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Events for May

  • Repeating EventAircraft Accident Investigation AAI 24-4

    Wed, May 01, 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

    View All Dates

    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

    Wed, May 01, 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

    View All Dates

    Contact: Daniel Scalese

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

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  • Alfred E.Mann Department of Biomedical Engineering - Seminar series

    Wed, May 01, 2024 @ 09:45 AM - 10:45 AM

    Alfred E. Mann Department of Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Jeff Saucerman, Ph.D., Professor of Biomedical Engineering and Cardiovascular Medicine Vivian Pinn Scholar, School of Medicine University of Virginia

    Talk Title: Fusing mechanistic networks and machine learning to understand inflammation-fibrosis coupling

    Abstract: Inflammation and fibrosis are conserved phases of wound healing in the heart,skin, and other organs. Yet therapeutic attempts at manipulating inflammationand fibrosis have had limited success. In this talk, I will present ourcomputational and experimental systems biology research on cardiacinflammation and fibrosis. These studies include large scale computationalmodels of the intracellular signaling networks of multiple cardiac cell types,experimental drug screens, and new methods that fuse mechanistic andmachine-learning approaches to understand how these drugs work. Ourcomputational models are validated with new experiments in cells and mice.

    Biography: Dr. Jeff Saucerman is a Professor of Biomedical Engineering and Professor ofCardiovascular Medicine at the University of Virginia. He leads a research group in cardiacsystems biology, focused on identifying and controlling the molecular networks involved inheart disease. He received a B.S. in Engineering Science from Pennsylvania StateUniversity, Ph.D. in Bioengineering from the University of California San Diego, andcompleted a postdoctoral fellowship with Dr. Donald Bers at Loyola University Chicago. Dr.Saucerman has received a number of awards including an NSF CAREER Award, Fellow ofthe American Heart Association and American Institute of Medical and BiologicalEngineering, the Dean’s Excellence in Teaching Award, BME Mentoring Award, and theVivian Pinn Scholar Award.

    Host: Stacey Finley

    Location: 101

    Audiences: Everyone Is Invited

    Contact: Carla Stanard

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  • PhD Defense- Woojeong Jin

    Wed, May 01, 2024 @ 10:00 AM - 11:30 AM

    Thomas Lord Department of Computer Science

    Student Activity


    PhD Defense- Woojeong Jin
    Title: Bridging the Visual Knowledge Gaps in Pre-trained Models
    Committee: Xiang Ren (chair), Ram Nevatia, Yan Liu, Toby Mintz.
     
    Abstract: Humans acquire knowledge by processing visual information through observation and imagination, which expands our reasoning capability about the physical world we encounter every day. Despite significant progress in solving AI problems, current state-of-the-art models in natural language processing (NLP) and computer vision (CV) have limitations in terms of reasoning and generalization, particularly with complex reasoning on visual information and generalizing to unseen vision-language tasks. In this thesis, we aim to build a reasoner that can do complex reasoning about the physical world and generalization on vision-language tasks. we will present a few lines of work to bridge the visual knowledge gaps in pre-trained models.

    Location: Henry Salvatori Computer Science Center (SAL) - 322

    Audiences: Everyone Is Invited

    Contact: Woojeong Jin

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  • Alfred E.Mann Department of Biomedical Engineering - Seminar series

    Wed, May 01, 2024 @ 11:00 AM - 12:00 PM

    Alfred E. Mann Department of Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Paula Cannon, Ph.D. , Distinguished Professor of Molecular Microbiology and Immunology in the Keck School of Medicine of USC

    Talk Title: Move over CAR T cells -“ engineering B cells to express custom molecules

    Abstract: We use CRISPR/Cas9 gene editing to reprogram B cells to express custom antibodies and antibody-like molecules. These include broadly neutralizing antibodies that can control HIV, but which are not made in response to candidate HIV vaccines. To do this, we developed a simplified gene editing protocol that inserts custom antigen-recognizing domains into constant regions of the immunoglobulin locus, resulting in molecules that mimic the heavy chain only antibodies found in Camelids. This approach preserves the important features of natural antibody expression, allowing engineered B cells to respond to matched antigens and differentiate into antibody-secreting cells. I will present our data evaluating this approach in ex vivo human tonsil organoids and in non-human primates, and describe the flexibility and potential applications of this new type of immune cell therapy.

    Biography: Paula Cannon, PhD, is a Distinguished Professor of Molecular Microbiology and Immunology in the Keck School of Medicine of USC. She obtained her PhD in bacterial gene transfer from the University of Liverpool in the UK and did postdoctoral work on HIV and gene therapy at both Harvard and Oxford Universities. Dr. Cannon uses gene editing technologies such as CRISPR/Cas9 to manipulate immune cells, with the goal of developing cell therapy treatments for HIV, cancer and other chronic diseases. Most recently, her group has been editing B cells to express completely customized molecules, such as antibodies that can neutralize multiple different strains of HIV. Such a platform could turn B cells into factories in the body to secrete antibodies with desirable properties, including those that are not easily generated by vaccination. Dr. Cannon is well known as a gene therapist and will become the president of the American Society for Gene and Cell Therapy in 2024.

    Host: Peter Wang

    Location: Corwin D. Denney Research Center (DRB) - 146

    Audiences: Everyone Is Invited

    Contact: Carla Stanard

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  • PhD Dissertation Defense- Basel Shbita

    Wed, May 01, 2024 @ 03:00 PM - 05:00 PM

    Thomas Lord Department of Computer Science

    Student Activity


    PhD Dissertation Defense- Basel Shbita
    Title: Transforming Unstructured Historical and Geographic Data into Spatio-Temporal Knowledge Graphs
    Committee: Craig A. Knoblock (chair), Cyrus Shahabi, John P. Wilson; Jay Pujara, Yao-Yi Chiang
     
    Abstract: This dissertation presents a comprehensive approach to the transformation, integration and semantic enrichment of historical spatio-temporal data into knowledge graphs. The dissertation encompasses three core contributions: one, the automated generation of knowledge graphs from digitized historical maps for analyzing geographical changes over time; two, the integration of spatial and semantic context embeddings for accurate geo-entity recognition and semantic typing; and three, the creation of a comprehensive knowledge graph for the analysis of historical data from digitized archived records. I introduce innovative methodologies and practical tools to support researchers from diverse fields, enabling them to derive meaningful insights from historical and geographic data. My approach is demonstrated through various applications, such as analyzing geospatial changes over time in USGS (United States Geological Survey) historical maps of transportation networks and wetlands, automatic semantic typing of unlabeled georeferenced spatial entities, and constructing a spatio-temporal knowledge graph from digitized historical mineral mining data. The dissertation combines semantic web technologies, representation learning, and semantic modeling to build comprehensive knowledge graphs that support geospatial and temporal analyses.

    Audiences: Everyone Is Invited

    Contact: Basel Shbita

    Event Link: https://usc.zoom.us/j/97894910088?pwd=ZVQ0VU9lYlJaWTM4V2w5Vk1maEVOQT09

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  • PhD Thesis Proposal - Ta-Yang Wang

    Wed, May 01, 2024 @ 03:00 PM - 04:00 PM

    Thomas Lord Department of Computer Science

    University Calendar


    Title: Training Heterogeneous Graph Neural Networks using Bandit Sampling        
     
    Presenter: Ta-Yang Wang        
     
    Time: May 1st, 3:00 PM - 4:00 PM          
     
    Location: EEB 219         
     
    Committee members: Viktor Prasanna (chair), Jyotirmoy Deshmukh, Rajgopal Kannan, Aiichiro Nakano, and Cauligi Raghavendra        
     
    Abstract: Graph neural networks (GNNs) have gained significant attention across diverse areas due to their superior performance in learning graph representations. While GNNs exhibit superior performance compared to other methods, they are primarily designed for homogeneous graphs, where all nodes and edges are of the same type. Training a GNN model for large-scale graphs incurs high computation and storage costs, especially when considering the heterogeneous structural information of each node. To address the demand for efficient GNN training, various sampling methods have been proposed. In this proposal, we hypothesize that one can improve the training efficiency via bandit sampling, an online learning algorithm with provable convergence under weak assumptions on the learning objective. The main idea is to prioritize node types with more informative connections with respect to the learning objective. Additionally, we analyze the limitations of the framework, thus advancing its applicability in large-scale graph learning tasks.

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 219

    Audiences: Everyone Is Invited

    Contact: Ellecia Williams

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  • 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

    View All Dates

    Contact: Daniel Scalese

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

    OutlookiCal
  • 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

    View All Dates

    Contact: Daniel Scalese

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

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  • 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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  • Repeating EventAircraft Accident Investigation AAI 24-4

    Fri, May 03, 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

    View All Dates

    Contact: Daniel Scalese

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

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  • Safety Management for Aviation Maintenance MAINT 24-2

    Fri, May 03, 2024 @ 08:00 AM - 12:00 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

    Contact: Daniel Scalese

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

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  • PhD Defense- Julie Jiang

    Fri, May 03, 2024 @ 10:00 AM - 12:00 PM

    Thomas Lord Department of Computer Science

    Student Activity


    PhD Defense- Julie Jiang
    Title:  Socially-informed content analysis of online human behavior
    Committee: Emilio Ferrara (CS and Communication, tenure, chair), Kristina Lerman (CS), Marlon Twyman II (Communication, external), Pablo Barberá (Poli Sci)
     

    Abstract: The explosive growth of social media has not only revolutionized communication but also brought challenges such as political polarization, misinformation, hate speech, and echo chambers. This dissertation employs computational social science techniques to investigate these issues, understand the social dynamics driving negative online behaviors, and propose data-driven solutions for healthier digital interactions. I begin by introducing a scalable social network representation learning method that integrates user-generated content with social connections to create unified user embeddings, enabling accurate prediction and visualization of user attributes, communities, and behavioral propensities. Using this tool, I explore three interrelated problems: 1) COVID-19 discourse on Twitter, revealing polarization and asymmetric political echo chambers; 2) online hate speech, suggesting the pursuit of social approval motivates toxic behavior; and 3) moral underpinnings of COVID-19 discussions, uncovering patterns of moral homophily and echo chambers, while also indicating moral diversity and plurality can improve message reach and acceptance across ideological divides. These findings contribute to the advancement of computational social science and provide a foundation for understanding human behavior through the lens of social interactions and network homophily.

    Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 104

    Audiences: Everyone Is Invited

    Contact: Julie Jiang

    Event Link: https://usc.zoom.us/j/5152754393?pwd=V1pzUnpEc0JtTVZlS0l5R1VMRWlRdz09&omn=91709345144

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  • AI Seminar- Understanding LLMs through their Generative Behavior, Successes and Shortcomings

    Fri, May 03, 2024 @ 11:00 AM - 12:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Swabha Swayamdipta, USC

    Talk Title: Understanding LLMs through their Generative Behavior, Successes and Shortcomings

    Series: AI Seminar

    Abstract: Abstract: Generative capabilities of large language models have grown beyond the wildest imagination of the broader AI research community, leading many to speculate whether these successes may be attributed to the training data or model design. I will present some work from my group which sheds light on understanding LLMs by studying their generative behavior, successes and shortcomings. First, I will show that standard inference algorithms work well because of the particular design behind LLMs. Next, I will discuss recently found successes and failures of LLMs on a combination of tasks, requiring world and domain-specific knowledge, linguistic capabilities and awareness of human and social utility. Overall, these findings paint a partial yet complex picture of our understanding of LLMs and provide a guide to the next steps forward.
     
    This event will be recorded.
    It will be posted on our USC/ISI YouTube page within 1-2 business days: https://www.youtube.com/user/USCISI.

    Biography: Swabha Swayamdipta is an Assistant Professor of Computer Science and a Gabilan Assistant Professor at the University of Southern California. Her research interests are in natural language processing and machine learning, with a primary interest in the estimation of dataset quality, understanding and evaluation of generative models of language, and using language technologies to understand social behavior. At USC, Swabha leads the Data, Interpretability, Language and Learning (DILL) Lab. She received her PhD from Carnegie Mellon University, followed by a postdoc at the Allen Institute for AI. Her work has received outstanding paper awards at ICML 2022, NeurIPS 2021 and an honorable mention for the best paper at ACL 2020. Her research is supported by awards from the Allen Institute for AI and Intel Labs.

    Host: Jay Pujara and Karen Lake

    More Info: https://www.isi.edu/events/4684/ai-seminar-understanding-llms-through-their-generative-behavior-successes-and-shortcomings/

    Webcast: https://usc.zoom.us/j/95888595423?pwd=VHBLa041dUJWcWx0NEhuYmQrV29ZQT09

    Location: Information Science Institute (ISI) - Conf Rm#1135-37

    WebCast Link: https://usc.zoom.us/j/95888595423?pwd=VHBLa041dUJWcWx0NEhuYmQrV29ZQT09

    Audiences: Everyone Is Invited

    Contact: Pete Zamar

    Event Link: https://www.isi.edu/events/4684/ai-seminar-understanding-llms-through-their-generative-behavior-successes-and-shortcomings/

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  • Alfred E.Mann Department of Biomedical Engineering - Seminar series

    Fri, May 03, 2024 @ 11:00 AM - 12:00 PM

    Alfred E. Mann Department of Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Kate Havens, Ph.D., Associate Professor of Clinical Physical Therapy Division of Biokinesiology & Physical Therapy, USC

    Talk Title: Oh Baby! Integrating Anatomy, Biomechanics, and Engineering to Address Postpartum Pain

    Abstract: In this presentation, Dr. Havens will introduce the biomechanics underlying pelvic girdle pain and dysfunction in postpartum mothers, integrating musculoskeletal anatomical, orthopedic biomechanical, and engineering principles. She will delve into the unique adaptations during pregnancy and postpartum, focusing on posture, gait, and balance activities, alongside an exploration of the anatomy of the region. This knowledge informs innovative engineering solutions for mitigating perinatal biomechanical challenges, particularly the unique demands of infant caregiving tasks.

    Biography: Dr. Kate Havens is an Associate Professor in the Division of Biokinesiology and Physical Therapy and specializes in biomechanics and anatomical sciences. Her research interest is perinatal health. She studies biopsychosocial aspects of new motherhood and focuses her laboratory work on biomechanics underlying lumbopelvic pain and dysfunction in postpartum mothers.

    Host: Megan McCain

    Location: Corwin D. Denney Research Center (DRB) - 145

    Audiences: Everyone Is Invited

    Contact: Carla Stanard

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  • Repeating EventAircraft Accident Investigation AAI 24-4

    Mon, May 06, 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

    View All Dates

    Contact: Daniel Scalese

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

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  • Repeating EventAircraft Accident Investigation AAI 24-4

    Tue, May 07, 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

    View All Dates

    Contact: Daniel Scalese

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

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  • PhD Defense- Yilei Zeng

    Tue, May 07, 2024 @ 10:30 AM - 12:00 PM

    Thomas Lord Department of Computer Science

    Student Activity


    PhD Defense- Yilei Zeng

    Title: Learning Social Sequential Decision-Making in Online Games
    Committee: Emilio Ferrara (chair), Dmitri Williams, Michael Zyda
     

    Abstract:


    A paradigm shift towards human-centered intelligent gaming systems is gradually setting in. This dissertation explores the complexities of social sequential decision-making within online gaming environments and presents comprehensive AI solutions to enhance personalized single and multi-agent experiences. The three core contributions of the dissertation are intricately interrelated, creating a cohesive framework for understanding and improving AI in gaming. I begin by delving into the dynamics of gaming sessions and sequential in-game individual and social decision-making, which establishes a baseline of how decisions evolve, providing the necessary context for the subsequent integration of diverse information sources; two, the integration of heterogeneous information and multi-modal trajectories, which enhances decision-making generation models; and three, the creation of a reinforcement learning with human feedback framework to train gaming AIs that effectively align with human preferences and strategies, which enables the system not only learning but also interacting with humans. Collectively, this dissertation combines innovative data-driven, generative AI, representation learning, and human-AI collaboration solutions to help advance both the fields of computational social science and artificial intelligence applications of gaming.

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

    Audiences: Everyone Is Invited

    Contact: Yilei Zeng

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  • Alfred E.Mann Department of Biomedical Engineering - Seminar series

    Tue, May 07, 2024 @ 10:45 AM - 11:45 AM

    Alfred E. Mann Department of Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Rong Li, Professor of Mechanobiology Institute, National University of Singapore Department of Cell Biology and Department of Chemical and Biomolecular Engineering, Johns Hopkins University School of Medicine

    Talk Title: Mechanics and stress in cellular development, adaptation, and aging

    Abstract: Mechanical processes are central to diverse cellular functions but can also be sources of cellular stress leading to aging phenotypes. My lab currently investigates three problems related to cell mechanics and stress: 1) how intracellular fluid dynamics coupled with cytoskeletal forces drive early mammalian development and reproductive aging; 2) how stress-induced protein aggregation and subsequent disaggregation are orchestrated by and affect organelles such as mitochondria and ER; and 3) the interplay between biophysical stress and chromosome instability and its contribution to cellular adaptation and cancer evolution. I will present a combination of recent findings in the first two areas of our research. 

    Biography: Professor Rong Li came from Johns Hopkins University where she served as the Director of the Centre for Cell Dynamics in the Johns Hopkins School of Medicine. She was recruited to NUS in 2019 as the second Director of Mechanobiology Institute (MBI). Professor Li is a globally respected leader in the study of cellular dynamics and mechanics. Her interdisciplinary research integrates genetics, quantitative imaging, biophysical measurements, mathematical modelling, genomics and proteomics — to understand how eukaryotic cells transmit their genomes, adapt to the environment, and establish distinct organisation to perform specialised functions. The diverse projects in Professor Rong Li’s lab contribute to two main research thrusts: cell and tissue aging; cellular and organismal adaptation. The study on aging focuses on understanding dynamic changes of crucial cellular components during the aging process and how these changes alter the mechanical functions of cells and tissues. The insights gained will be applied to the development of new methods for prolonging healthy aging and the repair and regeneration of deteriorated functions. The study of adaptation aims to understand the dynamics of genetic and epigenetic determinants of cells and tissues under acute or chronic stress which lead to adaptive behaviors ultimately beneficial or detrimental to the fitness of the organism. A potential application of the discoveries in this area is the prevention of cancer associated with chronic inflammatory diseases. 

