Bin Dong

    UCLA Mathematics Department

    Box 951555

    Los Angeles, CA 90095-1555

    Office: IPAM 1129C 
    Email: bdong {at} math{dot}ucla{dot}edu

math

 

 I have stopped updating this webpage as of June 30, 2009.

Please go to www.math.ucsd.edu/~b1dong for the latest updates.

 

Education

     Ph.D. candidate, University of California – Los Angeles, Los Angeles, CA, USA, 2005 – 2009.

 Advisor: Professor Stanley Osher.

     M.S., National University of Singapore, Singapore, 2003-2005.

 Advisor: Professor Zuowei Shen.

     B.S., Peking University, Beijing, China, 1999-2003.

Research Interests

1.        Numerical PDEs, Level Set Methods.

2.        Optimization Problems (e.g. L1-Minimizations and Compressed Sensing)

3.        Wavelets Theory and Applications.

4.        Image Processing and 3D Shape Analysis.

 

My CV: PDF.

My Master Thesis: PDF

My PhD Thesis: PDF

 

Current Projects/Working Problems

1.      Fast algorithms for L1 minimization and their applications in signal and image processing.

2.      Multiscaled representation (wavelet flavored but level set and PDE based) for surfaces and its applications.

3.      Capturing regions of interests in 3D biological surfaces via level set and PDE based models.

4.      Design fast solvers for nonlinear PDEs via wavelets/framelets transforms.

5.      Ultrasound image processing and analysis (denoising, segmentation and needle tracking).

6.      Level set and PDE based surface reconstruction/restoration.

Publications

1.     Bin Dong, Nira Dyn and Kai Hormann, Properties of dual pseudo-splines, Institut fur Informatik, Technical Report 09-03, 2009.

2.     Bin Dong, Aichi Chien, Zuowei Shen and Stanley Osher, A new multiscale representation for shapes and its application to blood vessel recovery, submitted, 2009.

3.     Bin Dong, The implicit representation of biological shapes and forms, Biomedical Computation Review (issue: Spring 2009), Published by Simbios, the NIH National Center for Physics-Based Simulation of Biological Structures, 2009.

4.     Bin Dong, Eric Savitsky and Stanley Osher, A Novel Method for Enhanced Needle Localization Using Ultrasound-Guidance, CAM-Report 08-65, Sep. 2008.

5.     Bin Dong, Aichi Chien, Yu Mao, Jian Ye, Fernando Vinuela and Stanley Osher, Level set based brain aneurysm capturing in 3D, submitted, 2008.

6.      Stanley Osher, Yu Mao, Bin Dong, Wotao Yin, Fast linearized Bregman iterations for compressive sensing and sparse denoising, accepted by Communications in Mathematical Sciences, CAM-Report 08-37, Dec. 2008.

7.      Bin Dong, Aichi Chien, Yu Mao, Jian Ye and Stanley Osher, Level set based surface capturing in 3D medical images, MICCAI 2008, 162-169, 2008.

8.      Bin Dong, Jian Ye, Stanley Osher and Ivo Dinov, Level set based nonlocal surface restoration, MMS Vol. 7(2), 589-598 (CAM-Report 07-44), 2008.

9.      Bin Dong, Yu Mao, Ivo D. Dinov, Zhuowen Tu, Yonggang Shi, Yalin Wang and Arthur W. Toga, Wavelet-Based Representation of Biological Shapes, CAM-Report 07-36 (unpublished manuscript), Sep. 2007.

10.                         Bin Dong and Zuowei Shen, Pseudo-splines, wavelets and framelets, Appl. Comput. Harmon. Anal., 22, 78-104, 2007.

11.                         Bin Dong and Zuowei Shen, Linear independence of pseudo-splines, Proc. Amer. Math. Soc., 134, 2685-2694, 2006.

12.                         Bin Dong and Zuowei Shen, Construction of biorthogonal wavelets from pseudo-splines, J. Approx. Theory, Vol. 138 (2), 211-231, 2006.

Courses Taken at UCLA

1.     MATH 266ABC - Ordinary Differential Equations; Applied Partial Differential Equations (general theories for first order linear, quasilinear PDEs; parabolic and hyperbolic PDEs; Hamilton-Jacobi equations; scalar conservation law, shocks and Riemann problems; hyperbolic systems and systems of conservation laws).

2.     MATH 269ABC - Numerical Ordinary Differential Equations; Finite Difference Methods in Solving Parabolic and Hyperbolic Partial Differential Equations; Finite Difference, Finite Element Method in Solving Elliptic Partial Differential Equations.

3.     MATH 270C - Iterative Methods in Solving Linear Systems (e.g. systems obtained from discretizing Poisson equations).

4.     MATH 273 (by Luminita Vese) - Optimization, Calculus of Variations, and Control Theory.

5.     MATH 270D&285J (by Stanley Osher) - Mathematical Aspects of Scientific Computing; given by Professor Stanley Osher. Topics include level set methods and its applications in image processing: Numerical methods, e.g. monotone and ENO schemes, for finding viscosity solutions of Hamilton-Jacobi equations (e.g. motion by mean curvature); ROF model; Snake and Chan-Vese model in image segmentation; BV$L_1$; Global minimization for snakes and Munford-Shah models in image segmentation and denoising; Bregman Iterations and Inverse Scale Space methods for image denoising\&deblurring; Image inpainting).

6.     MATH 285J (by Achi Brandt) - A two quarter course about Multigrid methods (Vcycles and Full Multigrid) in Solving Poisson equations and Bratu equation (\Delta u+\lambda e^u=0). We also used Full Multigrid method to solve the parameter \lambda and u of Bratu equation simultaneously with ||u|| being given. The course also includes Algebraic Multigrid method and my final project is using line integration and Algebraic Multigrid to do image denoising.

7.     EE 236A (by Lieven Vandenberghe) - Linear Programming: Basic definitions and geometry of linear programming, engineering applications, duality, the simplex method, interior-point methods, large-scale linear programming, introduction to network optimization and integer linear programming.

8.     EE 236B (by Lieven Vandenberghe) - Nonlinear Programming: Convex sets and convex functions, convex optimization problems, duality, approximation and fitting, statistical estimation, geometric problems, numerical linear algebra background, unconstrained minimization, equality constrained minimization, interior-point methods.

Teaching (Winter 2008)

     Math 3B, Calculus for Life Science Students (Instructor: Prof. Popa).

      Office Hour: 1pm-2pm, Thursday. Location: 1129C@IPAM (Institute for Pure and Applied Mathematics)

      Practice Exams (Note that the practice exams are only for practice. It does NOT mean the real exams will be of the same format or difficulty):

1.     Midterm1

2.     Midterm2

Hobbies:

     Sports: Basketball, Hiking, Diving (only did it twice though…looking for someone to take a class together), Watching “Man v.s. Wild” on Discovery Channel.

     PC Games: Baldur’s Gate, Neverwinter Nights, The Witcher, Heroes Might and Maggic, Starcraft/Brood War, Diablo, and pinball on Windows XP.

     Others: Watching TV (favorite TVs: The office, friends, CSI-LV, south park, six feet under, LOST)

Last updated: May 2009.

free web counter
Comcast Net