IEEE SPS Computational Imaging Webinar Series

Signal Processing And Computational imagE formation (SPACE)

• SPACE Invited Talks:

Season 3 (Sep - Dec, 2021)

1. (WEST Session) Sep 7, 2021, Qing Qu, From Shallow to Deep Representation Learning in Imaging and Beyond: Global Nonconvex Theory and Algorithms

   • Video Recording[ Youtube ]

2. (EAST Session) Sep 21, 2021, Bin Dong, Data- and Task-Driven CT Imaging by Deep Learning

   • Video Recording [ Youtube ]

3. (WEST Session) Oct 5, 2021, Wolfgang Heidrich, Deep Optics — Joint Design of Imaging Hardware and Reconstruction Methods

   • Video Recording[ Youtube ]

4. (EAST Session) Oct 19, 2021, canceled.

5. (WEST Session) Nov 2, 2021, Salman Asif, Lensless Imaging with Programmable Masks and Illumination

   • Video Recording[ Youtube ]

6. (WEST Session) Nov 30, 2021, Mathews Jacob, Model-based Deep Learning for Large-scale Inverse Problems

   • Video Recording[ Youtube ]

7. (EAST Session) Dec 14, 2021, Se Young Chun, Towards Deep Learning-Based Image Reconstruction With Model-Based Self-Supervision

   • Video Recording[ Youtube ]

Season 2 (Feb - June, 2021)

1. Feb 9, 2021, YongKeun Park, Quantitative phase imaging and artificial intelligence: label-free 3D imaging, classification, and inference.

1. • Video Recording [ Download ]

2. Feb 23, 2021, Pier Luigi Dragotti, Computational Imaging for Art Investigation: Revealing Hidden Drawings in Leonardo’s Paintings

   • Video Recording [ Youtube ]

3. Mar 9, 2021, Gordon Wetzstein, Towards Neural Signal Processing and Imaging

   • Video Recording [ Youtube ]

4. Mar 24, 2021, Yonina Eldar, Model Based Deep Learning: Applications to Imaging and Communications

   • Video Recording [ Youtube ]

5. Apr 6, 2021, Ivan Dokmanić, Learning the Geometry of Wave-Based Imaging

   • Video Recording [ Youtube ]

6. Apr 20, 2021, Ori Katz, Imaging with scattered light: Exploiting speckle to see deeper and sharper

   • Video Recording [ Youtube ]

7. May 4, 2021, Lei Tian, Model and learning strategies for computational 3D phase microscopy

   • Video Recording [ Youtube ]

8. May 18, 2021, Rebecca Willet , Machine Learning and Inverse Problems in Imaging

   • Video Recording [ Youtube ]

9. June 1, 2021, Marvin M. Doyley, Elastography from theory to practice

   • Video Recording [ Youtube ]

10. June 23, 2021, Sabine Süsstrunk, Opponency Revisted

    • Video Recording [ Youtube ]

Season 1 (May - Dec, 2020)

1. May 19, 2020, Raja Giryes, Joint Design of Optics and Post-Processing Algorithms Based on Deep Learning for Generating Advanced Imaging Features.

10. • Slides [ Download ]

2. June 2, 2020, Laura Waller, End-To-End Learning for Computational Microscopy

10. • Video Recording [ Youtube ]

3. June 16, 2020, Michael Unser, CryoGAN: A novel paradigm for single-particle analysis and 3D reconstruction in cryo-EM microscopy

10. • Video Recording [ Youtube ]

4. June 30, 2020, Katie Bouman, Capturing the First Image of a Black Hole & Designing the Future of Black Hole Imaging

10. • Video Recording [ Youtube ]

5. July 14, 2020, Jong Chul Ye , Optimal transport driven CycleGAN for unsupervised learning in inverse problems

10. • Video Recording [ Youtube ]

6. July 28, 2020, Orazio Gallo , Depth Estimation from RGB Images with Applications to Novel View Synthesis and Autonomous Navigation

10. • Video Recording [ Youtube ]

7. August 11, 2020, Xiao Xiang Zhu, Data Science in Earth Observation

10. • Video Recording [ Youtube ]

8. August 25, 2020, Saiprasad Ravishankar, From Transform Learning to Deep Learning and Beyond for Imaging

10. • Video Recording [ Youtube ]

9. Sep 8, 2020, Anat Levin , Rendering speckle statistics in scattering media and its applications in computational imaging

10. • Video Recording [ Youtube ]

10. Oct 6, 2020, John Wright , Geometry and Symmetry in (some!) Nonconvex Optimization Problems

10. • Video Recording [ Youtube ]

11. Oct 20, 2020, Bihan Wen , From Signal Processing to Machine Learning: How "Old" Ways Can Join The New

10. • Video Recording [ Youtube ]

12. Nov 3, 2020, Nicole Seiberlich , Bringing New Imaging Technologies to the Clinic

13. Nov 17, 2020, Yoram Bresler , Two Topics in Deep Learning for Image Reconstruction: (i) Physics-based x-ray scatter correction for CT; and (ii) Adversarial training for improved robustness.

10. • Video Recording [ Youtube ]

14. Dec 1, 2020, Singanallur V Venkatakrishnan, Pushing the Limits of Scientific CT Instruments using Algorithms : Model-based and Data-Driven Approaches

10. • Video Recording [ Youtube ]

15. Dec 15, 2020, J. Webster Stayman, Novel data acquisition and task-based optimization in computed tomography

10. • Video Recording [ Youtube ]

Speakers for 2020 Season 1

1. Raja Giryes (Tel Aviv University)

2. Laura Waller (UC Berkeley)

3. Michael Unser (EPFL)

4. Katie Bouman (Caltech)

5. Jong Chul Ye - (KAIST)

6. Orazio Gallo (NVIDIA)

7. Xiao Xiang Zhu (TUM)

8. Saiprasad Ravishankar (Michigan State University)

9. Anat Levin (Technion)

10. Pier Luigi Dragotti (Imperial College)

11. John Wright (Columbia University)

12. Bihan Wen (NTU)

13. Nicole Seiberlich (UMich)

14. Yoram Bresler (UIUC)

15. Singanallur V Venkatakrishnan (Oak Ridge National Laboratory)

16. J. Webster Stayman (Johns Hopkins)

Organizers

• Saiprasad Ravishankar, Michigan State University, USA ( ravisha3@msu.edu )

• Bihan Wen, Nanyang Technological University, Singapore ( bihan.wen@ntu.edu.sg )

• Raja Giryes, Tel Aviv University, Israel ( raja@tauex.tau.ac.il )

• Zhizhen Zhao, University of Illinois at Urbana-Champaign, USA ( zhizhenz@illinois.edu )

• Jong Chul Ye, Korea Advanced Institute of Science and Technology, Korea ( jong.ye@kaist.ac.kr )

[ Webinar Organizing Committee ]

• Upcoming Talks

Season 3 (Sep - Dec, 2021)