    Location: Corwin D. Denney Research Center (DRB) - 145

    Audiences: Everyone Is Invited

    Contact: Carla Stanard

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  • PhD Dissertation Defense - I-Hung Hsu

    Tue, May 07, 2024 @ 02:10 PM - 04:00 PM

    Thomas Lord Department of Computer Science

    University Calendar


    Title: Towards Generalized Event Understanding in Text via Generative Models
     
    Committee Members: Dr. Prem Natarajan (Chair), Dr. Nanyun Peng (Co-Chair), Dr. Dan O'Leary, Dr. Emilio Ferrara
     
    Date and Time:  May 7th, 2024 - 2:10p - 4:00p
     
    Abstract: Human languages in the world, such as news or narratives, are structured around events. Focusing on these events allows Natural Language Processing (NLP) systems to better understand plots, infer motivations, consequences, and the dynamics of situations. Despite the rapidly evolving landscape of NLP technology, comprehending complex events, particularly those rarely encountered in training such as in niche domains or low-resource languages, remains a formidable challenge. This thesis explores methods to enhance NLP model generalizability for better adaptability to unfamiliar events and languages unseen during training.
     
    My approach includes two main strategies: (1) Model Perspective: I propose a novel generation-based event extraction framework, largely different from typical solutions that make predictions by learning to classify input tokens. This new framework utilizes indirect supervision from natural language generation, leveraging large-scale unsupervised data without requiring additional training modules dependent on limited event-specific data. Hence, it facilitates the models’ ability on understanding general event concepts. I further explore advanced methods to extend this framework for cross-lingual adaptation and to utilize cross-domain robust resources effectively. (2) Data Perspective: I develop techniques to generate pseudo-training data broaden the training scope for event understanding models. This includes translating structured event labels into other languages with higher accuracy and fidelity, and synthesizing novel events for the existing knowledge base.
     
    Overall, my work introduces a novel learning platform to the NLP community, emphasizing an innovative modeling paradigm and comprehensive data preparation to foster more generalized event understanding models.
     

    Location: Information Science Institute (ISI) - 727

    Audiences: Everyone Is Invited

    Contact: I-Hung Hsu

    Event Link: https:/usc.zoom.us/j/95785927723?pwd=dFlGbEcwbXlGalJ6OVk3YW41RDMrdz09

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  • Repeating EventAircraft Accident Investigation AAI 24-4

    Wed, May 08, 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

    View All Dates

    Contact: Daniel Scalese

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

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  • Repeating EventAircraft Accident Investigation AAI 24-4

    Thu, May 09, 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

    View All Dates

    Contact: Daniel Scalese

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

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  • NL Seminar-Event Extraction for Epidemic Prediction

    Thu, May 09, 2024 @ 11:00 AM - 12:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Tanmay Parekh, UCLA

    Talk Title: Event Extraction for Epidemic Prediction

    Series: NL Seminar

    Abstract: *Meeting hosts only admit on-line guests that they know to the Zoom meeting. Hence, you’re highly encouraged to use your USC account to sign into Zoom. If you’re an outside visitor, please inform us at (nlg-seminar-host(at)isi.edu) to make us aware of your attendance so we can admit you. Specify if you will attend remotely or in person at least one business day prior to the event Provide your: full name, job title and professional affiliation and arrive at least 10 minutes before the seminar begins. If you do not have access to the 6th Floor for in-person attendance, please check in at the 10th floor main reception desk to register as a visitor and someone will escort you to the conference room location.  Tanmay Parekh is a third-year PhD student in Computer Science at the University of California Los Angeles (UCLA). He is advised by Prof. Nanyun Peng and Prof. Kai-Wei Chang. Previously, he completed his Masters at the Language Technologies Institute at Carnegie Mellon University (CMU) where he worked with Prof. Alan Black and Prof. Graham Neubig. He has completed his undergraduate studies at the Indian Institute of Technology Bombay (IITB). He has also worked in the industry at Amazon and Microsoft. He has worked on a wide range of research topics in multilingual, code-switching, controlled generation, and speech technologies. His current research focuses on improving the utilization and generalizability of Large Language Models (LLMs) for applications in Information Extraction (specifically Event Extraction) across various languages and domains.

    Biography: Early warnings and effective control measures are among the most important tools for policymakers to be prepared against the threat of any epidemic. Social media is an important information source here, as it is more timely than other alternatives like news and public health and is publicly accessible. Given the sheer volume of daily social media posts, there is a need for an automated system to monitor social media to provide early and effective epidemic prediction. To this end, I introduce two works to aid the creation of such an automated system using information extraction. In my first work, we pioneer exploiting Event Detection (ED) for better preparedness and early warnings of any upcoming epidemic by developing a framework to extract and analyze epidemic-related events from social media posts. We curate an epidemic event ontology comprising seven disease-agnostic event types and construct a Twitter dataset SPEED focused on the COVID-19 pandemic. Experimentation reveals how ED models trained on COVID-based SPEED can effectively detect epidemic events for three unseen epidemics of Monkeypox, Zika, and Dengue. Furthermore, we show that reporting sharp increases in the extracted events by our framework can provide warnings 4-9 weeks earlier than the WHO epidemic declaration for Monkeypox. Since epidemics can originate across the globe, social media posts discussing them can be in varied languages. However, training supervised models on every language is a tedious and resource-expensive task. The alternative is the usage of zero-shot cross-lingual models. In this work, we introduce a new approach for label projection that can be used to generate synthetic training data in any language using the translate-train paradigm. This novel approach, CLaP, translates text to the target language and performs contextual translation on the labels using the translated text as the context, ensuring better accuracy for the translated labels. We leverage instruction-tuned language models with multilingual capabilities as our contextual translator, imposing the constraint of the presence of translated labels in the translated text via instructions. We benchmark CLaP with other label projection techniques on zero-shot cross-lingual transfer across 39 languages on two representative structured prediction tasks — event argument extraction (EAE) and named entity recognition (NER), showing over 2.4 F1 improvement for EAE and 1.4 F1 improvement for NER.

    Host: Jon May and Justin Cho

    More Info: https://www.isi.edu/research-groups-nlg/nlg-seminars/

    Webcast: https://www.youtube.com/watch?v=8MPbW2abdKs

    Location: Information Science Institute (ISI) - Conf Rm#689

    WebCast Link: https://www.youtube.com/watch?v=8MPbW2abdKs

    Audiences: Everyone Is Invited

    Contact: Pete Zamar

    Event Link: https://www.isi.edu/research-groups-nlg/nlg-seminars/

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  • PhD Thesis Defense - Qinyi Luo

    Thu, May 09, 2024 @ 11:00 AM - 02:00 PM

    Thomas Lord Department of Computer Science

    University Calendar


    PhD Thesis Defense - Qinyi (Chelsea) Luo
     
    Committee members: Xuehai Qian (co-chair), Viktor Prasanna (co-chair), Ramesh Govindan, Chao Wang, Feng Qian
     
    Title: High-Performance Heterogeneity-Aware Distributed Machine Learning Model Training    
     
    Abstract: The increasing size of machine learning models and the ever-growing amount of data result in days or even weeks of time required to train a machine learning model. To accelerate training, distributed training with parallel stochastic gradient descent is widely adopted as the go-to training method. This thesis targets four challenges in distributed training: (1) performance degradation caused by large amount of data transfer among parallel workers, (2) heterogeneous computation and communication capacities in the training devices, i.e., the straggler issue, (3) huge memory consumption during training caused by gigantic model sizes, and (4) automatic selection of parallelization strategies. This thesis first delves into the topic of decentralized training and proposes system support and algorithmic innovation that strengthen tolerance against stragglers in data-parallel training. On the system side, a unique characteristic of decentralized training, the iteration gap, is identified, and a queue-based synchronization mechanism is proposed to efficiently support decentralized training as well as common straggler-mitigation techniques. In the experiments, the proposed training protocol, Hop, can provide strong tolerance against stragglers and train much faster than standard decentralized training when stragglers are present. On the algorithm side, a novel communication primitive, randomized partial All-Reduce, is proposed to enable fast synchronization in decentralized data-parallel training. The proposed approach, Prague, can achieve a 1.2x speedup against All-Reduce in a straggler-free environment and a 4.4x speedup when stragglers are present. Then, on the topic of memory optimization for training Deep Neural Networks (DNNs), an adaptive during-training model compression technique, FIITED, is proposed to reduce the memory consumption of training huge recommender models. FIITED adapts to dynamic changes in data and adjusts the dimension of each individual embedding vector continuously during training. Experiments show that FIITED is able to reduce the memory consumption of training significantly more than other embedding pruning methods, while maintaining the trained model's quality. In the end, in the aspect of automatic parallelization of training workloads, a novel unified representation of parallelization strategies, incorporating Data Parallelism (DP), Model Parallelism (MP) and Pipeline Parallelism (PP), is proposed, as well as a search algorithm that selects superior parallel settings in the vast search space. An ideal stage partition ratio for synchronous pipelines is derived for the first time, to the best of my knowledge, and it is theoretically proven that unbalanced partitions are better than balanced partitions. In addition, by examining the pipeline schedule, a trade-off between memory and performance is uncovered and explored. Experiments show that hybrid parallel strategies generated with the aforementioned optimizations consistently outperform those without such considerations.      
     
