Haitian
Scientific Society Seminar
Series
Saturday December 7, 2024
12:45-2:30
Zoom-Link: https://umassboston.zoom.us/j/94777986513
https://www.haitianscientificsociety.org/
Modern Radars: Challenges and Signal Processing
Webert Montlouis, PhD
Fellow of the IEEE, AAIA, AIIA
Webert_montlouis@ieee.org
Abstract: In the past decade, advances in Analog-to-Digital Converters
(ADCs) have led to significantly higher sampling rates, reducing the need for
multiple down-conversion stages. Simultaneously, computational infrastructures,
including parallel processing and Graphics Processing Units (GPUs), have
evolved rapidly, enabling more robust system designs. However, these advances
also generate massive datasets, which, if not managed effectively, can create
bottlenecks in data and signal processing. Traditional signal processing
methods struggle to keep up with these high data rates, creating a pressing
need for techniques that can efficiently extract relevant information from such
data streams.
Trained
deep learning networks excel in swiftly extracting key features from complex
datasets, making them a cutting-edge approach to addressing the demands of
high-rate data sensing and processing. In this talk, we will explore a proposed
architecture designed to manage high data volumes, sense relevant features from
the datasets, and address emerging challenges in radar signal processing.
Bio: Webert Montlouis (FIEEE) received
his BS, MS, and PhD in electrical and computer engineering from Northeastern
University, Boston, MA, USA. He is currently at Johns Hopkins University,
Baltimore, MD. He has served as Chief Scientist at the Applied Physics
Laboratory (APL) and faculty in the Electrical and Computer Engineering
department. He has been the chair of the IEEE Massive MIMO standard development
working group. He is also the co-chair of the Massive MIMO working group. He
has been the general co-chair of the IEEE Massive MIMO workshop and session
chair for many IEEE conferences. He is a vice chair for Trustworthy Internet of
Things (TRUST-IoT). His research interests include Multi-Channel System
Architecture, Sensing, Next Generation Radar Systems, Wireless Communications
5G and Beyond, Quantum Information Science, Digital Signal Processing, and
Biomedical Signal Processing. He is a Fellow of the IEEE, AAIA, AIIA, and a
member of the IEEE Signal Processing Society and the IEEE Communications
Society.
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