학력

Ph.D in Bio and Brain Engineering, KAIST (2021)

M.S. in Bio and Brain Engineering, KAIST (2017)

B.S. in Bio and Brain Engineering, KAIST (2015)

연구분야

Computer vision

Deep learning for image processing

Generative models

주요 연구 성과

"Regularization by denoising diffusion process meets deep relaxation in phase," Image and Vision Computing, vol. 151, p.105282, 2024

"DeepPhaseCut: Deep Relaxation in Phase for Unsupervised Fourier Phase Retrieval," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 44, no. 12, pp. 9931-9943, 2022.

“Low-dose sparse-view haadf-stem-edx tomography of nanocrystals using unsupervised deep learning,” ACS nano, vol. 16, no. 7, pp. 10 314–10 326, 2022. (*Co-first author)

“Two-stage deep learning for accelerated 3d time-of-flight mra without matched training data,” Medical Image Analysis, vol. 71, p. 102047, 2021.

“Deep learning stem-edx tomography of nanocrystals,” Nature Machine Intelligence, vol. 3, no. 3, pp. 267–274, 2021. (*Co-first author) **Selected as a front cover image**

“Unpaired training of deep learning tmra for flexible spatio-temporal resolution,” IEEE Transactions on Medical Imaging, vol. 40, no. 1, pp. 166–179, 2020.

“Accuracy improvement of quantification information using super-resolution with convolutional neural network for microscopy image”, Biomedical Signal Processing and Control, vol. 58, 2020.

"Geometric Approaches to Increase the Expressivity of Deep Neural Networks for MR Reconstruction.", Special Issue on Domain Enriched Learning for Medical Imaging, IEEE Journal of Selected Topics in Signal Processing, in press, 2020. **Selected as a front cover image**

“Deep convolutional framelets: A general deep learning framework for inverse problems", SIAM Journal on Imaging Sciences, vol. 11(2), pp. 991-1048, 2018.