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Events for September 28, 2022
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Viterbi Career & Internship Expo: Career Fair (On-Campus)
Wed, Sep 28, 2022 @ 10:00 AM - 03:00 PM
Viterbi School of Engineering Career Connections
Receptions & Special Events
Viterbi Career Connections is excited to announce the Fall 2022 Career & Internship Fair will be hosted on-campus! This recruitment event allows students the opportunity to have brief conversations with recruiters about full-time employment, internships, and co-ops. Join additional activities such as Trojan Talks and Meet & Greets September 26th-27th.
The Viterbi Career & Internship Expo is free and open to all students in the USC Viterbi School of Engineering. Don't forget your resume!
For more information about the Expo: https://viterbicareers.usc.edu/careerexpo/Location: Trousdale Parkway
Audiences: All Viterbi Students
Contact: RTH 218 Viterbi Career Connections
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Medical Imaging Seminar Series
Wed, Sep 28, 2022 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Rodrigo A. Lobos, Electrical and Computer Engineering, University of Southern California
Talk Title: New Theory and Methods for Accelerated MRI Reconstruction
Series: Medical Imaging Seminar Series
Abstract: Magnetic resonance imaging (MRI) has revolutionized medicine by providing high-quality images of living tissue in a safe and noninvasive manner. However, the data-acquisition time can still be restrictively long in real applications. To accelerate this task, one popular alternative has been acquiring a reduced amount of data samples, and then using reconstruction methods to generate images out of the acquired undersampled data. In this talk we discuss novel contributions to improve the performance and efficiency of MRI reconstruction methods.
We start revisiting the shift-invariant linear predictability relationships that exist in the MRI data (k-space), and how they can be leveraged using structured low-rank modeling (SLM). Then, we propose novel reconstruction approaches based on SLM which additionally incorporate in-prior knowledge learned from previously acquired reference data. We show that this approach is particularly useful in the context of ghost-artifact correction in echo planar imaging (EPI), where we theoretically establish that in-prior knowledge is necessary in order to avoid ill-posedness when using SLM reconstruction methods. Next, we provide a robust and powerful SLM reconstruction method able to account for potential imperfections in the reference data.
In the last part of the talk, we show that linear predictability principles can also be used in the context of sensitivity map estimation in multichannel MRI. We start showing new theoretical results that provide a novel mathematical description for the estimation problem. Specifically, we show that sensitivity maps at particular locations belong to a nullspace of a matrix created from linear predictability relationships. Then, based on advanced signal processing techniques, we propose a set of computational methods which allow massive improvements in the computational complexity of sensitivity map estimation methods based on subspaces. We show cases where conventional estimation methods obtain a ~30-fold acceleration when combined with our proposed computational techniques. Notably, these improvements in computational time and memory usage are obtained without sacrificing estimation accuracy.
Biography: Rodrigo A. Lobos is a Ph.D candidate in Electrical and Computer Engineering at University of Southern California, supervised by Prof. Justin Haldar. He obtained his Bachelor's and Master's degree in Electrical Engineering at Universidad de Chile, where he received the Best Master's Thesis award in Electrical Engineering in 2015. During this time, The School of Engineers of Chile recognized Rodrigo as the best electrical engineer graduated from Universidad de Chile in 2015. He then joined Prof. Haldar's group at USC where his research has been focused on signal processing, computational imaging, and machine learning applied to medical imaging applications. Rodrigo's work has been recognized in distinguished medical imaging conferences, where he obtained a Best Paper Finalist award in IEEE ISBI 2020. At University of Southern California Rodrigo was selected as a Ming Hsieh Institute Ph.D Scholar.
