Jack Xin

Chancellor’s Professor, University of California, Irvine

Biography

Jack Xin is a Chancellor’s Professor in the Department of Mathematics at the University of California, Irvine. He completed his Ph.D. in Mathematics at the Courant Institute of New York University in 1990, after earning his B.S. in Mathematics from Peking University in 1985. Before joining UC Irvine in 2005, Xin held faculty positions at the University of Texas at Austin and the University of Arizona. He has been a Chancellor’s Professor at UC Irvine since 2019.

Xin's research focuses on analysis and computational methods with applications in physical and data sciences. He has published extensively in journals such as the SIAM Journal on Mathematical Analysis and the Journal of Computational Physics. His research has been continuously funded by the National Science Foundation (NSF), with grants supporting projects on algorithms and mathematical studies for applications in deep neural networks, among others. Xin has received multiple recognitions, including being named a Fellow of the American Association for the Advancement of Science in 2020 and a Fellow of the Society for Industrial and Applied Mathematics in 2021.

At UC Irvine, Xin teaches both undergraduate and graduate courses in applied mathematics. He has supervised numerous doctoral students who have gone on to careers in academia and industry. Xin has also contributed to the mathematical community through various service roles, such as serving on editorial boards for journals like Multiscale Modeling and Simulation and organizing conferences to promote advances in applied mathematics. Additionally, he has been actively involved in educational outreach programs, such as directing iCAMP to mentor undergraduate students in computational mathematics.

Education

PhD in Mathematics, Courant Institute, New York University, 1990
MS in Mathematics, Courant Institute, New York University, 1988
BS in Mathematics, Peking University, 1985

Distinctions

Fellow of Asia-Pacific Artificial Intelligence Association, 2024
Qualcomm Gift Award, 2023-2024
Qualcomm Faculty Award, 2018-2020
Qualcomm Faculty Award, 2020
Qualcomm Faculty Award, 2022
Fellow of the Society for Industrial and Applied Mathematics, 2021
Fellow of the American Association for the Advancement of Science, 2020

Areas of Expertise

Mathematics and Computational Methods
Deep Learning Algorithms
Reaction-Diffusion Systems
Applied Mathematics in Physical Sciences
Nonlinear Dynamics and Waves
Data Science and Signal Processing
Machine Learning Applications
Graph Neural Networks
Turbulent Combustion Modeling
Statistical Learning and Optimization

Recent Publications

H. Gao, Z. Long, J. Xin, Y. Yu, “Existence of an effective burning velocity in a cellular flow for the curvature G-equation proved using a game analysis” (opens in new tab), Journal of Geometric Analysis, vol. 34, no. 3, pp. 81, 2024.
K. Bui, Y. Lou, F. Park, J. Xin, “An Efficient Smoothing and Thresholding Image Segmentation Framework with Weighted Anisotropic-Isotropic Total Variation” (opens in new tab), Comm. on Applied Math and Computation, vol. 34, no. 3, 2024.
Z. Wang, J. Xin, Z. Zhang, “A DeepParticle method for learning and generating aggregation patterns in multi-dimensional Keller-Segel chemotaxis systems” (opens in new tab), Physica D, vol. 460, pp. 134082, 2024.
J. Xin, Y. Yu, P. Ronney, “Lagrangian, Game Theoretic and PDE Methods for Averaging G-equations in Turbulent Combustion: Existence and Beyond” (opens in new tab), Bulletin of Amer. Math Soc., vol. 61, no. 3, pp. 470-514, 2024.
X. Dai, M. Hu, J. A. Zhou, “An Augmented Subspace Based Adaptive Proper Orthogonal Decomposition Method for Time Dependent Partial Differential Equations” (opens in new tab), J. Computational Physics, pp. 113231, 2024.
H. Mitake, C. Mooney, H. Tran, J. Xin, Y. Yu, “Bifurcation of homogenization and nonhomogenization of the curvature G-equation with shear flows” (opens in new tab), Mathematische Annalen, 2024.
E. Dayag, K. Bui, F. Park, J. Xin, “An Image Segmentation Model with Transformed Total Variation” (opens in new tab), 2024. Presented at European Signal Processing Conference, Aug, 2024.
N. T. V. Tran, J. Xin, G. Zhou, “FWin transformer for dengue prediction under climate and ocean influence”, 2024. Presented at International Conference on Machine Learning, Optimization, and Data Science, Sept, 2024.
Y. Zheng, Z. Xu, F. Xue, B. Yang, J. Lyu, S. Zhang, Y. Qi, J. Xin, “AFIDAF: Alternating Fourier and Image Domain Adaptive Filters as an Efficient Alternative to Attention in ViTs” (opens in new tab), 2024. Presented at International Symposium of Visual Computing, 2024.
Y. Liu, J. Xin, “Synchronized Front Propagation and Delayed Flame Quenching in Strain G-equation and Time-Periodic Cellular Flows”, Minimax Theory and its Applications, vol. 8, no. 1, pp. 109-119, 2023.
Z. Long, P. Yin, J. Xin, “Recurrence of Optimum for Training Weight and Activation Quantized Networks” (opens in new tab), Applied and Computational Harmonic Analysis, vol. 62, pp. 41-65, 2023.
K. Bui, Y. Lou, F. Park, J. Xin, “Difference of Anisotropic and Isotropic TV for Segmentation under Blur and Poisson Noise” (opens in new tab), Frontiers in Computer Science, vol. 5, pp. 1131317, 2023.
Z. Li, B. Yang, P. Yin, Y. Qi, J. Xin, “Feature Affinity Assisted Knowledge Distillation and Quantization of Deep Neural Networks on Label-Free Data” (opens in new tab), IEEE Access, vol. 11, pp. 78042-78051, 2023.
W. Whiting, B. Wang, J. Xin, “Convergence of Hyperbolic Neural Networks under Riemannian Stochastic Gradient Descent” (opens in new tab), Comm. on Applied Math and Computation, 2023.
K. Bui, F. Xue, F. Park, Y. Qi, J. Xin, “A Proximal Algorithm for Network Slimming” (opens in new tab), 2023. Presented at 9th International Conference on Machine Learning, Optimization and Data Science, Sept, 2023.
K. Bui, Y. Lou, F. Park, J. Xin, “Weighted Anisotropic-Isotropic Total Variation for Poisson Denoising” (opens in new tab), pp. 1020-1024, 2023. Presented at IEEE International Conference on Image Processing (ICIP), 2023.
Y. Sun, J. Xin, “Lorentzian Peak Sharpening and Sparse Blind Source Separation for NMR Spectroscopy” (opens in new tab), Signal, Image & Video Processing, vol. 16, no. 3, pp. 633-641, 2022.
Y. Sun, K. Huang, J. Xin, “Structure Assisted NMF Methods for Separation of Degenerate Mixture Data with Application to NMR Spectroscopy”, International Journal of Mathematics and Computation, vol. 33, no. 1, 2022.
C. Kao, Y. Liu, J. Xin, “A Semi-Lagrangian Computation of Front Speeds of G-equation in ABC and Kolmogorov Flows with Estimation via Ballistic Orbits” (opens in new tab), SIAM Interdisciplinary J. Multiscale Modeling & Simulation, vol. 20, no. 1, pp. 107-117, 2022.
Z. Wang, J. Xin, Z. Zhang, “Computing effective diffusivities of 3D time-dependent chaotic flows with a convergent Lagrangian numerical method” (opens in new tab), ESAIM: Mathematical Modeling and Numerical Analysis, vol. 56, pp. 1521-1544, 2022.

