[ East Session ] : 11:00 AM UTC (Greenwich Meantime)

[ West Session ] : 1:00 PM ET (New York Time)

IEEE SPS Computational Imaging Webinar Series

Signal Processing And Computational imagE formation (SPACE)

  • About SPACE Webinar Series

Given the impossibility of travel during the COVID-19 crisis, IEEE Computational Imaging TC is launching an SPS Webinar Series SPACE (Signal Processing And Computational imagE formation) as a regular bi-weekly online seminar series to reach out to the global computational imaging and signal processing community.

The seminar series will use the Zoom Webinar platform, and at each seminar, one keynote speaker will give a lecture, which is followed by Q&A and discussions.

We have successfully completed our Season 1 and Season 2.

  • How to Attend

We will use Zoom Webinars and YouTube to deliver the lectures.

Attendees can register using the following links to obtain the Zoom link with password:

  1. [ East Session Registration , 11:00 AM UTC (Greenwich Meantime) ]

  2. [ West Session Registration 1:00 PM ET (New York Time) ]

Since we use separate registration links, so you have to register twice if you wish to attend both EAST and WEST sessions.

Since the Zoom Webinar can only host up to 500 attendees, additional attendees will be directed to our YouTube channel to watch the streaming.

  • New Session!

We are now starting our Season 3 in 2021!

Time and Program Details have been changed. Now SPACE webinar will be divided into WEST and EAST sessions, to cater audiences from different time zones.

  • WEST sessions will be at 1:00pm New York Time ( UTC -4 ), on Tuesday once a month.

  • EAST sessions will be at 7:00pm Beijing / Singapore Time (UTC +8), 8:00pm Korean Time (UTC + 9), or 12:00pm London Time (UTC + 1), on Tuesday once a month.

For attendees from other time zones, please use the [ time zone converter ]. Talks will be approximately 1 hour, followed by Q&A and discussions.


  • Check out more about SPACE invited speakers here: [ Invited Speakers ].

  • Check out the detailed SPACE program here: [ Program ]

  • 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

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

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

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

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

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

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

Season 2 (Feb - June, 2021)

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

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

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

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

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

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

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

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

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

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

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.

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

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

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

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

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

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

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

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

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

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

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

  2. 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.

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

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

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

[ Webinar Organizing Committee ]

  • Upcoming Talks

Season 3 (Sep - Dec, 2021)