Stanley J. Osher, Ph.D.

Applied Mathematics University of California, Los Angeles, Los Angeles, CA 
Sparsity, Compressive Sensing, Imaging, PDE, Level sets
Stanley Osher (born April 24, 1942) is an American mathematician, known for his many contributions in shock capturing, level set methods, and PDE-based methods in computer vision and image processing. Osher is a professor at the University of California, Los Angeles (UCLA), Director of Special Projects in the Institute for Pure and Applied Mathematics (IPAM) and member of the California NanoSystems Institute (CNSI) at UCLA. He has a daughter, Kathryn, and a son, Joel. 2014 recipient of the CF Gauss award

Mean distance: 29.97


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Jacob T. Schwartz grad student 1966 NYU
 (Similarity Properties of Certain Volterra Operators on L sub p [0,1])


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Mark Sussman grad student 1994 UCLA (Physics Tree)
Li-Tien Cheng grad student 2000 UCLA
Hyeseon Shim grad student 2000 UCLA
Frederic G. Gibou grad student 2001 UCLA
Duc Q. Nguyen grad student 2001 UCLA
Yen-Hsi R. Tsai grad student 2002 UCLA
Thomas C. Cecil grad student 2003 UCLA
Chiu-Yen Kao grad student 2004 UCLA
Chohong Min grad student 2004 UCLA
Tsz S. Chung grad student 2005 UCLA
Shing-Yu Leung grad student 2006 UCLA
Jinjun Xu grad student 2006 UCLA
Jeremy Brandman grad student 2008 UCLA
Yanina Landa grad student 2008 UCLA
Igor Yanovsky grad student 2008 UCLA
Bin Dong grad student 2009 UCLA
Jian Ye grad student 2009 UCLA
Thomas Goldstein grad student 2010 UCLA
Yingying Li grad student 2010 UCLA
Zhaohui Guo grad student 2011 UCLA
Wenye Ma grad student 2011 UCLA
Ryo Takei grad student 2011 UCLA
Hayden K. Schaeffer grad student 2013 UCLA
Alan P. Mackey grad student 2015 UCLA
Braxton Osting post-doc UCLA


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Mark S. Cohen collaborator UCLA
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Rana A, Zhang J, Pham M, et al. (2020) Potential of Attosecond Coherent Diffractive Imaging. Physical Review Letters. 125: 086101
Wang B, Lin A, Yin P, et al. (2020) Adversarial defense via the data-dependent activation, total variation minimization, and adversarial training Inverse Problems and Imaging. 1-17
Pham M, Rana A, Miao J, et al. (2019) Semi-implicit relaxed Douglas-Rachford algorithm (sDR) for ptychography. Optics Express. 27: 31246-31260
Parkinson C, Arnold D, Bertozzi AL, et al. (2019) Optimal human navigation in steep terrain: a Hamilton–Jacobi–Bellman approach Communications in Mathematical Sciences. 17: 227-242
Arnold DJ, Fernandez D, Jia R, et al. (2019) Modeling Environmental Crime in Protected Areas Using the Level Set Method Siam Journal On Applied Mathematics. 79: 802-821
Wu Z, Zhu W, Chanussot J, et al. (2019) Hyperspectral Anomaly Detection via Global and Local Joint Modeling of Background Ieee Transactions On Signal Processing. 67: 3858-3869
Chow YT, Darbon J, Osher S, et al. (2019) Algorithm for overcoming the curse of dimensionality for state-dependent Hamilton-Jacobi equations Journal of Computational Physics. 387: 376-409
Wang B, Yin P, Bertozzi AL, et al. (2019) Deep Learning for Real-Time Crime Forecasting and Its Ternarization Chinese Annals of Mathematics, Series B. 40: 949-966
Kirchner MR, Hewer G, Darbon J, et al. (2018) A Primal-Dual Method for Optimal Control and Trajectory Generation in High-Dimensional Systems Arxiv: Systems and Control. 1583-1590
Royston M, Pradhana A, Lee B, et al. (2018) Parallel redistancing using the Hopf–Lax formula Journal of Computational Physics. 365: 7-17
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