    Date: May 9, 2024  
    Time: 11:00 a.m. - 1:00 p.m.  
    Location: EEB 110    
    Zoom link: https://usc.zoom.us/j/95741130954?pwd=dkRkblNlNGt0TlkwOU51SlRNS0hPZz09  

    Location: Hughes Aircraft Electrical Engineering Center (EEB) -

    Audiences: Everyone Is Invited

    Contact: CS Events

    Event Link: https://usc.zoom.us/j/95741130954?pwd=dkRkblNlNGt0TlkwOU51SlRNS0hPZz09

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  • Aircraft Accident Investigation AAI 24-4

    Fri, May 10, 2024 @ 08:00 AM - 12:00 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

    Contact: Daniel Scalese

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

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  • AI Seminar- Causal Inference to Inform Curation Practices in Online Platforms

    Fri, May 10, 2024 @ 11:00 AM - 12:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Giuseppe Russo, EPFL- Ecole Polytechnique Fédérale de Lausanne

    Talk Title: Causal Inference to Inform Curation Practices in Online Platforms

    Series: AI Seminar

    Abstract: Digital platforms like Facebook, Wikipedia, Amazon, and LinkedIn play a foundational role in our society. They engage in content curation through moderation, recommendations, and monetization efforts, impacting individuals positively or negatively. In this talk, I will highlight the critical need for improving the existing methodologies used in these curation practices. I’ll make a case for the essential role of academic research in shaping policy and establishing best practices, drawing on two significant projects from my doctoral research.   First, I will delve into an observational study on Reddit that uncovered a mechanism potentially driving the proliferation of extremist communities online. Following that, I will detail the outcomes of a study assessing the impact of removing entire extremist groups from Reddit. To conclude, I will examine potential research paths aimed at improving digital platforms, with a special focus on both the promises and challenges introduced by the emergence of generative AI technologies. My research demonstrates that investigating the direct effects of content curation practices with rigor can significantly enhance the quality of online platforms.

    Biography: I am a Postdoctoral Researcher at EPFL, guided by Professor Robert West. My research spans causal inference, machine learning, and the broader impacts of AI on both society and individuals. Currently, my focus is on understanding the effects of content moderation in online social networks. My research extends to the  applying causal methods to decision-making processes related to health and sustainability.   I earned both my PhD and MSc from ETH Zurich, under the mentorship of Professor Frank Schweitzer, and completed my Bachelor's degree at the Politecnico di Milano. My work has been showcased at several academic conferences, including ACL, EMNLP, ICWSM, WWW, and IC2S2. Notably, it has been featured in the enlightening talk series at the International Conference of Computational Social Science (IC2S2).

    Host: Fred Mortatter and Pete Zamar

    More Info: https://www.isi.edu/events/4871/ai-seminar-causal-inference-to-inform-curation-practices-in-online-platforms/

    Webcast: https://www.youtube.com/watch?v=XPf4ymbGRak

    Location: Information Science Institute (ISI) - Virtual Only

    WebCast Link: https://www.youtube.com/watch?v=XPf4ymbGRak

    Audiences: Everyone Is Invited

    Contact: Pete Zamar

    Event Link: https://www.isi.edu/events/4871/ai-seminar-causal-inference-to-inform-curation-practices-in-online-platforms/

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  • Repeating EventSeMS Aviation Security Management Systems AVSEC 24-2

    Mon, May 13, 2024 @ 08:00 AM - 04:00 PM

    Aviation Safety and Security Program

    University Calendar


    This course is designed for individuals responsible for managing and implementing aviation security measures at medium to small-size aircraft operators, all airports, and Indirect Air Carriers (IACs). The course applies the fundamentals of SMS (hazard identification, risk assessment, and mitigation of risk) to aviation security. It demonstrates how to conduct a risk-based security program that builds upon national and international standards and requirements. The course presents the PRIFISE operational risk assessment tool as a framework for meeting emerging security threats. As cyber security has become a more important issue, this course has been extended to include a half-day on cyber security. Note: This is a non-SSI course.

    Location: Century Boulevard Building (CBB) - 920

    Audiences: Everyone Is Invited

    View All Dates

    Contact: Daniel Scalese

    Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AAVSEC2

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  • Repeating EventSoftware Safety SFT 24-2

    Mon, May 13, 2024 @ 08:00 AM - 04:00 PM

    Aviation Safety and Security Program

    University Calendar


    Software requires special attention in system planning, architecture, design, and testing. This course presents philosophies and methods of developing and analyzing software and highlights managing a software safety program. Software design principles will be taught to create fault-tolerant and acceptably safe programs. Several software hazard analysis methods will be evaluated, including Fault Tree/Soft Tree, Software Sneak Analysis, and Petri Nets.

    Location: Century Boulevard Building (CBB) - 960

    Audiences: Everyone Is Invited

    View All Dates

    Contact: Daniel Scalese

    Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24ASFT2

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  • Repeating EventSeMS Aviation Security Management Systems AVSEC 24-2

    Tue, May 14, 2024 @ 08:00 AM - 04:00 PM

    Aviation Safety and Security Program

    University Calendar


    This course is designed for individuals responsible for managing and implementing aviation security measures at medium to small-size aircraft operators, all airports, and Indirect Air Carriers (IACs). The course applies the fundamentals of SMS (hazard identification, risk assessment, and mitigation of risk) to aviation security. It demonstrates how to conduct a risk-based security program that builds upon national and international standards and requirements. The course presents the PRIFISE operational risk assessment tool as a framework for meeting emerging security threats. As cyber security has become a more important issue, this course has been extended to include a half-day on cyber security. Note: This is a non-SSI course.

    Location: Century Boulevard Building (CBB) - 920

    Audiences: Everyone Is Invited

    View All Dates

    Contact: Daniel Scalese

    Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AAVSEC2

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  • Repeating EventSoftware Safety SFT 24-2

    Tue, May 14, 2024 @ 08:00 AM - 04:00 PM

    Aviation Safety and Security Program

    University Calendar


    Software requires special attention in system planning, architecture, design, and testing. This course presents philosophies and methods of developing and analyzing software and highlights managing a software safety program. Software design principles will be taught to create fault-tolerant and acceptably safe programs. Several software hazard analysis methods will be evaluated, including Fault Tree/Soft Tree, Software Sneak Analysis, and Petri Nets.

    Location: Century Boulevard Building (CBB) - 960

    Audiences: Everyone Is Invited

    View All Dates

    Contact: Daniel Scalese

    Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24ASFT2

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  • Repeating EventSeMS Aviation Security Management Systems AVSEC 24-2

    Wed, May 15, 2024 @ 08:00 AM - 04:00 PM

    Aviation Safety and Security Program

    University Calendar


    This course is designed for individuals responsible for managing and implementing aviation security measures at medium to small-size aircraft operators, all airports, and Indirect Air Carriers (IACs). The course applies the fundamentals of SMS (hazard identification, risk assessment, and mitigation of risk) to aviation security. It demonstrates how to conduct a risk-based security program that builds upon national and international standards and requirements. The course presents the PRIFISE operational risk assessment tool as a framework for meeting emerging security threats. As cyber security has become a more important issue, this course has been extended to include a half-day on cyber security. Note: This is a non-SSI course.

    Location: Century Boulevard Building (CBB) - 920

    Audiences: Everyone Is Invited

    View All Dates

    Contact: Daniel Scalese

    Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AAVSEC2

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  • Repeating EventSoftware Safety SFT 24-2

    Wed, May 15, 2024 @ 08:00 AM - 04:00 PM

    Aviation Safety and Security Program

    University Calendar


    Software requires special attention in system planning, architecture, design, and testing. This course presents philosophies and methods of developing and analyzing software and highlights managing a software safety program. Software design principles will be taught to create fault-tolerant and acceptably safe programs. Several software hazard analysis methods will be evaluated, including Fault Tree/Soft Tree, Software Sneak Analysis, and Petri Nets.

    Location: Century Boulevard Building (CBB) - 960

    Audiences: Everyone Is Invited

    View All Dates

    Contact: Daniel Scalese

    Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24ASFT2

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  • Repeating EventSeMS Aviation Security Management Systems AVSEC 24-2

    Thu, May 16, 2024 @ 08:00 AM - 04:00 PM

    Aviation Safety and Security Program

    University Calendar


    This course is designed for individuals responsible for managing and implementing aviation security measures at medium to small-size aircraft operators, all airports, and Indirect Air Carriers (IACs). The course applies the fundamentals of SMS (hazard identification, risk assessment, and mitigation of risk) to aviation security. It demonstrates how to conduct a risk-based security program that builds upon national and international standards and requirements. The course presents the PRIFISE operational risk assessment tool as a framework for meeting emerging security threats. As cyber security has become a more important issue, this course has been extended to include a half-day on cyber security. Note: This is a non-SSI course.

    Location: Century Boulevard Building (CBB) - 920

    Audiences: Everyone Is Invited

    View All Dates

    Contact: Daniel Scalese

    Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AAVSEC2

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  • Repeating EventSoftware Safety SFT 24-2

    Thu, May 16, 2024 @ 08:00 AM - 04:00 PM

    Aviation Safety and Security Program

    University Calendar


    Software requires special attention in system planning, architecture, design, and testing. This course presents philosophies and methods of developing and analyzing software and highlights managing a software safety program. Software design principles will be taught to create fault-tolerant and acceptably safe programs. Several software hazard analysis methods will be evaluated, including Fault Tree/Soft Tree, Software Sneak Analysis, and Petri Nets.

