Title: Statistical Graph Signal Processing with Applications to Smart Grids
Abstract: Graphs are fundamental mathematical structures that are widely used in various fields for network data analysis to model complex relationships within and between data, signals, and processes. In particular, graph signals arise in many modern applications, leading to the emergence of the area of graph signal processing (GSP) in the last decade. GSP theory extends concepts and techniques from traditional digital signal processing (DSP) to data indexed by generic graphs, including the graph Fourier transform (GFT), graph filter design, and sampling and recovery of graph signals. However, most of the research effort in this field has been devoted to the purely deterministic setting. In this study, we consider the extension of statistical signal processing (SSP) theory by developing graph SSP (GSSP) methods and bounds. Special attention will be given to the development of GSP methods for monitoring the power systems, which has significant practical importance, in addition to its contribution to the enrichment of theoretical GSSP tools. In particular, we will discuss the following problems (as time permits): 1) Bayesian estimation of graph signals in non-linear models; 2) the identification of edge disconnections in networks based on graph filter representation; 3) the development of performance bounds, such as the well-known Cramér-Rao bound (CRB), on the performance in various estimation problems that are related to the graph structure; 4) the detection of false data injected (FDI) attacks on the power systems by GSP tools; 5) Laplacian learning with applications to admittance matrix estimation. The methods developed in these works use GSP concepts, such as graph spectrum, GSP, graph filters, and sampling over graphs.
Biography: Tirza Routtenberg is an Associate Professor in the School of Electrical and Computer Engineering at Ben-Gurion University of the Negev, Israel. She also serves as the William R. Kenan, Jr., Visiting Professor for Distinguished Teaching in the Electrical and Computer Engineering Department at Princeton University for the 2022-2023 period. Routtenberg has been honored with four Best Student Paper Awards at international conferences. Currently, she is an Associate Editor for both the IEEE Transactions on Signal and Information Processing Over Networks and the IEEE Signal Processing Letters. Additionally, she represents the SPS Technical Directions Board on the Education Board. Her research focuses on statistical signal processing, graph signal processing, and optimization and signal processing for smart grids.
Title: The Art of Marriage: How to Integrate Data Communications and Radar Sensing?
Abstract: Joint communications and sensing (JCS), a.k.a. Integrated Sensing and Communications (ISAC), are expected to be a featuring technology in 6G wireless communication networks. It improves the efficiencies of spectrum and energy by sharing the same waveform for both tasks of communications and sensing. The waveform in JCS could be traditional communication waveforms (such as OFDM) or existing radar waveforms (such as FMCW). In this talk, we will discuss waveform design dedicated for JCS, which may go beyond existing waveform designs for individual systems. We focus on two questions, for the marriage of communications and sensing: (a) How to design a natural and enlightening framework for integrating both communications and sensing? To this end, we propose to consider JCS as a broadcast and thus unify several major designs within the same framework. (b) How to characterize the conflict and trade-off between communications and sensing when they are integrated within the same waveform? We will examine several types of conflict, such as randomness-determinism, environmental complexity, and coding-spreading trade-offs. Finally, I will provide an overview on my future research in the area of JCS.
Biography: Husheng Li received his BS and PhD degrees, both in electrical engineering, from Tsinghua University (1998) and Princeton University (2005), respectively. He joined Qualcomm Inc. as a senior engineer after his graduation from Princeton. In 2007, he joined the EECS department of the University of Tennessee, Knoxville, where he was promoted to associated professor and full professor in 2013 and 2019, respectively. In 2022, he joined Purdue University, affiliated in both the School of Aeronautics and Astronautics and the Elmore School of Electrical and Computer Engineering. His research interest includes wireless communications, statistical signal processing, cyber physical systems, networked control, and information theory. He has received numerous best paper awards in journals such as the EURASIP Journal on Wireless Communications and Networking (2015) and conferences such as IEEE ICC (2012) and Globecom (2017).