Most Cited Publications

J. Xin, “Front Propagation in Heterogeneous Media” (opens in new tab), SIAM Review, vol. 42, no. 2, pp. 161-230, 2000.
P. Yin, Y. Lou, Q. He, J. Xin, “Minimization of l1−2 for compressed sensing” (opens in new tab), SIAM J. Sci. Computing, vol. 37, no. 1, pp. A536-A563, 2015.
P. Yin, J. S. Zhang, S. Osher, Y-Y. Qi, J. Xin, “Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets”, International Conference on Learning Representations (ICLR), 2019.
Y. Lou, T. Zeng, S. Osher, J. Xin, “A Weighted Difference of Anisotropic and Isotropic Total Variation Model for Image Processing” (opens in new tab), SIAM J. Imaging Sci, vol. 8, no. 3, pp. 1798-1823, 2015.
Y. Lou, P. Yin, Q. He, J. Xin, “Computing Sparse Representation in a Highly Coherent Dictionary Based on Difference of L1 and L2” (opens in new tab), J. Scientific Computing, vol. 64, no. 1, pp. 178-196, 2015.
E. Esser, M. Möller, S. Osher, G. Sapiro, J. Xin, “A Convex Model for Nonnegative Matrix Factorization and Dimensionality Reduction on Physical Space” (opens in new tab), IEEE Transactions on Image Processing, vol. 21, no. 7, pp. 3239–3252, 2012.
E. Esser, Y. Lou, J. Xin, “A Method for Finding Structured Sparse Solutions to Non-negative Least Squares Problems with Applications” (opens in new tab), SIAM Journal on Imaging Sciences, vol. 6, no. 4, pp. 2010–2046, 2013.
Xin, J., “Existence of Planar Flame Fronts in Convective-Diffusive Periodic Media” (opens in new tab), Arch. Rat. Mech. and Anal., vol. 121, pp. 205-233, 1992.
Xin, J., “Existence and nonexistence of traveling waves and reaction-diﬀusion front propagation in periodic media” (opens in new tab), J. of Stat. Phys., vol. 73, pp. 893-926, 1993.
S. Zhang, J. Xin, “Minimization of transformed L1 penalty: Theory, Difference of Convex Function Algorithm, and Robust Application in Compressed Sensing” (opens in new tab), Mathematical Programming Series B, vol. 169, no. 1, pp. 307-336, 2018.

Contact Information

Website: http://math.uci.edu/~jxin

Email: jxin@math.uci.edu

Phone: (949) 824

Address: Department of Mathematics UC Irvine Irvine, CA 92697, USA

This profile was created with the help of AI.

Last updated on 2/14/2025.