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Events for May 02, 2024

  • Repeating EventAircraft Accident Investigation AAI 24-4

    Thu, May 02, 2024 @ 08:00 AM - 04:00 PM

    Aviation Safety and Security Program

    University Calendar


    The course is designed for individuals who have limited investigation experience. All aspects of the investigation process are addressed, starting with preparation for the investigation through writing the final report. It covers National Transportation Safety Board and International Civil Aviation Organization (ICAO) procedures. Investigative techniques are examined with an emphasis on fixed-wing investigation. Data collection, wreckage reconstruction, and cause analysis are discussed in the classroom and applied in the lab.
    The USC Aircraft Accident Investigation lab serves as the location for practical exercises. Thirteen aircraft wreckages form the basis of these investigative exercises. The crash laboratory gives the student an opportunity to learn the observation and documentation skills required of accident investigators. The wreckage is examined and reviewed with investigators who have extensive actual real-world investigation experience. Examination techniques and methods are demonstrated along with participative group discussions of actual wreckage examination, reviews of witness interview information, and investigation group personal dynamics discussions.

    Location: WESTMINSTER AVENUE BUILDING (WAB) - Unit E

    Audiences: Everyone Is Invited

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    Contact: Daniel Scalese

    Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AAAI4

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  • Repeating EventSafety Management for Aviation Maintenance MAINT 24-2

    Thu, May 02, 2024 @ 08:00 AM - 04:00 PM

    Aviation Safety and Security Program

    University Calendar


    This course provides supervisors with aviation safety principles and practices needed to manage the problems associated with aircraft maintenance operations. In addition, it prepares attendees to assume safety responsibilities in their areas of operation. It does not teach aircraft maintenance and assumes the attendee has a maintenance background.

    Location: Century Boulevard Building (CBB) - 920

    Audiences: Everyone Is Invited

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    Contact: Daniel Scalese

    Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AMAINT2

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  • Computational Science Distinguished Seminar Series

    Computational Science Distinguished Seminar Series

    Thu, May 02, 2024 @ 09:30 AM - 10:30 AM

    USC School of Advanced Computing

    Conferences, Lectures, & Seminars


    Speaker: Yannis Kevrekidis, Johns Hopkins University

    Talk Title: No Equations, No Variables, No Space and No Time: Data and the Modeling of Complex Systems

    Abstract: I will give an overview of a research path in data driven modeling of complex systems over the last 30 or so years – from the early days of shallow neural networks and autoencoders for nonlinear dynamical system identification, to the more recent derivation of data driven “emergent” spaces in which to better learn generative PDE laws. In all illustrations presented, I will try to point out connections between the “traditional” numerical analysis we know and love, and the more modern data-driven tools and techniques we now have – and some mathematical questions they hopefully make possible for us to answer.

    Biography: Yannis Kevrekidis studied Chemical Engineering at the National Technical University in Athens. He then followed the steps of many alumni of that department to the University of Minnesota, where he studied with Rutherford Aris and Lanny Schmidt (as well as Don Aronson and Dick McGehee in Math). He was a Director's Fellow at the Center for Nonlinear Studies in Los Alamos in 1985-86 (when Soviets still existed and research funds were plentiful). He then had the good fortune of joining the faculty at Princeton, where he taught Chemical Engineering and also Applied and Computational Mathematics for 31 years; seven years ago he became Emeritus and started fresh at Johns Hopkins (where he somehow is also Professor of Urology). His work always had to do with nonlinear dynamics (from instabilities and bifurcation algorithms to spatiotemporal patterns to data science in the 90s, nonlinear identification, multiscale modeling, and back to data science/ML); and he had the additional good fortune to work with several truly talented experimentalists, like G. Ertl's group in Berlin. Currently -on leave from Hopkins- he works with the Defense Sciences Office at DARPA. When young and promising he was a Packard Fellow, a Presidential Young Investigator and the Ulam Scholar at Los Alamos National Laboratory. He holds the Colburn, CAST Wilhelm and Walker awards of the AIChE, the Crawford and the Reid prizes of SIAM, he is a member of the NAE, the American Academy of Arts and Sciences, and the Academy of Athens. 

