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Events for May 30, 2023
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Traffic Flow of Urban Air Mobility: Modeling, Control, and Simulation
Tue, May 30, 2023 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Jack Haddad, Associate Professor of Transportation Engineering with the Civil and Environmental Engineering faculty, the Technion -“ Israel Institute of Technology
Talk Title: Traffic Flow of Urban Air Mobility: Modeling, Control, and Simulation
Abstract: In this talk, we will focus on traffic flow modeling, control, and simulation of urban air mobility. The imminent penetration of low-altitude passenger and delivery aircraft into the urban airspace will give rise to new urban air transport systems, which we call low-altitude air city transport (LAAT) systems. As the urban mobility revolution approaches, we must investigate (i) the individual and collective behavior of LAAT aircraft in cities, and (ii) ways of controlling LAAT systems. Future LAAT systems exemplify a new class of modern large scale engineering systems -” networked control systems. They are spatially distributed, consist of many interconnected elements with control loops through digital communication networks such that the system signals can be exchanged among all components through a common network. Therefore, a decentralized controller design in framework of the unilateral event-driven paradigm is considered. Inspired by controlled urban road networks, in this talk we first establish the concept of Macroscopic Fundamental Diagram (MFD) for LAAT systems and develop a collective and aggregate aircraft traffic flow model. Then, based on that, we design an adaptive boundary feedback flow control which is robust to various anomalies in technical devices and network communication links for LAAT systems.
Biography: Jack Haddad is an Associate Professor of Transportation Engineering with the Civil and Environmental Engineering faculty, the Technion -“ Israel Institute of Technology, and the Head of the Technion Sustainable Mobility and Robust Transportation (T-SMART) Laboratory. He received all his degrees B.Sc. (2003), M.Sc. (2006), and Ph.D. (2010) in Transportation Engineering from the Technion. He served as a post-doctoral researcher (2010-2013) at the Urban Transport Systems Laboratory (LUTS), EPFL, Switzerland. His current research interests include urban air mobility, autonomous vehicles, traffic flow modeling
and control, large-scale complex networks, advanced transportation systems management, and public transportation.
Dr. Haddad serves as an Associate Editor for two journals: Transportation Research Part C and IEEE Transactions on Intelligent Transportation Systems. He was a recipient of the European Union Marie Curie, Career Integration Grant (CIG), and a recipient of two Israel Science Foundation (ISF) grants. He is currently the head of the Technion Transportation Research Institute (TRI), and the Assistant to the Senior Executive Vice President for Equal Opportunities. He is also a Visiting Faculty Researcher at Google.
Host: Dr. Petros Ioannou, ioannou@usc.edu
Webcast: https://usc.zoom.us/j/94759707407?pwd=NGJOMERvNmlyWGtqRkh0dkdDc0dzZz09More Information: ECE-Controls_Seminar-2_Announcement.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
WebCast Link: https://usc.zoom.us/j/94759707407?pwd=NGJOMERvNmlyWGtqRkh0dkdDc0dzZz09
Audiences: Everyone Is Invited
Contact: Miki Arlen
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Nonlinear Small-Gain Theory for Networks and Control
Tue, May 30, 2023 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Zhong-Ping Jiang, Professor, New York University
Talk Title: Nonlinear Small-Gain Theory for Networks and Control
Abstract: The world is nonlinear and linked. Small-gain theory is one of the most important tools to tackle fundamentally challenging control problems for interconnected nonlinear systems. In this talk, I will first review early developments in nonlinear small-gain theorems and associated nonlinear control design and show how it served as a basic tool to unify numerous results in constructive nonlinear control. Then, I will present recent developments in network/cyclic small-gain theorems for complex large-scale nonlinear systems, with applications to networked and event-triggered control under communications and computation constraints. Finally, I will discuss briefly how machine learning techniques can be invoked to relax the conservativeness of small-gain designs, that falls into the emerging area of learning- based control, a new direction in control theory.
Biography: Zhong-Ping JIANG received the M.Sc. degree in statistics from the University of Paris XI, France, in 1989, and the Ph.D. degree in automatic control and mathematics from ParisTech-Mines (formerly called the Ecole des Mines de Paris), France, in 1993, under the direction of Prof. Laurent Praly.
