SUNMONTUEWEDTHUFRISAT
Events for March 25, 2024
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ECE Seminar: Dr. Guanghan Meng, "Capturing Life: Optical Microscopy for in vivo Deep Tissue Imaging at High Spatiotemporal Resolution"
Mon, Mar 25, 2024 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Guanghan Meng, Postdoctoral Scholar, Dept of EECS, UC Berkeley
Talk Title: Capturing Life: Optical Microscopy for in vivo Deep Tissue Imaging at High Spatiotemporal Resolution
Abstract: Optical microscopy has become an indispensable tool for non-invasive, high-resolution in vivo imaging of living organisms. Its capability to provide insights into real-time physiological and pathological processes within the body underscores its significance in bioscience and medicine. However, conventional optical microscopy methods have certain limitations. For instance, multiphoton fluorescence microscopy, the method of choice for in vivo imaging through scattering tissue such as the mammalian brains, delivers excellent resolution but falls short in speed for capturing rapid biological activities, such as blood flow dynamics. On the other hand, optical coherence tomography (OCT), a label-free deep-tissue imaging method, stands as a powerful instrument in contemporary optometry clinics, but its high cost limits its broad use, especially in lower-income communities. In this presentation, I will share my research on the development of high-speed multiphoton fluorescence microscopy and cost-effective OCT for brain and eye imaging, respectively, through the utilization of both optical engineering and computational methods.
Biography: Dr. Guanghan Meng, currently a postdoctoral scholar in the Department of Electrical Engineering and Computer Science at the University of California, Berkeley, focuses on advancing high-speed, high-resolution fluorescence, and label-free microscopy technologies for deep tissue imaging in vivo. Having earned her PhD from the same university, her doctoral research spanned the disciplines of Molecular and Cell Biology and Physics, primarily concentrating on enhancing two-photon fluorescence microscopy for mouse brain imaging. At present, she is working on computational label-free imaging with a specific interest in the human eye. Guanghan has been recognized with various best presentation awards at scientific conferences and is a recipient of the Berkeley Center for Innovation in Vision and Optics (CIVO) postdoctoral fellowship. Guanghan is also an invited lecturer at the 17th Edition of the Frontiers in Neurophotonics Summer School in Quebec City, Canada in 2024.
Host: Dr. Justin Haldar, jhaldar@usc.edu
Webcast: https://usc.zoom.us/j/96234786783?pwd=eXF0NnlvNEhPRHllS1NDUEFZWklSdz09Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
WebCast Link: https://usc.zoom.us/j/96234786783?pwd=eXF0NnlvNEhPRHllS1NDUEFZWklSdz09
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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CSC/CommNetS-MHI Seminar: Chandra Murthy
Mon, Mar 25, 2024 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Chandra Murthy, Professor, Department of Electrical Communication Engineering | Indian Institute of Science, Bangalore, India
Talk Title: Sparsity-aware Bayesian Inference and its Applications
Series: CSC/CommNetS-MHI Seminar Series
Abstract: This talk presents a set of tools based on a Bayesian framework to address the general problem of sparse signal recovery, and discusses the challenges associated with them. Bayesian methods offer superior performance compared to convex optimization-based methods and are largely parameter tuning-free. They also have the flexibility necessary to deal with a diverse range of measurement modalities and structured sparsity in signals than hitherto possible. We discuss recent developments towards providing rigorous theoretical guarantees for these methods. Further, we show that, by re-interpreting the Bayesian cost function as a technique to perform covariance matching, one can develop new and ultra-fast Bayesian algorithms for sparse signal recovery. As example applications, we discuss the utility of these algorithms in the context of (a) 5G communications with several case studies such as wideband time-varying channel estimation, low-resolution ADCs, etc, and (b) controllability and observability of linear dynamical systems under sparsity constraints.
Biography: Chandra R. Murthy is a professor in the department of Electrical Communication Engineering at the Indian Institute of Science, Bangalore, India. His research interests are in sparse signal recovery, energy harvesting-based communication, performance analysis, and optimization of 5G and beyond communications. Papers coauthored by him have received Student/Best Paper Awards at the NCC 2014, IEEE ICASSP 2018, IEEE ISIT 2021, IEEE SPAWC 2022, and NCC 2023. He is a senior area editor for the IEEE Transactions on Signal Processing and the IEEE Transactions on Information Theory. He is an elected member of the IEEE SPS SAM Technical Committee. He is an IEEE Fellow (Class of 2023), and a fellow of the Indian National Academy of Engineering (2023).
Host: Dr. Urbashi Mitra, ubli@usc.edu
More Information: 2024.03.25 CSC Seminar - Chandra Murthy.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
Audiences: Everyone Is Invited
Contact: Miki Arlen