    Host: The School of Advanced Computing

    More Info: https://sac.usc.edu/events/?hash=1m3nCA4M337

    Location: Michelson Center for Convergent Bioscience (MCB) - 101

    Audiences: Everyone Is Invited

    Contact: Tessa Yao

    Event Link: https://sac.usc.edu/events/?hash=1m3nCA4M337

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  • Machine Learning Center Seminar

    Thu, May 02, 2024 @ 12:00 PM - 01:00 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Pengtao Xie , Assistant Professor, Department of Electrical and Computer Engineering - University of California, San Diego

    Talk Title: Foundation Models and Generative AI for Medical Imaging Segmentation in Ultra-Low Data Regimes

    Abstract: Semantic segmentation of medical images is pivotal in disease diagnosis and treatment planning. While deep learning has excelled in automating this task, a major hurdle is the need for numerous annotated masks, which are resource-intensive to produce due to the required expertise and time. This scenario often leads to ultra-low data regimes where annotated images are scarce, challenging the generalization of deep learning models on test images. To address this, we introduce two complementary approaches. One involves developing foundation models. The other involves generating high-fidelity training data consisting of paired segmentation masks and medical images. In the former, our bi-level optimization based method can effectively adapt the general-domain Segment Anything Model (SAM) to the medical domain with just a few medical images. In the latter, our multi-level optimization based method can perform end-to-end generation of high-quality training data from a minimal number of real images. On eight segmentation tasks involving various diseases, organs, and imaging modalities, our methods demonstrate strong generalization performance in both in-domain and out-of-domain settings. Our methods require 8-12 times less training data than baselines to achieve comparable performance.

    Biography: Pengtao Xie is an assistant professor in the Department of Electrical and Computer Engineering at the University of California San Diego. His research interest lies in machine learning for healthcare. His PhD thesis was selected as a top-5 finalist for the Doctoral Dissertation Award of the American Medical Informatics Association (AMIA). He was recognized as Global Top-100 Chinese Young Scholars in Artificial Intelligence by Baidu, Tencent AI-Lab Faculty Award, Innovator Award by the Pittsburgh Business Times, Amazon AWS Machine Learning Research Award, among others. He serves as an associate editor for the ACM Transactions on Computing for Healthcare, senior area chair for AAAI, area chairs for ICML and NeurIPS, etc.

    Host: Machine Learning Center

    Location: Ronald Tutor Hall of Engineering (RTH) - 211

    Audiences: Everyone Is Invited

    Contact: Thomas Lord Department of Computer Science

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  • DEN@Viterbi - 'Limited Status: How to Get Started' Virtual Info Session

    Thu, May 02, 2024 @ 12:00 PM - 01:00 PM

    DEN@Viterbi, Viterbi School of Engineering Graduate Admission

    Workshops & Infosessions


    Join USC Viterbi for our upcoming Limited Status: How to Get Started Virtual Information Session via WebEx to learn about the Limited Status enrollment option. The Limited Status enrollment option allows individuals with an undergraduate degree in engineering or related field, with a 3.0 GPA or above to take courses before applying for formal admission into a Viterbi graduate degree program. USC Viterbi representatives will provide a step-by-step guide for how to get started as a Limited Status student and enroll in courses online via DEN@Viterbi as early as the Summer 2024 semester. 

    WebCast Link: https://uscviterbi.webex.com/weblink/register/r80d33c78db1dcbf7f1baca0b7fd56d3b

    Audiences: Everyone Is Invited

    Contact: Corporate & Professional Programs

    Event Link: https://uscviterbi.webex.com/weblink/register/r80d33c78db1dcbf7f1baca0b7fd56d3b

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  • PhD Thesis Defense - Matthew Ferland

    Thu, May 02, 2024 @ 12:00 PM - 02:00 PM

    Thomas Lord Department of Computer Science

    University Calendar


    PhD Thesis Defense: Matthew Ferland  
     
    Committee: Shanghua Teng (Chair), David Kempe, Jiapeng Zhang, Larry Goldstein (Math)      
     
    Title: Exploring the Computational Frontier of Combinatorial Games      
     
    Abstract: People have been playing games since before written history, and many of the earliest games were combinatorial games, that is to say, games of perfect information and no chance. This type of game is still widely played today, and many popular games of this type, such as Chess and Go, are some of the most studied games of all time. This proposed work resolves around a game-independent systemic study of these games. More specifically, computational properties involving evaluating mathematical analysis tools for combinatorial games, such as Grundy values and confusion intervals, as well as identifying what can be determined about these games using simple oracle models.

