At the intersection of control engineering and signal processing sits the upcoming field of sparse control and state estimation of linear dynamical systems. It deals with linear dynamical systems with states or control inputs having a few nonzero entries compared to their dimensions. Several networks that model phenomena like disease or epidemic spreading in the human society, air or water pollution, and viruses spreading in computer and mobile phone networks are known to have a sparse initialization. Similarly, constraining the inputs to be sparse is often necessary to select a small subset of the available sensors or actuators at each time instant due to energy, bandwidth, or physical network constraints. Bringing together research from the classical control theory and compressed sensing, the talk presents a comprehensive overview and critical insights into the conceptual foundations of sparsity-constrained systems, including the formulation, theory, and algorithms.
Geethu Joseph received the B. Tech. degree in electronics and communication engineering from the National Institute of Technology, Calicut, India, in 2011, and the M. E. degree in signal processing and the Ph.D. degree in electrical communication engineering (ECE) from the Indian Institute of Science (IISc), Bangalore, in 2014 and 2019, respectively. She was a postdoctoral fellow with the department of electrical engineering and computer science, Syracuse University, NY, USA, from 2019 to 2021. She is currently an assistant professor in the circuits and systems group at the Delft University of Technology, Delft, Netherlands. Her research interests include statistical signal processing, network control, and machine learning. She holds 20+ peer-reviewed publications in the fields of signal processing, communications, and control theory. Dr. Joseph was awarded the Prof. I. S. N. Murthy Medal in 2014 for being the best M. E. (signal processing) student in the ECE dept., IISc, the 2020 SPCOM Best Doctoral Dissertation Award, and the Seshagiri Kaikini Medal for the best Ph.D. thesis of the ECE dept., at IISc for the year 2019-'20.