Webinar Details

Friday, February 23, 2024

Join us for our upcoming YOUser webinar titled Optimizing Sparse Interactions for Control and Sensing in Complex Networks hosted by Assistant Professor, Department of Electrical and Computer Engineering, Northeastern University, Dr. Milad Siami. This webinar promises to delve into cutting-edge techniques aimed at minimizing resource usage to enhance system performance, with a particular emphasis on addressing the challenges of non-submodular sensor scheduling in large-scale linear time-varying dynamics.

In this webinar, Dr. Siami will navigate intricate topics, starting from simple greedy algorithm and progressing to more advanced discussions surrounding approximation bounds based on submodularity and curvature principles. By showcasing the superiority of these approaches over existing methods, attendees will gain valuable insights into tackling combinatorial, non-convex, NP-hard tasks effectively.

Furthermore, the webinar will explore the application of graph-theoretic principles in the context of discrete-time autonomous vehicle platoons. Dr. Siami will analyze stability conditions based on underlying graph properties and update cycles, while also delving into H2-based robustness considerations. Through practical examples and results derived from simulations and experiments, including collaborations with industry-leading platforms such as Quanser’s Qlabs and QCar, attendees will witness firsthand the effectiveness of strategic sensor scheduling and robust design in autonomous vehicle platoons. This webinar will offer a unique opportunity to deepen your understanding of innovative strategies in control and sensing within large-scale complex networks.

Join us on Friday, February 23, 2024 at 2 pm EST for Optimizing Sparse Interactions for Control and Sensing in Complex Networks webinar.


Presenter’s Bio

Dr. Milad Siami

Milad Siami is an Assistant Professor in the Department of Electrical and Computer Engineering at Northeastern University and a Core Faculty Member of the Institute for Experiential AI at the same institution. Prior to joining Northeastern, he served as a Postdoctoral Associate at the MIT Institute for Data, Systems, and Society. He earned his M.Sc. and Ph.D. degrees in Mechanical Engineering from Lehigh University and was a long-term visiting researcher at the Institute for Mathematics and Its Applications at the University of Minnesota. Additionally, he has experience as a Software Engineering Research Intern in the Modeling and Data Mining Group at Google Research NYC.

Dr. Siami’s research primarily focuses on the structural/graphical underpinnings of large-scale dynamical networks and enhancing the reliability and security of AI-based autonomous systems. His specific areas of interest include distributed control systems, multi-robot systems, and autonomous networks. His current research is supported by grants from the National Science Foundation (NSF), the Department of Homeland Security (DHS), the Office of Naval Research (ONR), and the Army Research Laboratory (ARL).