October 17, 2019
Location: 750 CEPSR
Speaker: Paul Bogdan, Associate Professor, Ming Hsieh Department of Electrical and Computer Engineering, USC
A large variety of time-varying complex networks (TVCNs) are characterized by multiscale nonlinear interactions with correlated dynamics and occurring between more than two nodes. Moreover, in many practical situations we can only partially observe the dynamics of TVCNs. When mining the TVCN's structure and dynamics, we also have to overcome various malicious interventions that can hide nodes and causal interactions transiently or permanently. Similar to brain networks or quantum gravity investigations, understanding the multiscale dynamics of TVCNs, detecting signs of instability hidden in noisy data and predicting the rare extreme events in TVCNs calls for radical mathematical and algorithmic tools to analyze the geometry of TVCN’s spacetime interdependence. In this talk, we will discuss our work on identifying the unknown unknowns (unknown stimuli and unobserved variables) that allow us to reconstruct TVCNs from various heterogeneous data, model their fractal spatiotemporal dynamics through fractional differential equations and show how concepts from multifractal and differential geometry can help us to analyze and mine the complexity of TVCNs.
Paul Bogdan is an associate professor in the Ming Hsieh Department of Electrical and Computer Engineering at University of Southern California. He received his Ph.D. degree in Electrical & Computer Engineering at Carnegie Mellon University. His work has been recognized with a number of honors and distinctions, including the 2017 Defense Advanced Research Projects Agency (DARPA) Young Faculty Award, 2017 Okawa Foundation Award, 2015 National Science Foundation (NSF) CAREER Award, the 2012 A.G. Jordan Award from Carnegie Mellon University for an outstanding Ph.D. thesis and service, and several best paper awards. His research interests include the theoretical foundations of cyber-physical systems, the control of complex time-varying interdependent networks, the modeling and analysis of biological systems and swarms, new control algorithms for dynamical systems exhibiting multi-fractal characteristics, modeling biological / molecular communication, the development of fractal mean field games to model and analyze biological, social and technological system-of-systems, performance analysis and design methodologies for manycore systems.
Hosted by Aurel A. Lazar
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