    Location: Century Boulevard Building (CBB) - 960

    Audiences: Everyone Is Invited

    View All Dates

    Contact: Daniel Scalese

    Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24ASFT2

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  • PhD Dissertation Defense - Nicolaas Weideman

    Thu, May 16, 2024 @ 09:00 AM - 11:00 AM

    Thomas Lord Department of Computer Science

    Student Activity


    PhD Dissertation Defense - Nicolaas Weideman

    Title: Improving Binary Program Analysis to Enhance the Security of Modern Software Systems


    Committee: Jelena Mirkovic (chair), Chao Wang and Paul Bogdan
     

    Abstract: With the ever-increasing reliance of the modern world on software systems, the frequency and impact of cyberattacks have greatly increased as well. Software must be analyzed thoroughly to evaluate its security, as vulnerabilities in software can have devastating consequences such as compromised privacy of users, shutdown of infrastructure, significant business losses, and even pose threat to human life. Unfortunately, manual analysis of the source code is insufficient to evaluate the security of software. This is firstly due to the quantity and size of modern software making this method impractical and secondly due to low-level vulnerabilities that are invisible in the source code. Conversely, binary program analysis focuses on automatically analyzing the machine code instructions of executables to reason about security-related properties. In this thesis we enhance automatic software security evaluation by leveraging and extending binary program analysis. We develop approaches to 1) automatically discover vulnerabilities and 2) automatically and safely patch vulnerabilities. We improve the reliability of binary data-flow analysis by 3) evaluating three state of the art binary analysis frameworks and 4) improving the state of the art. Each of these directions independently pushes the boundaries of what is possible in defending modern software, leading to a more secure digital environment.

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

    Audiences: Everyone Is Invited

    Contact: Nicolaas Weideman

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  • Alfred E.Mann Department of Biomedical Engineering - Seminar series

    Thu, May 16, 2024 @ 11:00 AM - 12:00 PM

    Alfred E. Mann Department of Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Ben Almquist, Senior Lecturer (US equivalent: Associate Professor) in the Department of Bioengineering at Imperial College London and Director of the Biomedical Technology Ventures Programme

    Talk Title: Pilfering Patient Pharmacies -“ Using Bioinspiration to Drive Wound Repair

    Abstract: Over the course of our lives, our bodies break down and we fix them. Everything from a scraped knee to a broken bone can be mended. But there is always the chance that the task becomes a bit too much for our bodies to handle. Whether it is a chronic skin wound that has persisted for twenty years in an elderly individual, a diabetic ulcer that is trying hard to steal a life, or simply a major traumatic injury that is simply too much for our bodies to handle, the impact is astounding. Chronic non-healing skin wounds have been called a silent epidemic, drive social isolation and depression, and consume 3-5% of national healthcare budgets. Meanwhile, non-union fractures of bones, such as the tibia, score lower in quality-of-life surveys than acute myocardial infarction, AIDS, and T1 diabetes, with a one in two chance of not returning to work. Somewhat surprisingly, there is an astounding lack of innovative approaches carrying clinical approval for treating defective wound healing; in the area of skin repair, the last FDA approved pharmacologic treatment for chronic wounds was approved over 20 years ago! In this talk, I will discuss our push to develop new methods for promoting tissue repair for both chronic and acute wounds, using bioinspiration to link together insights from materials science, nanotechnology and biology to enable new possibilities for driving tissue repair. This goal has led us to establish a new method for controlling drug delivery based on cellular traction forces, while also allowing us to ask the question – can our bodies simply give us the helping hand we need to heal our tissues? 

    Biography: Dr Ben Almquist is a Senior Lecturer (US equivalent: Associate Professor) in the Department of Bioengineering at Imperial College London and Director of the Biomedical Technology Ventures Programme. His research aims to develop new methods for seamlessly bridging the interface between engineered materials and devices and biological systems, with a major focus on tissue repair and regeneration. Dr Almquist has been recognized as an Emerging Investigator in Biomaterials Science and is a Fellow of the Institute of Materials, Minerals, and Mining. Before joining Imperial College, Dr Almquist spent time as a NIH Ruth L. Kirschstein Postdoctoral Fellow at the Koch Institute for Integrative Cancer Research and Institute for Solider Nanotechnologies at MIT and was a Research Fellow in the Center for Probing the Nanoscale at Stanford University. He has an MS and PhD in Materials Science from Stanford University and a BSc in Materials Science from Michigan Technological University.

    Host: Eun Ji Chung

    Location: Corwin D. Denney Research Center (DRB) - 145

    Audiences: Everyone Is Invited

    Contact: Carla Stanard

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  • DEN@Viterbi: Active Duty Military and Veterans Info Session

    Thu, May 16, 2024 @ 12:00 PM - 01:00 PM

    DEN@Viterbi, Viterbi School of Engineering Graduate Admission

    Workshops & Infosessions


    Join USC Viterbi representatives for a step-by-step guide and tips for how to apply for formal admission into a Master's degree or Graduate Certificate program. The session is intended for individuals who wish to pursue a graduate degree program completely online via USC Viterbi's flexible online DEN@Viterbi delivery method. Attendees will have the opportunity to connect directly with USC Viterbi representatives and ask questions about the admission process throughout the session. 

    WebCast Link: https://uscviterbi.webex.com/weblink/register/r6b09657bde1e9fef8b36ffd0b45ac6e8

    Audiences: Everyone Is Invited

    Contact: Corporate & Professional Programs

    Event Link: https://uscviterbi.webex.com/weblink/register/r6b09657bde1e9fef8b36ffd0b45ac6e8

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  • SeMS Aviation Security Management Systems AVSEC 24-2

    Fri, May 17, 2024 @ 08:00 AM - 12:00 PM

    Aviation Safety and Security Program

    University Calendar


    This course is designed for individuals responsible for managing and implementing aviation security measures at medium to small-size aircraft operators, all airports, and Indirect Air Carriers (IACs). The course applies the fundamentals of SMS (hazard identification, risk assessment, and mitigation of risk) to aviation security. It demonstrates how to conduct a risk-based security program that builds upon national and international standards and requirements. The course presents the PRIFISE operational risk assessment tool as a framework for meeting emerging security threats. As cyber security has become a more important issue, this course has been extended to include a half-day on cyber security. Note: This is a non-SSI course.

    Location: Century Boulevard Building (CBB) - 920

    Audiences: Everyone Is Invited

    Contact: Daniel Scalese

    Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AAVSEC2

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  • PhD Defense- Hongkuan Zhou

    Fri, May 17, 2024 @ 10:00 AM - 12:00 PM

    Thomas Lord Department of Computer Science

    Student Activity


    PhD Defense- Hongkuan Zhou
    Title: Scaling up Temporal Graph Learning: Powerful Models, Efficient Algorithms, and Optimized Systems
    Committee Members: Prof. Keith Michael Chugg, Prof. Rajgopal Kannan, Prof Viktor K. Prasanna (Chair), Prof. Mukund Raghothaman
     
    Abstract: Recently, Temporal Graph Neural Networks (TGNNs) have extended the scope of Graph Representation Learning (GRL) to dynamic graphs. TGNNs generate high-quality and versatile dynamic node embeddings by simultaneously encoding the graph structures, node and edge contexts, and their temporal dependencies. TGNNs are shown to demonstrably outperform traditional dynamic graph analytic algorithms in impactful applications that address critical real-world challenges, such as social network analysis, healthcare applications, and traffic prediction and management. However, due to the challenges of the prevalent noise in real-world data, irregular memory accesses, complex temporal dependencies, and high computation complexity, current TGNNs face the following problems when scaling to large dynamic graphs: (1) Unpowerful models. Current TGNN models struggle to capture high-frequency information and handle the diverse and dynamic noise. (2) Ineffcieint algorithms. Current training algorithms cannot leverage the massive parallel processing architecture of modern hardware, while current inference algorithms cannot meet the requirements in different scenarios. And (3) Unoptimized systems. Current TGNN systems suffer from inefficient designs that hinder overall performance. In this dissertation, we address the above issues via model-algorithm-system co-design. For model improvements, we propose a static node-memory-enhanced TGNN model and a temporal adaptive sampling technique. For algorithm improvements, we propose a scalable distributed training algorithm with heuristic guidelines to achieve the optimal configuration, and a versatile inference algorithm. For system improvements, we propose techniques of dynamic feature caching, simplified temporal attention, etc., to compose optimized training and inference systems. We demonstrate significant improvements in accuracy, training time, inference latency, and throughput compared with state-of-the-art TGNN solutions.
     

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132

    Audiences: Everyone Is Invited

    Contact: Hongkuan Zhou

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  • Join us to learn about the Advancements in Research Ultrasound from Verasonics

    Fri, May 17, 2024 @ 10:00 AM - 11:00 AM

    Alfred E. Mann Department of Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Christian Coviello, PhD and Miguel Bernal, Phd, Verasonics

    Talk Title: Join us to learn about the Advancements in Research Ultrasound from Verasonics

    Host: Qifa Zhou

    Location: Corwin D. Denney Research Center (DRB) - 145

    Audiences: Everyone Is Invited

    Contact: Stephanie Perales

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  • Quantum Science & Technology Seminar - Z.Y. Jeff Ou, Friday, May 17th at 10:30am in EEB 248

    Fri, May 17, 2024 @ 10:30 AM - 11:45 AM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Z.Y. Jeff Ou, Physics, City University of Hong Kong

    Talk Title: Quantum Entangled Interferometers and Their Applications

    Series: Quantum Science & Technology Seminar Series

    Abstract: A new type of quantum interferometer utilizes nonlinear parametric processes as the wave splitting and recombination elements. Because of the nonlinear interaction, the fields inside the interferometer are intrinsically entangled and quantum mechanically correlated. This type of quantum correlated interferometer exhibits some unique properties that we will review in this talk. Because of these properties, this type of interferometer is superior to traditional beam splitter-based interferometers in many aspects. We will present its various forms and its realizations with different types of waves such as microwave, atomic waves (both internal and external degrees), and sound waves. We will discuss its applications in quantum metrology, quantum imaging, quantum spectroscopy, and quantum state engineering.