Currently, he is a Professor of Electrical and Computer Engineering at the Tandon School of Engineering, New York University. His main research interests include stability theory, robust/adaptive/distributed nonlinear control, robust adaptive dynamic programming, reinforcement learning and their applications to information, mechanical and biological systems. In these fields, he has written six books and is the author/co-author of over 500 peer-reviewed journal and conference papers. Prof. Jiang is a recipient of the prestigious Queen Elizabeth II Fellowship Award from the Australian Research Council, CAREER Award from the U.S. National Science Foundation, JSPS Invitation Fellowship from the Japan Society for the Promotion of Science, Distinguished Overseas Chinese Scholar Award from the NSF of China, and several best paper awards. He has served as Deputy Editor- in-Chief, Senior Editor and Associate Editor for numerous journals. Prof. Jiang is a Fellow of the IEEE, IFAC, CAA and AAIA, a foreign member of the Academia Europaea (Academy of Europe) and is among the Clarivate Analytics Highly Cited Researchers. In 2022, he received the Excellence in Research Award from the NYU Tandon School of Engineering.
Host: Dr. Petros Ioannou, ioannou@usc.edu
Webcast: https://usc.zoom.us/j/99411640901?pwd=SjBXZmFjTis3QUZVK3EvOS9ialNWUT09More Information: ECE-Controls_Seminar-1_Announcement.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
WebCast Link: https://usc.zoom.us/j/99411640901?pwd=SjBXZmFjTis3QUZVK3EvOS9ialNWUT09
Audiences: Everyone Is Invited
Contact: Miki Arlen
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MoBI Seminar: Dr Annalisa Pascarella
Tue, May 30, 2023 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr Annalisa Pascarella, Senior Researcher, Institute of Applied Mathematics M. Picone | National Council of Research, Rome, Italy
Talk Title: New adventures in brain electromagnetism: From EEG source reconstruction to exploring the neural dynamics of meditation with MEG
Series: MoBI Seminar Series
Abstract: Electrical source imaging (ESI) is a key component in many EEG analysis pipelines, in both research and clinical settings. Different ESI methods mainly differ by the quality and quantity of a priori information used in the solution of the inverse problem. In this talk I'll present the main result of a recent study in which we compare in-vivo ten different ESI methods from the MNE-python package: wMNE, dSPM, sLORETA, eLORETA, LCMV, dipole fitting, RAP-MUSIC, MxNE, gamma map and Sesame. Exploiting a recently published HD scalp EEG dataset recorded at Niguarda Hospital (Milan, Italy) from Stereo-EEG implanted patients during Single Pulse Electrical Stimulation, the different inverse methods were compared under multiple choices of input parameters to assess the accuracy of the best reconstruction, as well as the impact of the parameters on the localization performance. In the second part of the talk, I'll present some preliminary results on an MEG dataset recorded in a group of expert Buddist monks during resting state (RS) and two different meditation practices: Samatha, a form of focused-attention meditation (FAM) and Vipassana that refers to open-monitoring meditation (OMM). Despite a flourishing body of research investigating the neural correlates of meditation, the underlying neural mechanisms that mediate the distinct processes associated with different forms of meditation are still poorly understood. Exploiting the high temporal resolution of MEG, the key questions we address focus on the characterization of changes in brain dynamics induced by different meditative states as evidenced by criticality and complexity measures.
Biography: Dr. Annalisa Pascarella is a senior researcher at Institute of Applied Mathematics M. Picone, National Council of Research since October 2011. Her main research interests are centered on the formulation, implementation and validation of computational methods for the solution of the MEG/EEG inverse problems with a focus on Bayesian methods to track neural activity. In the last years she has been involved in the development of Neuropycon, an open-source brain data analysis kit which provides reproducible Python-based pipelines for advanced multi-thread processing of fMRI, MEG and EEG data, with a focus on connectivity and graph analyses. Some of her recent projects include the classification of mental states from MEG measurements during various meditation techniques.
Host: Dr Richard Leahy, leahy@sipi.usc.edu | Dr Karim Jerbi, karim.jerbi.udem@gmail.com
Webcast: https://usc.zoom.us/j/91439298406?pwd=bUEvSjlqN1lTZ3lUSVFMbElEV0NVUT09More Information: MoBI Seminar - 2023.05.30 Annalisa Pascarella Flyer.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
WebCast Link: https://usc.zoom.us/j/91439298406?pwd=bUEvSjlqN1lTZ3lUSVFMbElEV0NVUT09
Audiences: Everyone Is Invited
Contact: Miki Arlen
