Hung Nien (粘紘)
I obtained my Ph.D. from the Electrical Engineering: Systems program in the Department of Electrical Engineering and Computer Science at the University of Michigan, Ann Arbor. I worked on X-ray computed tomography (CT) image reconstruction under the supervision of Prof. Jeffrey A. Fessler, and I am now working as a postdoctoral research fellow in the same group.
My research interests include convex optimization, iterative algorithm, compressed sensing, and computational photography. I am seeking a professional position in imaging and machine learning research to dedicate myself with my knowledge and skill set in mathematical optimization.
Here are my resume, Google scholar citation, and articles on arXiv.
My research projects have included
Model-based tomographic reconstruction of translucent objects using lenslet-based plenoptic cameras
Convergence analysis of convex optimization method with inexact updates
Fast X-ray CT image reconstruction using variable splitting methods and ordered subsets
Blind gain correction in X-ray CT image reconstruction
Model-based light field reconstruction using a focal stack
For more information, please see the Research page.
H. Nien and J. A. Fessler, " Relaxed linearized algorithms for faster X-ray CT image reconstruction, " in Proc. Intl. Mtg. on Fully 3D Image Recon. in Rad. and Nuc. Med., pp. 260–3, 2015.
[pdf] [slides] [bibtex]
H. Nien and J. A. Fessler, " Fast X-ray CT image reconstruction using a linearized augmented Lagrangian method with ordered subsets, " IEEE Trans. Med. Imag., vol. 34, pp. 388-99, Feb. 2015.
H. Nien and J. A. Fessler, " A convergence proof of the split Bregman method for regularized least-squares problems, " , 2014. arXiv 1402.4371.
For more information, please see the Publication page.