    Biography: Professor Ou obtained his BS in 1984 from Peking University and his Ph.D. in 1990 from University of Rochester. He is now a chair professor in City University of Hong Kong. Professor Ou is an expert in quantum optics, especially in quantum interference, for which he is famous for the Hong-Ou-Mandel interferometer. His current research focuses on quantum metrology, quantum sensing, quantum state engineering, and the fundamental quantum interference effects. Professor Ou is a fellow of American Physical Society and of Optica (formerly Optical Society of America).

    Host: Quntao Zhang, Wade Hsu, Mengjie Yu, Jonathan Habif & Eli Levenson-Falk

    More Information: Z.Y. Jeff Ou Flyer.pdf

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

    Audiences: Everyone Is Invited

    Contact: Marilyn Poplawski

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  • AI Seminar- AI for Fostering Constructive Online Conversations

    Fri, May 17, 2024 @ 11:00 AM - 12:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Kristina Gligoric, Stanford University

    Talk Title: AI for Fostering Constructive Online Conversations

    Abstract: REMINDER:  Meeting hosts only admit guests that they know to the Zoom meeting. Hence, you’re highly encouraged to use your USC account to sign into Zoom. If you are an outside visitor, please inform us at aiseminars DASH poc AT isi DOT edu beforehand so we will be aware of your attendance and let you in.  Zoom meeting ID: 704 285 0182Passcode: 832239  Abstract: NLP systems promise to positively impact society in high-stakes social domains. However, current evaluation and development focus on tasks that are not grounded in specific societal implications, which can lead to societal harms. In this talk, I will present recent work addressing these issues in the domain of online content moderation. In the first part, I will discuss online content moderation to enable constructive conversations about race. Content moderation practices on social media risk silencing the voices of historically marginalized groups. Both the most recent models and humans disproportionately flag posts in which users share personal experiences of racism. Not only does this censorship hinder the potential of social media to give voice to marginalized communities, but we also find that witnessing such censorship exacerbates feelings of isolation. A psychologically informed reframing intervention offers a path to reduce censorship through. In the second part, I will discuss how identified biases in models can be traced to the use-mention distinction, which is the difference between the use of words to convey a speaker’s intent and the mention of words for quoting what someone said or pointing out properties of a word. Computationally modeling the use-mention distinction is crucial for enabling counterspeech to hate and misinformation. Counterspeech that refutes problematic content mentions harmful language but is not harmful itself. Even recent language models fail at distinguishing use from mention. This failure propagates to downstream tasks but can be reduced through introduced mitigations. Finally, I discuss the big picture and other recent efforts to address these issues in different domains beyond content moderation, including education, emotional support, sustainability, and public discourse about AI. I will reflect on how, by doing so, we can minimize the harms and develop and apply NLP systems for social good.

    Biography: Kristina Gligoric is a Postdoctoral Scholar at Stanford University Computer Science Department, advised by Dan Jurafsky at the NLP group. Previously she obtained her Ph.D. in Computer Science at EPFL, where she was advised by Robert West. Her research focuses on developing computational approaches to address societal issues, drawing methods from NLP and causal inference. Her work has been published in top computer science conferences focused on computational social science and social media (CSCW, ICWSM, TheWebConf), natural language processing (EACL, NAACL, EMNLP), and broad audience journals (Nature Communications and Nature Medicine). She is a Swiss National Science Foundation Fellow and University of Chicago Rising star in Data Science. She received awards for her work, including EPFL Thesis Distinction and CSCW Best Paper Honorable Mention Award. This event will be recorded. It will be posted on our USC/ISI YouTube page within 1-2 business days: https://www.youtube.com/user/USCISI.

    Host: Myrl Marmarelis and Maura Covaci

    More Info: https://www.isi.edu/events/4952/ai-for-fostering-constructive-online-conversations/

    Location: Information Science Institute (ISI) - Conf Rm#1014

    Audiences: Everyone Is Invited

    Contact: Pete Zamar

    Event Link: https://www.isi.edu/events/4952/ai-for-fostering-constructive-online-conversations/

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  • PhD Dissertation Defense - Binh Vu

    Fri, May 17, 2024 @ 03:00 PM - 05:00 PM

    Thomas Lord Department of Computer Science

    University Calendar


    Title: Exploiting Web Tables and Knowledge Graphs for Creating Semantic Descriptions of Data Sources  
     
    Committee: Craig Knoblock (Chair), Sven Koenig, Daniel Edmund O'Leary, Yolanda Gil, Jay Pujara  
     
    Date and Time: Friday, May 17th - 3:00p - 5:00p
     
    Location: SAL 322
     
    Abstract: There is an enormous number of tables available on the web, and they can provide valuable information for diverse applications. To harvest information from the tables, we need precise mappings, called semantic descriptions, of concepts and relationships in the data to classes and properties in a target ontology. However, creating semantic descriptions, or semantic modeling, is a complex task requiring considerable manual effort and expertise. Much research has focused on automating this problem. However, existing supervised and unsupervised approaches both face various difficulties. The supervised approaches require lots of known semantic descriptions for training and, thus, are hard to apply to a new or large domain ontology. On the other hand, the unsupervised approaches exploit the overlapping data between tables and knowledge graphs; hence, they perform poorly on tables with lots of ambiguity or little overlapping data. To address the aforementioned weaknesses, we present novel approaches for two main cases: tables that have overlapping data with a knowledge graph (KG) and tables that do not have overlapping data. Exploiting web tables that have links to entities in a KG, we automatically create a labeled dataset to learn to combine table data, metadata, and overlapping background knowledge (if available) to find accurate semantic descriptions. Our methods for the two cases together provide a comprehensive solution to the semantic modeling problem. In the evaluation, our approach in the overlapping setting yields an improvement of approximately 5\% in F$_1$ scores compared to the state-of-the-art methods. In the non-overlapping setting, our approach outperforms strong baselines by  10\% to 30\% in F$_1$ scores.

    Location: Henry Salvatori Computer Science Center (SAL) - 322

    Audiences: Everyone Is Invited

    Contact: Felante' Charlemagne

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  • Repeating EventAviation Law & Aviation Dispute Resolution LEGAL 24-2

    Mon, May 20, 2024 @ 08:00 AM - 04:00 PM

    Aviation Safety and Security Program

    University Calendar


    This course is designed to provide information on the legal risks inherent in aviation operations and an overview of the legal system as it relates to aviation safety. It provides an understanding of the various legal processes relating to aviation and discusses ways to engage aviation authorities responsibly and successfully. The judicial process, current litigation trends, legal definitions, and procedures are also covered.
    Our experienced aviation lawyers, as instructors, will encourage "preventative legal medicine" to avoid legal problems. Classes are not just lectures but include interactive issue-spotting so that students can get relevant legal advice from their organizations' lawyers if and when legal problems develop.

    Location: Century Boulevard Building (CBB) - 920

    Audiences: Everyone Is Invited

    View All Dates

    Contact: Daniel Scalese

    Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24ALEGAL2

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  • Repeating EventAdvanced Software Safety ADVSFT 24-1

    Mon, May 20, 2024 @ 08:00 AM - 04:00 PM

    Aviation Safety and Security Program

    University Calendar


    This course builds upon the skills learned in the Software Safety (SFT) course. It is presumed and highly recommended that the student understands the importance of software safety in planning, analyzing architecture, designing, and coding and testing automated systems. The course expands upon those skills and presents opportunities to apply them in class in diverse situations using a small unmanned aerial system (sUAS) that is also weaponized.

    Location: Century Boulevard Building (CBB) - 960

    Audiences: Everyone Is Invited

    View All Dates

    Contact: Daniel Scalese

    Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AADVSFT1

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  • Semiconductors & Microelectronics Technology Seminar - Roozbeh Tabrizian, Monday, May 20th at 2pm in EEB 248

    Mon, May 20, 2024 @ 02:00 PM - 03:30 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Roozbeh Tabrizian, University of Florida

    Talk Title: Unleashing the Power of Nano-Mechanics on Chip using CMOS-based Ferroelectric Hafnia

    Series: Semiconductors & Microelectronics Technology

    Abstract: The incorporation of nanoscale piezoelectric transducers into advanced semiconductor nodes enables the direct implementation of high-frequency nanomechanical resonators onto CMOS chips. The discovery of metastable ferroelectric phase in hafnia heralds the long-awaited arrival of this integrated piezoelectric transducer. Hafnia films, already utilized in amorphous form as high-k dielectrics in standard semiconductor processes, can be further engineered to stabilize in the ferroelectric phase with significant piezoelectric coupling. Hafnia piezoelectric transducers pave the way for the development of on-chip nanomechanical resonators with quality factors several orders of magnitude higher than solid-state counterparts. This exceptional performance, combined with seamless integration with electronic circuitry, enables the creation of on-chip clocks, local oscillators, and microwave filters, meeting the escalating frequency-control requirements in computing and communication applications. This presentation will provide an overview of Tabrizian Lab's work focusing on the development of nanoscale hafnia transducers and resonators, and their application in creating on-chip distributed clocks for massive computing and monolithic microwave spectral processors for adaptive wireless communication. 

