Monday, November 13, 2023 - 4:45pm
Event Calendar Category
LIDS Seminar Series
Speaker Name
Eduardo Sontag
Affiliation
Northeastern
Building and Room Number
32-155
This talk will focus on systems-theoretic and control theory tools that help characterize the responses of nonlinear systems to external inputs, with an emphasis on how network structure constrains finite-time, transient behaviors. Of interest are qualitative features that are unique to nonlinear systems, such as non-harmonic responses to periodic inputs or invariance to transformations on inputs. These properties play a key role as tools for model discrimination and reverse engineering in systems biology, as well as in characterizing robustness to disturbances. Our research has been largely motivated by biological problems at all scales, from the molecular (e.g., extracellular ligands affecting signaling and gene networks), to cell populations (e.g., resistance to chemotherapy due to systemic interactions between the immune system and tumors; drug-induced mutations; sensed external molecules triggering activations of specific neurons in worms), to interactions of individuals (e.g., periodic or single-shot non-pharmaceutical ``social distancing'' interventions for epidemic control and minimizing transient effects on hospital capacities; adaptive strategies for distancing mandates). Subject to time constraints, we'll briefly discuss some of these applications. Moreover, given the universality of control and dynamical systems concepts, there are shared principles that emerge from such applications, and the theoretical concepts and computational approaches developed can be expected to be relevant to other (non-biology) fields in which the effect of inputs and transient behaviors are of interest. In that regard, we will illustrate the use of input to state stability for studying the effect of perturbations of gradient flows for loss functions that satisfy a relaxed form of the Polyak-Łojasiewicz inequality, specifically when solving direct LQR problems and a simple model of neural network learning.
Eduardo D. Sontag received his Licenciado in Mathematics at the University of Buenos Aires (1972) and a Ph.D. in Mathematics (1977) under Rudolf E. Kalman at the University of Florida. From 1977 to 2017, he was at Rutgers University, where he was a Distinguished Professor of Mathematics and a Member of the Graduate Faculty of the Departments of Computer Science of Electrical and Computer Engineering and the Cancer Institute of NJ. He directed the undergraduate Biomathematics Interdisciplinary Major, the Center for Quantitative Biology, and was Graduate Director at the Institute for Quantitative Biomedicine. In January 2018, Dr. Sontag became a University Distinguished Professor in the Departments of Electrical and Computer Engineering and of BioEngineering at Northeastern University, where he is also affiliated with the Mathematics and the Chemical Engineering departments. Since 2006, he has been a Research Affiliate at the Laboratory for Information and Decision Systems, MIT, and since 2018 he has been the Faculty Member in the Program in Therapeutic Science at Harvard Medical School. His major current research interests lie in several areas of control and dynamical systems theory, systems molecular biology, cancer and immunology, machine learning, and computational biology. Sontag has authored over five hundred research papers and monographs and book chapters in the above areas with about 60,000 citations and an h-index of 106 (56 since 2018). He is a Fellow of various professional societies: IEEE, AMS, SIAM, and IFAC, and is also a member of SMB and BMES. He was awarded the Reid Prize in Mathematics in 2001, the 2002 Hendrik W. Bode Lecture Prize and the 2011 Control Systems Field Award from the IEEE, the 2022 Richard E. Bellman Control Heritage Award, the 2023 IFAC Triennial Award on Nonlinear Control, the 2002 Board of Trustees Award for Excellence in Research from Rutgers, and the 2005 Teacher/Scholar Award from Rutgers.