For God so loved the world, that He gave His only Son, that whoever believes in Him should not perish but have eternal life. For God did not send His Son into the world to condemn the world, but in order that the world might be saved through Him. - John 3:16-17 Claire Hong

Claire Hong

Resume
Email: claire.lin.hong@gmail.com

About Me

I am a staff at the Johns Hopkins University Applied Physics Lab in Laurel, MD.
My research interests include large-scale inverse problems, optimization algorithms, computational modeling and simulations, image and signal processing, machine learning, and computer vision.

Education

Ph.D., Applied and Interdisciplinary Mathematics, Department of Mathematics, University of Michigan, 2016 - 2021
Thesis: Efficient Model-Based Reconstruction for Dynamic MRI
Advisors: Prof. Jeff Fessler and Prof. Anna Gilbert

B.S., Applied Mathematics (Summa Cum Laude), Department of Mathematics, Emory University, 2012 - 2016
Thesis: Line-to-Point Registration with Applications in Geometric Reconstruction of Coronary Stents
Advisor: Prof. Lars Ruthotto

Teaching

Math 115: Calculus I (Winter 2017, Fall 2017, Fall 2018)
Math 105: Data, Functions and Graphs (Fall 2016)

Conference Proceedings / Abstracts

Generalizability test of a deep learning-based CT image denoising method [pdf]
R. Zeng, C. Y. Lin, Q. Li, J. Lu, J. A. Fessler, K. J. Myers
Proc. CT Meeting, pp. 224-227, 2020.
A Temporal Model for Task-based Functional MR Images [pdf]
C. Y. Lin, D. C. Noll, J. A. Fessler
Proc. IEEE Intl. Symp. Biomed. Imag., pp. 1035-1038, 2020.
Evaluation of Sparse Sampling Approaches for 3D Functional MRI [pdf]
M. Karker, C. Lin, J. A. Fessler, D. C. Noll
Proc. Intl. Soc. Mag. Res. Med., p. 0370, 2019.
Accelerated Methods for Low-Rank Plus Sparse Image Reconstruction [pdf]
C. Y. Lin, J. A. Fessler
Proc. IEEE Intl. Symp. Biomed. Imag., pp. 48-51, 2018.

Journal Articles

Performance of a Deep Learning-based CT Image Denoising Method: Generalizability over Dose, Reconstruction Kernel, and Slice Thickness [pdf]
R. Zeng, C. Y. Lin, Q. Li, L. Jiang, M. Skopec, J. A. Fessler, K. J. Myers
Med. Phys., 49(2): 836-853, Dec. 2021.
Efficient Regularized Field Map Estimation in 3D MRI [pdf] [code]
C. Y. Lin, J. A. Fessler
IEEE Trans. Comput. Imag., 6: 1451-1458, Oct. 2020.
Efficient Dynamic Parallel MRI Reconstruction for the Low-Rank Plus Sparse Model [pdf] [code]
C. Y. Lin, J. A. Fessler
IEEE Trans. Comput. Imag., 5(1): 17-26, Mar. 2019.
Numerical Methods for Polyline-to-Point-Cloud Registration with Applications to Patient-Specific Stent Reconstruction [pdf]
C. Y. Lin, A. Veneziani, L. Ruthotto
Int. J. Numer. Method Biomed. Eng., 34(3): e2934, Mar. 2018.
Global Sensitivity Analysis in a Mathematical Model of the Renal Interstitium [pdf]
M. Bedell, C. Y. Lin, E. Roman-Melendez, I. Sgouralis
Involve, a Journal of Mathematics, 10(4): 625-649, Mar. 2017.