Host: Justin Haldar, jhaldar@usc.edu
Webcast: https://urldefense.com/v3/__https://usc.zoom.us/j/94607557250__;!!LIr3w8kk_Xxm!uZV7rWNY9SZv84hGG8xVjIzaW-bOpw5wrC274dcH8O-_Ls5VS_GnF-W-kPDxVNU489rUSCih4KKPsjXwog$Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Talyia White
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New Theory and Methods for Accelerated MRI Reconstruction
Wed, Sep 28, 2022 @ 10:00 AM - 11:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Rodrigo Lobos , Electrical and Computer Engineering
Talk Title: Dissertation Defense
Host: Rodrigo Lobos
More Information: Rodrigo Lobos_MHI-MISS_Sept. 28, 2022.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Talyia White
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Computer Science General Faculty Meeting
Wed, Sep 28, 2022 @ 12:00 PM - 02:00 PM
Thomas Lord Department of Computer Science
Receptions & Special Events
Bi-Weekly regular faculty meeting for invited full-time Computer Science faculty only. Event details emailed directly to attendees.
Location: Ronald Tutor Hall of Engineering (RTH) - 526 - Hybrid
Audiences: Invited Faculty Only
Contact: Assistant to CS chair
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DEN@Viterbi Information Session - National Harbor, Maryland
Wed, Sep 28, 2022 @ 12:00 PM - 01:00 PM
DEN@Viterbi, Viterbi School of Engineering Graduate Admission
Workshops & Infosessions
Join USC Viterbi School of Engineering for an in-person information session in National Harbor, Maryland. The session will provide an introduction to DEN@Viterbi, our top ranked online delivery method and the 40+ graduate engineering and computer science programs available entirely online.
Attendees will have the opportunity to connect directly with a USC Viterbi representative during the session to discuss the enrollment options, admission process, program details, the benefits of online delivery, scholarships and more.
Register Today!Location: National Harbor, Maryland
WebCast Link: https://uscviterbi.webex.com/uscviterbi/onstage/g.php?MTID=e28f77d830a3209cadd75a8f880794f54
Audiences: Everyone Is Invited
Contact: Corporate & Professional Programs
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Center of Autonomy and AI, Center for Cyber-Physical Systems and the Internet of Things, and Ming Hsieh Institute Seminar Series
Wed, Sep 28, 2022 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Giulia Pedrielli, School of Computing and Augmented Intelligence (SCAI) at Arizona State University.
Talk Title: Going Inside the Box: Bayesian Optimization for Verification of Cyber Physical Systems with Varying Levels of System Knowledge
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: Systems across automotive, bio-pharma, aerospace, energy, have become increasingly complex, and simulation represents a standard tool to evaluate their performance independently from the purpose of the analysis being optimization, control, certification. As a result, black-box optimization, that can embed simulation to perform a wide range of analyses, has attracted a lot of attention from the science and engineering communities. This talk centers around Black-box optimization methods, focusing on random search approaches (such randomness is injected in the search independently from the problem being affected by noise) in the broad area of verification of Cyber Physical Systems. In this context, the problem of falsifying properties is translated into the minimization of a robustness function. This is a metric function that quantifies how far a CPS execution is from violating a property of interest.
We first focus on control and acceleration of the explore/exploit process for the falsification of safety requirements without exploiting any property of the system under analysis. Our approach alternates local and global search using local knowledge while exploring the space of possible solutions. The performance of the proposed approach is analyzed, and key future directions are discussed in the context of Cyberphysical systems safety evaluation.
In the second part of the talk, we present algorithms developed in the scope of certification of safety critical systems that in some form exploit some structure of the problem at hand. Part-X is a family of partitioning informed Bayesian optimizers that can identify regions in which the system can present safety concerns (bugs in the case a software is analyzed). In this sense, the algorithm learns structure of the robustness function used to find falsification. We also produce a global estimate of the falsification volume. The algorithm min-BO works to identify faults in systems that have complex requirements that can be decomposed into a set of simpler requirements that need to be simultaneously satisfied by the system (conjunctive requirements). Finally, we show the basic ideas behind the design of algorithms that can exploit, when available, instrumented source code for the CPS to verify.
