DCL Seminar: Jr-Shin Li - Targeted Coordination of Dynamic Populations: Decoding and Engineering Dynamic Structures
Decision and Control Lecture Series
Coordinated Science Laboratory
“Targeted Coordination of Dynamic Populations:
Decoding and Engineering Dynamic Structures”
Jr-Shin Li, Ph.D.
Washington University
Wednesday, November 29, 2017
3:00 p.m. to 4:00 p.m.
CSL Auditorium (B02)
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Abstract:
Natural and engineered systems that consist of populations of isolated or interacting dynamical components exhibit levels of complexity that are beyond human comprehension. These complex systems often require an appropriate excitation, an optimal hierarchical organization, or a periodic dynamical structure, such as synchrony, to function as desired or operate optimally. In many applications, the dynamics of such ensemble systems can be regulated by the application of a single or sparsely distributed external inputs in order to alter their state configurations or dynamic structures; for example, the application of electromagnetic fields to excite quantum ensembles in nuclear magnetic resonance spectroscopy and imaging, the modulation of light protocol to adjust clocks of a population of circadian cells in chronobiology, and invasive and noninvasive neurostimulation to desynchronize a population of pathologically synchronized neurons for the treatment of neurological disorders, such as Parkinson's disease or epilepsy, in brain medicine. This unconventional control paradigm gives rise to challenging problems regarding robust broadcast control and computation for underactuated dynamic populations. Moreover, valid and precise models for describing the dynamics of such complex systems are often elusive, while the measurement time-series data are available.
In this talk, I will address theoretical and computational challenges for targeted coordination of both isolated and networked population systems, for example, for engineering dynamic structures and controlling collective behavior, through various compelling applications. I will introduce both data-driven and model-based approaches for learning, decoding, control, and computation of dynamic structures and patterns in population systems. Practical control designs, including synchronization waveforms for pattern formation in nonlinear oscillator networks and optimal pulses in quantum control will be illustrated along with their experimental realizations.
Bio:
Dr. Jr-Shin Li is currently Das Family Distinguished Career Development Associate Professor of Systems Science and Mathematics in the Department of Electrical and Systems Engineering at Washington University in St. Louis, where he also holds a joint appointment in the Division of Biology \& Biomedical Sciences since he joined Washington University in 2006. Dr. Li holds a BS and an MS degree from National Taiwan University, and a PhD in Applied Mathematics from Harvard University in 2006. His research interests lie in the areas of systems, computational, and data sciences with broad applications to biology, neuroscience, quantum physics, and public health. He is a recipient of the NSF Career Award in 2008 and the AFOSR Young Investigator Award in 2010. He is currently Associate Editor of the SIAM Journal on Control and Optimization and Associate Editor of the IEEE Transactions on Control Systems Technology.