The FIND Seminar is a bi-weekly seminar series that hosts cutting-edge research talks on topics related to the broad themes of Foundations of Information, Networks and Decision Systems. Talks are about 50 minutes long with time for questions and discussion.
Location: Cornell Tech (201 Bloomberg) and Zoom
Time: 4:15PM ET, bi-weekly on (alternating) Thursdays
Delivery format: All talks will have a live audience in Rhodes Hall 310. Until circumstances allow otherwise, external speakers will give the talk remotely via Zoom (broadcasted in RH310). Remote audience is also welcome, but in-person participation is encouraged.
Mailing list: To subscribe to the FIND seminar mailing list, email find-seminar-l-request@cornell.edu, with “join” in the subject line and a blank email body. All talks info and reminders will be sent via the mailing list.
Upcoming Talk
Title: Emerging computational imaging inverse problems: from theory to algorithms
Speaker: Shirin Jalali
Date and Time: 04/25/2024 4:15PM ET
Location: Cornell Tech (201 Bloomberg) and Zoom
Please note that this week’s talk is at a different location than usual.
Abstract:
In this talk, I will focus on two challenging imaging systems: snapshot compressive imaging and coherent imaging under speckle noise interference. I will begin by reviewing the core mathematical modeling of the inverse problem corresponding to each system. I will develop a maximum likelihood estimator (MLE)-based optimization for each, employing untrained neural networks (NNs) to model the source structure. Theoretical analysis of the MLE-based methods will be shown to enable, on one hand, an understanding of the fundamental limits of these systems and, on the other hand, optimization of the image recovery algorithms and hardware. I will also discuss our proposed algorithms that merge classic bagging ideas with untrained neural networks for solving the inverse problems in these imaging systems. For each application, I will demonstrate how our method achieves state-of-the-art performance.
Schedule for Spring 2024:
A list of previous talks can be found here.