SEAN I YOUNG, PhD | About Me | Curriculum Vitae | Publications | Google Scholar | E-mail
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Personal Information
Sean I. Young, PhD
MGH/HST Martinos Center
149 13th Street
Boston, MA 02129
United States of America
P: +1 617 758 9783
E: siyoung@mit.edu
Academic Appointments
05/2023–Present Instructor Department of Radiology Harvard Medical School
10/2021–Present Affiliated Computer Science and Artificial MIT
Researcher Intelligence Lab (CSAIL)
Postdoctoral Training
04/2019–10/2020 Postdoctoral Department of Electrical Engineering Stanford University
Scholar (Advisor: Bernd Girod) Stanford, CA
10/2020–05/2023 Research Department of Radiology Harvard Medical School
Fellow (Advisor: Bruce Fischl) Boston, MA
Education
03/2003–11/2007 BEng Software Engineering University of Auckland
Awarded 05/2008 Auckland, New Zealand
07/2010–10/2011 MEngSc Computer Science University of New South Wales
Awarded 08/2011 Sydney, NSW, Australia
03/2012–02/2018 PhD Electrical Engineering University of New South Wales
Awarded 07/2018 (Advisor: David Taubman) Sydney, NSW, Australia
Funding and Awards
2023–2028 Principal Ultra-precision Clinical Imaging of AD NIH
(Awarded) Investigator Using Deep Learning (K99AG081493-01) ($995,000)
Teaching Positions
2015–2016 TA (3 hrs biweekly Multimedia Signal Processing University of New South Wales
(two semesters) for 16 wks) (Fourth-year EE course) Sydney, NSW, Australia
2017 Tutor (1.5 hrs Multimedia Signal Processing University of New South Wales
weekly for 6 wks) (Fourth-year EE course) Sydney, NSW, Australia
2022–2023 Lecturer (2.5 hrs Artificial Intelligence Kaplan Australia and
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(four trimesters) weekly for 48 wks) and Machine Learning New Zealand (Online)
Other Professional Positions
12/2007–05/2009 Programmer Software Engineering Intergen Limited
(Manager: Joe Newton) Auckland, New Zealand
07/2009–06/2010 Programmer Software Engineering Datacom Systems Limited
(Manager: Ratnakar Garikipati) Auckland, New Zealand
01/2011–12/2011 Tester Software Engineering Free Software Foundation
(Manager: Jordi Gutierréz) Boston, MA
07/2016–01/2017 Research Intern Electrical Engineering InterDigital Communications
(Manager: Yan Ye) San Diego, CA
Professional Societies
2013–Present Institute of Electrical and Electronics Engineers (IEEE) Member
2013–Present IEEE Signal Processing Society Member
2018–Present Australian Pattern Recognition Society (APRS) Member
Editorial Activities
2017–2018 IEEE Int. Conf. on Image Processing Reviewer
2020–Present IEEE Transactions on Multimedia Reviewer
2020–Present IEEE Transactions on Image Processing Reviewer
2021–Present Nature Scientific Reports Reviewer
2022–Present Frontiers in Artificial Intelligence Reviewer
2022–Present Information Processing in Medical Imaging Reviewer
2023–Present Medical Image Computing and Computer Assisted Intervention Reviewer
2023–Present IEEE/CVF Conf. on Computer Vision and Pattern Recognition Reviewer
Honors and Prizes
2011 University of New South Wales CSE Performance Award Award
2012–2015 University of New South Wales APA Faculty Award Scholarship
2012–2015 University of New South Wales APA Award (Ph.D.) Scholarship
2018 Australian Pattern Recognition Society Best Paper Award Award
Local Invited Presentations
2016 Graph-based regularization for signal processing UC San Diego
(Group seminar) San Diego, CA
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2018 Solving vision problems via filtering University of New South Wales
(Group seminar) Sydney, NSW, Australia
2018 “Solving vision problems via filtering” Stanford University
(Group seminar) Stanford, CA
2021 “Transform quantization for CNN compression” ARM Research
(Group seminar) Boston, MA
2021 “Non-line-of-sight Surface Reconstruction” CSAIL, MIT
(Group seminar) Cambridge, MA
2021 “Supervision by denoising for medical image segmentation” McGovern Institute
(Group seminar) Cambridge, MA
2021 “Supervision by denoising for medical image segmentation” CSAIL, MIT
(Group Seminar) Cambridge, MA
2022 “Non-line-of-sight Surface Reconstruction Using the D-LCT” Boston University
(Group seminar) Boston, MA
2023 “Fully Convolutional Slice-to-volume Reconstruction McGovern Institute
(Group seminar) Cambridge, MA
National Invited Presentations
2018 “Fast optical flow extraction from compressed video” DICTA Conference
(Conference presentation) Canberra, ACT, Australia
2020 “NLOS surface reconstruction using the directional LCT” CVPR Conference
(Conference presentation) Online
