[AI Seminar Series] Seminar by Prof. Vishwanath Saragadam, Friday May 30, 12-1pm, MRB Seminar Room

[Vassilis Tsotras]

Colleagues,
the next AI Seminar will be on Friday May 30, 12:00-1:00pm at the MRB 
Seminar Room (1st floor).

**** Pizza and refreshments will be provided ****

To keep track of the number of attendees, please *register* at:
https://www.eventbrite.com/e/ai-seminar-series-tickets-1379917031989

The talk will be given by Prof. Vishwanath Saragadam, Department of 
Electrical and Computer Engineering, UCR

TITLE:
"Non-Linear Signal Processing with Implicit Neural Representations"


ABSTRACT:
Implicit neural representations (INRs) are a powerful family of 
continuous learned function approximators for signal data that are 
implemented using multilayer perceptron (MLP). INRs enable a non-linear 
signal representation of bases functions that are generated by scaling 
and shifting the activation function. Inspired by this insight, this 
talk will focus on the role played by the activation function, and the 
weights and biases of INRs. I will first focus on development of wavelet 
INRs (or WIRE) for highly robust representations for visual data such as 
images and videos. Second, I will talk about how the weights and biases 
of an INR can be modulated to efficiently and continuously represent 
videos, and thereby generate slo-mo videos without any external 
supervision, underscoring the importance of INRs as a powerful signal 
processing tool. The talk will focus on applications in CT 
reconstruction, low-level image processing, video processing, and 
solving inverse problems with meta-optics.


Bio:
Vishwanath Saragadam is an Assistant Professor in the Department of 
Electrical and Computer Engineering (ECE) at the University of 
California Riverside where he leads the computational optics and display 
engineering (CODE) lab. Vishwanath received his Ph.D. from Carnegie 
Mellon University in ECE, and was a postdoctoral researcher at Rice 
University. He is a recipient of an outstanding postdoctoral researcher 
award in 2023, best paper award at ICCP in 2022, and outstanding thesis 
award in 2021. His research focus includes meta-optics, hyperspectral 
imaging, thermal imaging, and self-supervised algorithms for linear 
inverse problems.

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Sponsored by the RAISE at UCR Institute, the AI Seminar Series presents 
speakers working on cutting edge Foundational AI or apply AI in their 
research. The goal of these seminars is to inform the UCR community 
about current trends in AI research and promote collaborations between 
faculty in this emerging field.
These seminars are open to interested faculty and graduate students. 
Please forward this email to other colleagues or graduate students in 
your lab that may be interested. After the seminar a discussion will 
follow for questions, open problems, ideas for possible collaborations 
etc.

Sincerely,
Vassilis Tsotras
Professor, CSE Department
co-Director, RAISE at UCR Institute

Amit Roy-Chowdhury
Professor, ECE Department
co-Director, RAISE at UCR Institute
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