I am currently a fifth year PhD student in the Department of Statistics at the University of Chicago. I am very happy to be advised by Rina Foygel Barber. My research is supported by Kwanjeong Fellowship.
My current research is centered on high-dimensional statistics and (non)convex optimization. I also work on calibration and image reconstruction for medical imaging. I also look forward to exploring research in other areas of statistics and machine learning!
- Ph.D. in Statistics, 2018
- Advisor: Rina Foygel Barber
- M.S., Statistics, 2013
- B.S., Statistics, B.A., Economics, Minor in Mathematics, 2011
Preprints / Publications
Estimating the spectrum in computed tomography via Kullback-Leibler divergence constrained optimization. Wooseok Ha, Emil Y Sidky, Rina Foygel Barber, Taly Gilat Schmidt, and Xiaochuan pan. submitted. arXiv:1805.00162
Gradient descent with nonconvex constraints: local concavity determines convergence. (Code.) Rina Foygel Barber and Wooseok Ha. Information and Inference. arXiv:1703.07755
X-ray spectral calibration from transmission measurements using Gaussian blur model. Wooseok Ha, Emil Y Sidky and Rina Foygel Barber. Proceedings of the SPIE conference on Medical Imaging 2017: Physics of Medical Imaging.
Trimmed conformal prediction for high-dimensional models. Wenyu Chen, Zhaokai Wang, Wooseok Ha, Rina Foygel Barber. arXiv:1611.09933
Robust PCA with compressed data. Wooseok Ha and Rina Foygel Barber. 28th Annual Conference on Neural Information Processing Systems (NIPS 2015).
- Simultaneous spectral scaling and basis material map reconstruction for spectral CT with photon-counting detectors. Emil Y Sidky, Taly Gilat Schmidt, Rina Foygel Barber, Wooseok Ha, and Xiaochuan Pan. 4th International Conference on Image Formation in X-ray Computed Tomography (CT meeting 2016).