Ke Wang  
(王 )

kw_ws.jpg

I am currently a research scientist/engineer at Adobe Inc, with Marc Levoy’s computational photography team. Before that, I was a senior research engineer at Samsung Research America (SRA), MPI Lab.

I obtained my Ph.D. degree from Electrical Engineering and Computer Sciences at UC Berkeley, working with Prof. Miki Lustig and Prof. Stella Yu. I was a member of Berkeley Artificial Intelligence Research (BAIR). I graduated with honor from the department of Biomedical Engineering in Tsinghua University. My research interests lie in computational imaging, computational photography, deep learning, signal processing, inverse problem, medical imaging and computer vision. I am an enthusiast of science, engineering, music, ice skating, rock climbing and everything related to medicine and healthcare! My name in Chinese is 王可.

Feel free to reach me at kewang [at] adobe [dot] com.

news

Jan 22, 2024 I join Adobe Inc. as a computer scientist with Marc Levoy’s computational photography team!
Sep 21, 2023 Our MRI off-resonance correction paper (Physics-Informed Deep Learning Framework for MRI Off-Resonance Correction Trained with Noise Instead of Data) was accpeted to NeurIPS 2023! Project led by my awesome collaborator Alfredo! Arxiv and code will be available soon! [Paper]
Jun 30, 2023 Our image harmonization work (Semi-supervised Parametric Real-world Image Harmonization) is presented at CVPR 2023. [Project page] [Paper] [Video] [Code] [Poster]
Jun 19, 2023 Our paper High-fidelity Direct Contrast Synthesis from MR Fingerprinting was accepted by MRM is now published online! Please check it out! [Paper]
Jun 1, 2023 I join Samsung Research America (SRA) as a senior research engineer, working on real-worled computational imaging and computer vision! Lets keep making impacts!
May 12, 2023 Graduation time! I offically obtained my Ph.D degree from EECS, UC Berkeley! Go Bears! My thesis Magnetic Resonance Image Reconstruction with Greater Fidelity and Efficiency is available!
Jan 1, 2023 I will be serving as reviewer for MICCAI 2023, Neurips 2023, Siggraph Asia 2023, Siggraph 2023, ICLR 2023.
May 30, 2022 I presented our work on Rigorous Uncertainty Estimation for MRI Reconstruction at ISMRM 2022 as an oral presentation. Manuscript and abstract is available upon request.
Apr 30, 2022 Our UFLoss paper titled High fidelity deep learning-based MRI reconstruction with instance-wise discriminative feature matching loss was accecpted by MRM and is now published online! Please check it out! [paper] [talk] [code]
Feb 20, 2022 Three abstracts (1 first-authored and 2 co-authored) were accepted by ISMRM 2022 as oral presentations!
Feb 1, 2022 Our Data Crimes paper with title Implicit data crimes: Machine learning bias arising from misuse of public data was accpeted for publication in PNAS! More infromation and details for this paper are avaible on Efrat’s website.
Sep 30, 2021 I presented our work on Memory-efficient Learning for High-dimensional MRI Reconstruction at MICCAI 2021. Date & Time: September 29th (Wednesday), 09:30 - 11:00 (UTC). Welcome to check it out! [Paper] [Poster] [Video]

selected publications

  1. ×
    PhD Thesis: Magnetic Resonance Imaging with Greater Fidelity and Efficiency
    Ke Wang
    University of California, Berkeley, 2023
  2. ×
    ResoNet: a Physics-Informed DL Framework for Off-Resonance Correction in MRI Trained with Noise
    Alfredo De Goyeneche, Shreya Ramachandran, Ke Wang, Ekin Karasan, and 3 more authors
    In Thirty-seventh Conference on Neural Information Processing Systems, 2023
  3. ×
    Semi-supervised Parametric Real-world Image Harmonization
    Ke Wang, Michaël Gharbi, He Zhang, Zhihao Xia, and 1 more author
    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
  4. ×
    High-fidelity direct contrast synthesis from magnetic resonance fingerprinting
    Ke Wang, Mariya Doneva, Jakob Meineke, Thomas Amthor, and 5 more authors
    Magnetic Resonance in Medicine, 2023
  5. ×
    High fidelity deep learning-based MRI reconstruction with instance-wise discriminative feature matching loss
    Ke Wang, Jonathan I Tamir, Alfredo De Goyeneche, Uri Wollner, and 3 more authors
    Magnetic Resonance in Medicine, 2022
  6. ×
    Memory-efficient learning for high-dimensional mri reconstruction
    Ke Wang, Michael Kellman, Christopher M Sandino, Kevin Zhang, and 4 more authors
    In Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th International Conference, Strasbourg, France, September 27–October 1, 2021, Proceedings, Part VI 24
  7. ×
    Rigorous Uncertainty Estimation for MRI Reconstruction
    Ke Wang, Anastasios Angelopoulos, Alfredo De Goyeneche, Amit Kohli, and 4 more authors
    In Proc. Intl. Soc. Mag. Reson. Med, 2022
  8. ×
    Implicit data crimes: Machine learning bias arising from misuse of public data
    Efrat Shimron, Jonathan I Tamir, Ke Wang, and Michael Lustig
    Proceedings of the National Academy of Sciences, 2022
  9. ×
    Non-Invasive Remote Temperature Monitoring Using Microwave-Induced Thermoacoustic Imaging
    Hao Nan, Aidan Fitzpatrick, Ke Wang, and Amin Arbabian
    In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)