2021 “Transform quantization for CNN compression” University of Southern California
(Group seminar) Los Angeles, CA
2021 “Transform quantization for CNN compression” UC San Diego
(Group seminar) San Diego, CA
2021 “Transform quantization for CNN compression” Stanford Compression Workshop
(Group seminar) Stanford, CA
2022 “Supervision by Denoising” NIST
(Group seminar) Bethesda, MD
2022 “Supervision by Denoising” University of Maryland
(Group seminar) Bethesda, MD
2023 “Supervision by Denoising” ICCP Conference
(Conference presentation) Madison, WI
International Invited Presentations
2021 “Supervision by denoising for medical segmentation” University College London
(Group seminar) London, UK
2021 “Transform quantization for CNN compression” Facebook AI Toronto
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(Group seminar) Toronto, ON, Canada
2021 “Transform quantization for CNN compression” Simon Fraser University
(Group seminar) Vancouver, BC, Canada
2021 “Transform quantization for CNN compression” York University
(Group seminar) Toronto, ON, Canada
2023 “Fully convolutional slice-to-volume Auckland Bioengineering Institute
reconstruction for single-stack MRI” (Group seminar) Auckland, New Zealand
Report of Technological and Other Scientific Innovations
2016 “Higher-order motion models and graduated motion estimation” US Patent (PCT)
(Patent) (W02018209067A1)
Report of Scholarship
1. S. I. Young, D. Taubman. “Rate–distortion optimized optical flow estimation,” Proc. IEEE ICIP
2015
2. S. I. Young, R. Mathew, D. Taubman. “Optimizing block-coded motion parameters with block-
partition graphs,” Proc. IEEE ICIP 2016
3. S. I. Young, A. Naman, D. Taubman. “COGL: Coefficient graph Laplacians for optimized JPEG
image decoding,” IEEE Trans. Image Process. 2019; 28:343–355 (pdf)
4. S. I. Young, A. Naman, B. Girod, D. Taubman. “Solving vision problems via filtering,” Proc. ICCV,
2019 (poster, pdf)
5. S. I. Young, A. Naman, D. Taubman. “Graph Laplacian regularization for robust optical flow
estimation,” IEEE Trans. Image Process. 2020; 29:3970–83 (pdf)
6. S. I. Young, B. Girod, D. Taubman. “Gaussian lifting for fast bilateral and nonlocal means filtering,”
IEEE Trans. Image Process. 2020; 29:6082–95 (pdf)
7. S. I. Young, B. Girod, D. Taubman. “Fast optical flow extraction from compressed video,” IEEE
Trans. Image Process. 2020; 29:6409–21 (APRS/IAPR best paper, pdf)
8. S. I. Young, D. B. Lindell, B. Girod, D. Taubman, G. Wetzstein. “Non-line-of-sight surface
reconstruction using the directional light-cone transform,” Proc. CVPR, 2020 (oral, pdf)
9. S. Kim, A. Sharma, Y. Liu, S. I . Young. “Rethinking Satelllite Data Merging: From averaging to
SNR optimization,” IEEE Trans. Geosci. Remote Sens. 2021 (pdf)
10. S. I. Young, W. Zhe, D. Taubman, B. Girod. “Transform quantization for CNN compression,” IEEE
Trans. Pattern Anal. Mach. Intell. 2021 (pdf)
11. S. M. Abulnaga, S. I. Young, K. Hobgood, E. Pan, C. J. Wang, P. E. Grant, E. A. Turk, P. Golland.
“Automatic Segmentation of the Placenta in BOLD MRI Time Series,” Lecture Notes in Computer
Science, vol 13575, Springer
12. S. I. Young, A. V. Dalca, E. Ferrante, P. Golland, C. A. Metzler, J. E. Iglesias, B. Fischl. “Supervision
by denoising,” IEEE Trans. Pattern Anal. Mach. Intell. 2023, 1–1
13. S. I. Young, Y. Balbastre, A. V. Dalca, W. M. Wells, J. E. Iglesias, B. Fischl. “SuperWarp: Supervised
Learning and Warping on U-Net for Invariant Subvoxel-Precise Registration” Medical Image
Computing and Computer Assisted Intervention Workshops. 2022, 103–115.
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14. M. G. French, G. D. Maso Talou, T. P. Babarenda Gamage, M. P. Nash, J. E. Iglesias, Y. Balbastre,
S. I. Young. “Learning strategies for Breast MR image registration under diffeomorphic constraints,”
Medical Image Computing and Computer Assisted Intervention Workshops. 2023
15. M. Chan, S. I. Young, C. A. Metzler, “SUD2 for semi-supervised computational imaging,” NeurIPS
Workshops. 2023
16. S. I. Young, Y. Balbastre, B. Fischl, P. Golland, J. E. Iglesias. “Fully convolutional slice-to-volume
reconstruction for single-stack MRI,” Proc. CVPR, 2024 (Submitted)
17. S. M. Abulnaga, N. Dey, S. I. Young, E. Pan, K. I. Hobgood, Clinton J. Wang, P. E. Grant, E. A.
Turk, P. Golland. “Shape-aware Segmentation of the Placenta in BOLD Fetal MRI Time Series,”
Mach. Learn. Biomed. Imaging. 2023, 2:527–546 .
Thesis
1. S. I. Young. “Graph regularization for inverse problems in imaging,” PhD Thesis, School of Electrical
Engineering and Telecommunications, University of New South Wales, Sydney, NSW, Australia,
June 2018