    Biography: Roozbeh Tabrizian is an Associate Professor and the NELMS Rising Star Endowed Professor at the Department of Electrical and Computer Engineering, University of Florida. He received his B.S. (2007) degree in EE from Sharif University of Technology, Iran, and the Ph.D. (2013) degree in ECE from Georgia Tech. He was a Post-Doctoral Scholar (2014) at the University of Michigan. His research interests include semiconductor micro- and nano-electro-mechanical systems for frequency control applications; microwave acoustics; and novel ferroic materials and devices. Tabrizian has received the DARPA Director's Fellowship Award, a DARPA Young Faculty Award, and an NSF CAREER Award. He is an associate editor of the IEEE Journal of Microelectromechanical Systems (JMEMS) and Sensors and Actuators A: Physical. Tabrizian and his students are recipients of multiple outstanding paper awards at top-tier conferences such as IEEE MEMS, IEEE IFCS, IEEE IEDM, IEEE NEMS, and Transducers.

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

    More Information: Roozbeh Tabrizian Flyer.pdf

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

    Audiences: Everyone Is Invited

    Contact: Marilyn Poplawski

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  • Repeating EventAviation Law & Aviation Dispute Resolution LEGAL 24-2

    Tue, May 21, 2024 @ 08:00 AM - 04:00 PM

    Aviation Safety and Security Program

    University Calendar


    This course is designed to provide information on the legal risks inherent in aviation operations and an overview of the legal system as it relates to aviation safety. It provides an understanding of the various legal processes relating to aviation and discusses ways to engage aviation authorities responsibly and successfully. The judicial process, current litigation trends, legal definitions, and procedures are also covered.
    Our experienced aviation lawyers, as instructors, will encourage "preventative legal medicine" to avoid legal problems. Classes are not just lectures but include interactive issue-spotting so that students can get relevant legal advice from their organizations' lawyers if and when legal problems develop.

    Location: Century Boulevard Building (CBB) - 920

    Audiences: Everyone Is Invited

    View All Dates

    Contact: Daniel Scalese

    Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24ALEGAL2

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  • Repeating EventAdvanced Software Safety ADVSFT 24-1

    Tue, May 21, 2024 @ 08:00 AM - 04:00 PM

    Aviation Safety and Security Program

    University Calendar


    This course builds upon the skills learned in the Software Safety (SFT) course. It is presumed and highly recommended that the student understands the importance of software safety in planning, analyzing architecture, designing, and coding and testing automated systems. The course expands upon those skills and presents opportunities to apply them in class in diverse situations using a small unmanned aerial system (sUAS) that is also weaponized.

    Location: Century Boulevard Building (CBB) - 960

    Audiences: Everyone Is Invited

    View All Dates

    Contact: Daniel Scalese

    Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AADVSFT1

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  • PhD Dissertation Defense - Avi Thawani

    Tue, May 21, 2024 @ 01:30 PM - 03:30 PM

    Thomas Lord Department of Computer Science

    University Calendar


    Title: Aggregating Symbols fo Language Modeling
     
    Date and Time: Tuesday, May 21st, 2024 - 1:30p - 3:30p
     
    Committee: Jay Pujara (Chair), Swabha Swayamdipta, Dani Yogatama, Aiichiro Nakano, Gerard Hoberg
     
    Abstract:  Natural language is a sequence of symbols. Language Models (LMs) are powerful at learning sequence patterns. The first step for large language models (LLMs) like ChatGPT is to convert text (that humans understand) into indices (that models do). This crucial phase in the Language Modeling pipeline has unfortunately been understudied and is currently achieved by subword segmentation, a manually engineered set of heuristics. I will deep dive into case studies where these heuristics fail and my recommended improvements: for example when representing numbers in text, as well as multi-word phrases. I present an end-to-end tokenized language model that understands both words and numbers better than subwords without any manually engineered heuristic. It also outperforms character-level tokenisation, promising up to 4/6x speed up in inference and training respectively.
     
    I show the benefits of aggregating symbols for language modeling, and investigate key aspects of symbol use in LMs:
     
    1. Aggregating on the number line improves both numeracy and literacy of language models
     
    2. We can learn to aggregate symbols given a corpus with improved language modeling and approximate 
     
    3. Learning to aggregate symbols helps downstream performance in certain application areas like neural machine translation of non-concatenative languages
     
    Zoom Link: https://usc.zoom.us/j/96005480765?pwd=TXFUWU5KWjA1S3JtM3FNaWRQZVZOZz09

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 110

    Audiences: Everyone Is Invited

    Contact: Felante' Charlemagne

    Event Link: https://urldefense.com/v3/__https:/usc.zoom.us/j/96005480765?pwd=TXFUWU5KWjA1S3JtM3FNaWRQZVZOZz09__;!!LIr3w8kk_Xxm!sXUo_YDrZLAELdFJEyNxepj4ganXUKlYiO1ytcWoggusov1R4wnuPXkZMn53jBuRkalJulQpdmzDszUs$

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  • Repeating EventAviation Law & Aviation Dispute Resolution LEGAL 24-2

    Wed, May 22, 2024 @ 08:00 AM - 04:00 PM

    Aviation Safety and Security Program

    University Calendar


    This course is designed to provide information on the legal risks inherent in aviation operations and an overview of the legal system as it relates to aviation safety. It provides an understanding of the various legal processes relating to aviation and discusses ways to engage aviation authorities responsibly and successfully. The judicial process, current litigation trends, legal definitions, and procedures are also covered.
    Our experienced aviation lawyers, as instructors, will encourage "preventative legal medicine" to avoid legal problems. Classes are not just lectures but include interactive issue-spotting so that students can get relevant legal advice from their organizations' lawyers if and when legal problems develop.

    Location: Century Boulevard Building (CBB) - 920

    Audiences: Everyone Is Invited

    View All Dates

    Contact: Daniel Scalese

    Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24ALEGAL2

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  • Repeating EventAdvanced Software Safety ADVSFT 24-1

    Wed, May 22, 2024 @ 08:00 AM - 04:00 PM

    Aviation Safety and Security Program

    University Calendar


    This course builds upon the skills learned in the Software Safety (SFT) course. It is presumed and highly recommended that the student understands the importance of software safety in planning, analyzing architecture, designing, and coding and testing automated systems. The course expands upon those skills and presents opportunities to apply them in class in diverse situations using a small unmanned aerial system (sUAS) that is also weaponized.

    Location: Century Boulevard Building (CBB) - 960

    Audiences: Everyone Is Invited

    View All Dates

    Contact: Daniel Scalese

    Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AADVSFT1

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  • DEN@Viterbi - Online Graduate Engineering Virtual Information Session

    Wed, May 22, 2024 @ 05:00 PM - 06:00 PM

    DEN@Viterbi, Viterbi School of Engineering Graduate Admission

    Workshops & Infosessions


    Join USC Viterbi School of Engineering for a virtual information session via WebEx, providing an introduction to DEN@Viterbi, our top-ranked online delivery system. Discover the 40+ graduate engineering and computer science programs available entirely online. Attendees will have the opportunity to connect directly with USC Viterbi representatives during the session to discuss the admission process, program details, and the benefits of online delivery.

    WebCast Link: https://uscviterbi.webex.com/weblink/register/ra9e59a829e912676f1808c0d064f02a0

    Audiences: Everyone Is Invited

    Contact: Corporate & Professional Programs

    Event Link: https://uscviterbi.webex.com/weblink/register/ra9e59a829e912676f1808c0d064f02a0

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  • Repeating EventAviation Law & Aviation Dispute Resolution LEGAL 24-2

    Thu, May 23, 2024 @ 08:00 AM - 04:00 PM

    Aviation Safety and Security Program

    University Calendar


    This course is designed to provide information on the legal risks inherent in aviation operations and an overview of the legal system as it relates to aviation safety. It provides an understanding of the various legal processes relating to aviation and discusses ways to engage aviation authorities responsibly and successfully. The judicial process, current litigation trends, legal definitions, and procedures are also covered.
    Our experienced aviation lawyers, as instructors, will encourage "preventative legal medicine" to avoid legal problems. Classes are not just lectures but include interactive issue-spotting so that students can get relevant legal advice from their organizations' lawyers if and when legal problems develop.

    Location: Century Boulevard Building (CBB) - 920

    Audiences: Everyone Is Invited

    View All Dates

    Contact: Daniel Scalese

    Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24ALEGAL2

    OutlookiCal
  • Repeating EventAdvanced Software Safety ADVSFT 24-1

    Thu, May 23, 2024 @ 08:00 AM - 04:00 PM

    Aviation Safety and Security Program

    University Calendar


    This course builds upon the skills learned in the Software Safety (SFT) course. It is presumed and highly recommended that the student understands the importance of software safety in planning, analyzing architecture, designing, and coding and testing automated systems. The course expands upon those skills and presents opportunities to apply them in class in diverse situations using a small unmanned aerial system (sUAS) that is also weaponized.

