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TZID:Asia/Kolkata
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TZOFFSETFROM:+0530
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DTSTART:20250101T000000
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DTSTART;TZID=Asia/Kolkata:20250421T160000
DTEND;TZID=Asia/Kolkata:20250421T170000
DTSTAMP:20260404T044217
CREATED:20250421T044654Z
LAST-MODIFIED:20250421T044802Z
UID:242003-1745251200-1745254800@ee.iisc.ac.in
SUMMARY:Talk on Phase Retrieval: computational imaging in the machine learning era
DESCRIPTION: A talk on\n\nPhase Retrieval: computational imaging in the machine learning era\n\nby Jonathan Dong\, Biomedical Imaging Group\, Ecole polytechnique federale de Lausanne\, Switzerland\n\nVenue: B303\, Electrical Engineering Department (second floor)\, IISc\n\nDate: April 21\, 2025; Time: 4 PM (Coffee will be served at 3.45 PM)\n\nHost: Prof. Chandra Sekhar Seelamantula (EE)\n\nAbstract: \nPhase retrieval is a fundamental nonlinear inverse problem that appears across a wide range of computational imaging applications\, from X-ray and electron ptychography to phase imaging in optical microscopy. Because it is often addressed through nonlinear optimization techniques\, it has deep links with modern machine learning theory. In this talk\, I will provide a unified overview of phase retrieval models and algorithms\, highlighting the connections between different applications. I will also discuss recent theoretical insights on reconstruction guarantees derived from random matrix theory. Finally\, we’ll explore practical implementations\, and I’ll share how these extend to our recent work on differentiable physical models and open-source computational imaging tools.\n\nBiography of the speaker: \nJonathan Dong is an SNF Ambizione Fellow with Prof. Michael Unser at the Biomedical Imaging Group\, EPFL\, Lausanne\, Switzerland. He received his Ph.D. degree in Physics in 2020 from Ecole Normale Supérieure in Paris\, France. His research interests include nonlinear inverse problems and computational imaging\, with a focus on physics-based models\, reconstruction algorithms\, and statistical analysis methods.
URL:https://ee.iisc.ac.in/event/talk-on-phase-retrieval-computational-imaging-in-the-machine-learning-era/
LOCATION:B-303\,EE
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