, Punit Prakash, David E. Thompson, et al.. (2016). Design projects motivated and informed by the needs of severely disabled autistic children. PubMed. 63. 3015–3018. 1 indexed citations

12.

Yin, Penghang, Yifei Lou, Qi He, & Jack Xin. (2015). Minimization of $\ell_{1-2}$ for Compressed Sensing. SIAM Journal on Scientific Computing. 37(1). A536–A563. 276 indexed citations

13.

Xin, Jack & Yifeng Yu. (2014). Asymptotic Growth Rates and Strong Bending of Turbulent Flame Speeds of G-Equation in Steady Two-Dimensional Incompressible Periodic Flows. SIAM Journal on Mathematical Analysis. 46(4). 2444–2467. 8 indexed citations

14.

Nolen, James & Jack Xin. (2008). Computing reactive front speeds in random flows by variational principle. Physica D Nonlinear Phenomena. 237(23). 3172–3177. 6 indexed citations

15.

Nolen, James & Jack Xin. (2008). Asymptotic spreading of KPP reactive fronts in incompressible space–time random flows. Annales de l Institut Henri Poincaré C Analyse Non Linéaire. 26(3). 815–839. 32 indexed citations

16.

Lin, Fen & Jack Xin. (1999). On the Incompressible Fluid Limit and the Vortex Motion Law of the Nonlinear Schrödinger Equation. Communications in Mathematical Physics. 200(2). 249–274. 60 indexed citations

17.

Xin, Jack. (1997). Stability of Traveling Waves of a Solute Transport Equation. Journal of Differential Equations. 135(2). 269–298. 5 indexed citations

18.

Collet, Pierre & Jack Xin. (1996). Global existence and large time asymptotic bounds of $L^\infty $ solutions of thermal diffusive combustion systems on $\mathbb {R}^n$. French digital mathematics library (Numdam). 23(4). 625–642. 16 indexed citations

19.

Xin, Jack, Anthony Peirce, John Chadam, & P. Ortoleva. (1995). Reactive flows in layered porous media, I. Homogenization of free boundary problems. Asymptotic Analysis. 11(1). 31–54.

20.

Berlyand, Leonid & Jack Xin. (1995). Large time asymptotics of solutions to a model combustion system with critical nonlinearity. Nonlinearity. 8(2). 161–178. 8 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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