    Location: Henry Salvatori Computer Science Center (SAL) - 213

    Audiences: Everyone Is Invited

    Contact: CS Events

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  • Semiconductors & Microelectronics Technology Seminar - Ke Du, Thursday, May 2nd at 2pm in EEB 248

    Thu, May 02, 2024 @ 02:00 PM - 03:30 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Ke Du, UC Riverside

    Talk Title: Micro- and Nanofluidic Systems for Molecular Biosensing, Nanotoxicity, and Optogenetics

    Series: Semiconductors & Microelectronics Technology

    Abstract: Micro- and nanofluidic systems, in conjunction with biochemistry, microscopy, nanomaterials, and machine learning components, serve as potent tools with a wide array of applications in the biomedical field. These applications encompass crucial areas like molecular diagnosis, biophysics, and optogenetics. In this presentation, we shed light on an innovative pneumatic-controlled nano-sieve device. This device is packed with magnetic beads and facilitates the rapid concentration of drug-resistant bacteria from blood samples. Subsequently, an isothermal amplification and CRISPR assay are conducted. This system achieves an on-chip concentration factor of 20x, effectively pushing the bacterial detection threshold to 100 cfu/mL. To make sensing automatic and devoid of the need for specialized instruments, a computer vision program is developed. This program exhibits an approximate accuracy rate of 100% in discerning both positive and negative samples within the microfluidic chip. This attribute renders it particularly suitable for on-site detection in resource-limited environments. Furthermore, we delve into our recent strides in comprehending the interactions between nanomaterials and eukaryotic organisms. This understanding is facilitated by a deformable microfluidic platform, advanced microscopy, and molecular dynamic simulations. Within this context, we explore a range of clinical applications. These applications span from in vivo bioimaging employing optofluidics to addressing dentine hypersensitivity and advancing the realm of synthetic biology.

    Biography: Dr. Ke Du is an assistant professor of chemical and environmental engineering at UC-Riverside and leads the Nanobiosensing, Nanomanufacturing, and Nanomaterials (3N) Lab. He received his Ph.D. degree at Stevens Institute of Technology in 2015. Following post- doctoral training at UC-Berkeley with Richard A. Mathies, he started his independent career at the Rochester Institute of Technology in 2018. In 2022, Du's lab moved back to California and joined UC-Riverside. Du's research interests include in vitro molecular diagnostics, in vivo bioimaging, nanotoxicity, and nanomanufacturing. He is recipient of numerous awards and honors such as the EIPBN Best Journal Paper Award (2022), the NIH Maximizing Investigators' Research Award (2021), the Burroughs Wellcome Fund (BWF) Collaborative Travel Grant (2019), the James H. Potter Award for the outstanding Ph.D. students (2014), and the NSF Graduate Student Fellowship (2012). He has been recognized as a global rising starin sensing by ACS Sensors and a finalist for the MINE 2020 Young Scientists Award. Du's research has been supported by NIGMS, NIAID, NSF, USDA, DOE, BWF, the UNYTE Translational Research Network, and industry partners such as L3Harris, Mammoth Biosciences, Colgate Palmolive, and Biological Mimetics. Additionaly, he serves as an early career editorial advisory member for Biomicrofluidics (AIP Publishing) and Sensors and Actuators Reports (Elsevier).

    Host: J Yang, H Wang, C Zhou, S Cronin, W Wu

    More Information: Ke Du_2024-05-02.pdf

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248

    Audiences: Everyone Is Invited

    Contact: Marilyn Poplawski

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