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X-WR-CALDESC:Events for Department of Electrical & Computer Engineering
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DTSTART;TZID=America/New_York:20210412T090000
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DTSTAMP:20260513T151939
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UID:4780-1618218000-1618221600@ece.northeastern.edu
SUMMARY:ECE PhD Dissertation Defense: Armin Moharrer
DESCRIPTION:PhD Dissertation Defense: Leveraging Structural Properties for Large-Scale Optimization \nArmin Moharrer \nLocation: Zoom Link \nAbstract: Large scale optimization problems abound in data mining\, machine learning\, and system design. We address the challenges posed by such large scale optimization problems by providing efficient optimization algorithms. The scope of studied problems is quite broad; it includes applications such as experimental design\, computing graph distances (dissimilarity scores)\, training auto-encoders\, multi-target regression\, and the design of cache networks. We leverage the structural properties present in these problems\, e.g.\, sparsity or separability. In particular\, we introduce some structural properties under which the Frank-Wolfe algorithm (FW) can be distributed over a cluster of computers. We show that the distributed FW running over 350 workers (CPUs) solves an instance of experimental design problem with 20M variables in 79 minutes\, while the serial implementation takes 48 hours. Furthermore\, we study a variant of FW for the design of cache networks. The problem is NP-hard\, but we achieve a $1-1/e$ approximation ratio\, by optimizing a non-convex relaxation via FW. We also propose a distributed Alternating Direction Method of Multipliers (ADMM) algorithm for computing graph distances. We observe speedups of 153 times when running over a cluster with 448 CPUs\, in comparison with running over 1 CPU\, for graphs with 2.4K nodes. Moreover\, we study applications of ADMM in solving robust variants of risk minimization problems; in these variants we replace the typically chosen mean squared error loss with a general lp norm. We combine model based optimization with ADMM to minimize the resulting non-smooth and non-convex objectives. We show that a stochastic variant of ADMM converges with the rate O(log T/T) and is highly efficient for optimizing the corresponding model functions.
URL:https://ece.northeastern.edu/event/ece-phd-dissertation-defense-armin-moharrer/
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DTSTART;TZID=America/New_York:20210412T150000
DTEND;TZID=America/New_York:20210412T160000
DTSTAMP:20260513T151939
CREATED:20210401T223643Z
LAST-MODIFIED:20210401T223643Z
UID:4822-1618239600-1618243200@ece.northeastern.edu
SUMMARY:ECE PhD Dissertation Defense: Neville Sun
DESCRIPTION:PhD Dissertation Defense: RF Magnetoelectric Devices for Communication\, Sensing\, and Power Electronics \nNeville Sun \nLocation: Zoom Link \nAbstract: A strong magnetoelectric (ME) coupling of layered magnetic/ferroelectric heterostructures can effectively convert energy between electric and magnetic fields. By utilizing strain mediated ME coupling\, it is possible to use an electric field to control magnetic film properties\, such as magnetization\, permeability\, and spin wave. Additionally\, an applied magnetic field can be used to control electric polarization. In this talk\, ME voltage tunable inductors and ME acoustically actuated mechanical antennas/sensors are demonstrated and analyzed with different heterostructure compositions and design considerations for improving device performance.\nThe first part examines a new class of voltage tunable magnetoelectric inductors with textured multiferroic cores consisting of a Metglas/piezoelectric laminate/Metglas composite for MHz adaptive power systems. These inductors demonstrate a large\, instantaneous\, and non-discrete tunable range with a wide operational frequency range from DC to 10 MHz. A tunable inductance range of up to 346% was achieved with an applied electric field of 24 kV/cm. However\, low voltage tunability is miniscule\, typically less than 6% at 30 V applied voltage. By optimizing the anisotropy of magnetoelastic stress\, a 50 um thick PMN-PT slab is shown to improve low voltage tuning by 6 times. These ME tunable inductors with low driving voltage provide adaptability for changing circuit conditions and are ideal for compact/lightweight power systems for electronic warfare and communication systems.\nThe second device of interest is a new MEMS ME antenna/sensor design based on the solidly mounted resonator (SMR) structure. The SMR replaces the freestanding membrane structure of a film-bulk acoustic resonator (FBAR) with a Bragg acoustic reflector for concentrated energy confinement while improving structural integrity and power handling. The antenna radiates using converse ME coupling physics while receiving and sensing EM waves by using direct ME coupling. A unique spin sprayed NiZn ferrite/AlN structure and performance characterization for arrayed resonators are presented. The acoustic resonance in the heterostructure films operates at UHF range for seamless on-chip integration with WiFi\, Bluetooth\, and GPS devices. The robust features of the sub-mm size SMR ME antenna are demonstrated in a miniature aerial drone communication system and provide a possible alternative for biomedical implantables for neurological studies.
URL:https://ece.northeastern.edu/event/ece-phd-dissertation-defense-neville-sun/
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DTSTART;TZID=America/New_York:20210412T150000
DTEND;TZID=America/New_York:20210412T170000
DTSTAMP:20260513T151939
CREATED:20210412T185039Z
LAST-MODIFIED:20210412T185039Z
UID:4835-1618239600-1618246800@ece.northeastern.edu
SUMMARY:ECE PhD Proposal Review: Murphy Wonsick
DESCRIPTION:PhD Proposal Review: Improving Human Robot Interaction through Extended Reality Technologies \nMurphy Wonsick \nLocation: Teams Link \nAbstract: Recent advancements in robotics have allowed robots to become capable enough to be used in a wide variety of domains\, such as manufacturing\, search-and-rescue\, and space exploration. However\, human-robot interaction with these systems are still primarily achieved using 2D devices\, such and laptops\, tablets\, and/or game controllers despite operating in a 3D world. And although these interfaces can be very capable in operating a robot\, they are often complex and require expert operators as well as extensive training. Extended reality technologies provide an opportunity to create more intuitive human-robot interaction by allowing operators to visualize and interact with 3D data in a 3D environment\, allowing for a more natural interaction. Usage of extended reality technologies in human-robot interaction though are still very limited. In this proposal\, I aim to investigate how to provide better experiences for humans in human-robot interaction using extended reality technologies. Focus will be spent on using virtual reality headset to create supervisory control interfaces for remote robot operation and augmented reality head-mounted displays to help facilitate communication in human-robot shared workspaces. The goal of this work is to move towards more intuitive and easy-to-use interfaces for human-robot interaction.
URL:https://ece.northeastern.edu/event/ece-phd-proposal-review-murphy-wonsick/
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