Biography: Giulia Pedrielli (https://www.gpedriel.com/) is currently Associate Professor for the School of Computing and Augmented Intelligence (SCAI) at Arizona State University. She graduated from the Department of Mechanical Engineering of Politecnico di Milano. Giulia develops her research in design and analysis of random algorithms for global optimization, with focus on improving finite time performance and scalability of these approaches. Her work is motivated by design and control of next generation manufacturing systems in bio-pharma and aerospace applications, as well as problems in the design and evaluation of complex molecular structures in life-science. Applications of her work are in individualized cancer care, bio-manufacturing, design and control of self-assembled RNA structures, verification of Cyberphysical systems. Her research is funded by the NSF, DHS, DARPA, Intel, Lockheed Martin.
Host: Pierluigi Nuzzo, nuzzo@usc.edu
Webcast: https://usc.zoom.us/j/98083929768?pwd=SUJreHk0N0ZXbk5QZ1ZPUkRlM3FmZz09Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
WebCast Link: https://usc.zoom.us/j/98083929768?pwd=SUJreHk0N0ZXbk5QZ1ZPUkRlM3FmZz09
Audiences: Everyone Is Invited
Contact: Talyia White
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AME Seminar
Wed, Sep 28, 2022 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Jerry Qi, Georgia Tech
Talk Title: Multimaterial Additive Manufacturing toward Shape Changing Functional Devices and 4D Printing
Abstract: 3D printing (additive manufacturing) where materials are deposited in a layer-by-layer manner to form a 3D solid has seen significant advances in the recent decades. 3D printing has the advantage in creating a part with complex geometry from a digit file, making them an idea candidate for making architected materials. Multimaterial 3D printing is an emerging field in recent years in additive manufacturing. It offers the advantage of placement of materials with different properties in the 3D space with high resolution, or controllable heterogeneity. In this talk, we present our recent progress in developing multimaterial additive manufacturing methods. In the first approach, we present a new development of a novel multi-material multi-method (m4) 3D printing where we integrate four types of additive manufacturing methods and two complementary methods into one platform. In the second approach, we recently developed a novel grayscale digit light processing (DLP) 3D printing method where we can print a part with gradient material properties. We further explore on how to use multimaterial 3D printing to fabricate architected materials and demonstrate their advantage, including direct 4D printing of 2D lattice structures, lattice structures with changing shape driven by liquid crystal elastomers, and 3D lattice structures by gradient materials.
Biography: Dr. H. Jerry Qi is a professor in the School of Mechanical Engineering at Georgia Institute of Technology and is the site director of NSF IUCRC on Science of Heterogeneous Additive Printing of 3D Materials (SHAP3D). He received his undergraduate and graduate degrees from Tsinghua University and a ScD degree from MIT. After one-year postdoc at MIT, he joined University of Colorado Boulder as an assistant professor and moved to Georgia Tech in 2014. His research is in the broad field of nonlinear mechanics of polymeric materials and focuses on developing fundamental understanding of multi-field properties of soft active materials through experimentation and constitutive modeling then applying these understandings to application designs. He and his collaborators have been working on a range of soft active materials, including shape memory polymers, shape memory elastomeric composites, light activated polymers, covalent adaptable network polymers, for their interesting behaviors such as shape memory, light actuation, surface patterning, surface welding, healing, and reprocessing. In recent years, he has been working on investigating integrating active materials with 3D printing. He and his collaborators pioneered the 4D printing concept. Prof. Qi is a recipient of NSF CAREER award (2007) and was elected to an ASME Fellow in 2015.
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Webcast: https://usc.zoom.us/j/98775609685?pwd=a2lSd01oY0o2KzA4VWphbGxjWk5Qdz09Location: Seaver Science Library (SSL) - 202
WebCast Link: https://usc.zoom.us/j/98775609685?pwd=a2lSd01oY0o2KzA4VWphbGxjWk5Qdz09
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://ame.usc.edu/seminars/