    Location: Century Boulevard Building (CBB) - 960

    Audiences: Everyone Is Invited

    View All Dates

    Contact: Daniel Scalese

    Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AADVSFT1

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  • AI Seminar-Things Multimodal LLMs Cannot See: Toward Discovering and Mitigating Perceptual Biases in Neural Networks through Visual Interventions

    Thu, May 23, 2024 @ 11:00 AM - 12:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Mahyar Khayatkhoei , USC/ISI

    Talk Title: Things Multimodal LLMs Cannot See: Toward Discovering and Mitigating Perceptual Biases in Neural Networks through Visual Interventions

    Abstract: In this talk, I will discuss our recent research on the use of pixel-space interventions for discovering and mitigating biases in visual neural networks, including in multimodal large language models (MLLMs). I will start by showcasing our discovered perceptual limitations and biases of MLLMs (including commercial ones such as GPT-4V and LLaVA). I will then discuss our simple yet effective intervention-based approach for mitigating such limitations, which can do so without requiring any training. Finally, I will more broadly discuss the problem of removing attribute-specific bias from neural networks, present our latest information theoretic bounds on this problem, and explain our adversarial input-intervention approach for removing strong attribute bias.
    This event will be recorded but only shared with AI Division Leadership.

    Biography: I am a Computer Scientist at the AI Division of the USC Information Sciences Institute. I received my Ph.D. and M.Sc. in computer science from Rutgers University working with Dr. Ahmed Elgammal, and my B.Sc. in electrical engineering from the University of Tehran. My research explores the theory and application of deep generative models, and has identified and resolved major bottlenecks in neural networks’ ability to learn from heterogeneous data (NeurIPS 2018), to learn high frequency features (AAAI 2022), and in their reliable evaluation (ICML 2023). My latest focus is on adopting large-scale generative neural networks to real-world mission-critical tasks. I am particularly interested in developing reliable and efficient data-driven computational models of real-world phenomena that would enhance our current physics-based models. My personal website is at https://mahyarkoy.github.io 

    Host: Host: Adam Russell, POC Justina Gilleland and Alma Nava

    More Info: https://www.isi.edu/events/4966/things-multimodal-llms-cannot-see-toward-discovering-and-mitigating-perceptual-biases-in-neural-networks-through-visual-interventions/

    Webcast: https://usc.zoom.us/j/93179461297?pwd=d2RpNWlEblhxcHRFMU9RbnRxbWJBUT09

    Location: Information Science Institute (ISI) - Conf Rm#1135

    WebCast Link: https://usc.zoom.us/j/93179461297?pwd=d2RpNWlEblhxcHRFMU9RbnRxbWJBUT09

    Audiences: Everyone Is Invited

    Contact: Pete Zamar

    Event Link: https://www.isi.edu/events/4966/things-multimodal-llms-cannot-see-toward-discovering-and-mitigating-perceptual-biases-in-neural-networks-through-visual-interventions/

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  • PhD Dissertation Defense - Myrl Marmarelis

    Tue, May 28, 2024 @ 02:00 PM - 04:00 PM

    Thomas Lord Department of Computer Science

    University Calendar


    Title: Robust Causal Inference with Machine Learning on Observational Data
     
    Date and Time: Tuesday, May 28th - 2:00pm - 4:00pm
     
    Committee: Aram Galstyan (Chair), Greg Ver Steeg, Fred Morstatter, Shanghua Teng, and Roger Ghanem (external)
     
    Abstract: 
    The rise of artificial intelligence and deep learning has led to unprecedented capabilities in prediction. As these black-box algorithms are deployed in different parts of society, it is becoming increasingly clear that predictions alone do not always translate to enabling effective decisions, policies, or reliable forecasts in a changing world. What is often needed is a stronger understanding of a system than a predictive model of observations can offer. This deficit arises when attempting to predict the system’s behavior in novel situations. Causal inference refers to a set of theoretical frameworks and practical methods for identifying cause-and-effect structures from data. Knowledge of this structure can help anticipate what would happen in a novel situation, like subjecting the system to intervention. Much work in causal inference is concerned with finding the minimal assumptions required to answer specific causal questions, like estimating the effect of a certain treatment. The more reasonable and relaxed the assumptions of a causal-inference method, the more applicable it is to diverse datasets and machine learning. There are many methodological aspects to performing causal inference on observational data—that is, without the ability to perform experiments. Of fundamental significance is having workable representations of the system that can be learned from data. Closely related to the quality of the representations is the ability to make downstream causal estimates robust to confounding. Confounders in a system are common structures that might confuse apparent relations between cause and effect, or treatment and outcome.
     
    In this dissertation, I propose methods for addressing these problems in challenging machine-learning contexts. I introduce an improved representation of single-cell RNA sequencing data for inference tasks in medicine and biology. Looking for high-dimensional interactions in biological processes leads to better resolution of phenotypes. More broadly, I make numerous contributions towards increased robustness of machine learning to hidden or observed confounding. I address sensitivity of dose-response curves to hidden confounding, prediction of interventional outcomes under hidden confounding; robust effect estimation for continuous-valued and multivariate interventions, and estimation for interventions that might only encourage treatment as a function of susceptibility.
     

    Location: Information Science Institute (ISI) - 553

    Audiences: Everyone Is Invited

    Contact: Myrl Marmarelis

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  • MHI Seminar - Karen Livescu - Tuesday, May 28th at 3pm in EEB 248 & Zoom

    Tue, May 28, 2024 @ 03:00 PM - 05:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Karen Livescu, Professor TTI-Chicago

    Talk Title: What Do Pre-Trained Speech Representation Models Know?

    Abstract: Pre-trained speech representation models have become ubiquitous in speech processing over the past few years.  They have both improved the state of the art and made it feasible to learn task-specific models with very little labeled data.  However, it is not well understood what linguistic information is encoded in pre-trained models, where in the models it is encoded, and how best to apply this information to downstream tasks. In this talk I will describe recent work that begins to build an understanding of pre-trained speech models, through both layer-wise analysis and benchmarking on tasks.  We consider a number of popular pre-trained models and investigate the extent to which they encode spectral, phonetic, and word-level information.  The results of these analyses also suggest some ways to improve or simplify the application of pre-trained models for downstream tasks.  Finally, I will describe our efforts to benchmark model performance on a variety of spoken language understanding tasks, in order to broaden our understanding of the semantic capabilities of speech models.

    Biography: Karen Livescu is a Professor at TTI-Chicago.  This year she is on sabbatical, splitting her time between the Stanford NLP group and the CMU Language Technologies Institute.  She completed her PhD at MIT in 2005. She is an ISCA Fellow and a recent IEEE Distinguished Lecturer.  She has served as a program chair/co-chair for ICLR, Interspeech, and ASRU, and is an Associate Editor for TACL and IEEE T-PAMI.  Her group's work spans a variety of topics in spoken, written, and signed language processing, with a particular interest in representation learning, cross-modality learning, and low-resource settings.

    Host: Shrikanth Narayanan

    More Info: https://usc.zoom.us/j/98343896109?pwd=VWxRVTJVc3NLMjZGcEVVNGw1a1J0dz09

    More Information: 2024 Karen Livescu Seminar.pdf

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

    Audiences: Everyone Is Invited

    Contact: Marilyn Poplawski

    Event Link: https://usc.zoom.us/j/98343896109?pwd=VWxRVTJVc3NLMjZGcEVVNGw1a1J0dz09

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  • Human-AI Interaction: From Supporting Surgical Training to Inspecting Social Bias in LLMs

    Fri, May 31, 2024 @ 11:00 AM - 12:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Rafal Kocielnik, California Institute of Technology

    Talk Title: Human-AI Interaction: From Supporting Surgical Training to Inspecting Social Bias in LLMs

    Series: AI Seminar

    Abstract: *Meeting hosts only admit on-line guests that they know to the Zoom meeting. Hence, you’re highly encouraged to use your USC account to sign into Zoom. If you’re an outside visitor, please inform us at (aiseminars-poc(at)isi.edu) to make us aware of your attendance so we can admit you. Specify if you will attend remotely or in person at least one business day prior to the event Provide your: full name, job title and professional affiliation and arrive at least 10 minutes before the seminar begins. If you do not have access to the 6th Floor for in-person attendance, please check in at the 10th floor main reception desk to register as a visitor and someone will escort you to the conference room location.
    In this talk, I will present my recent contributions to Human-AI interaction, focusing on two distinct projects looking at opportunities and challenges involved in the use of modern AI. In the first part of my talk, I will present my work on leveraging AI in clinician education, specifically within the surgical context. I will detail my work on utilizing multimodal deep-learning techniques to analyze formative feedback from surgeons to trainees in the context of real-world robot-assisted surgeries. This project marks a significant step forward in harnessing contemporary AI for the specialized domain of surgical education, receiving the best paper award at the ML4H conference. For the second part of my talk, I will focus on Human-AI interaction in the context of empowering domain experts (e.g., social scientists and ethicists) to inspect modern generative AI for the presence of harmful stereotypes. I will describe our BiasTestGPT framework which offers two important contributions: 1) a novel approach for generating high-quality synthetic data for social bias testing at scale and 2) a user-friendly and open-sourced interface for engaging the general public and domain experts in the inspection of modern AI. Together, these projects demonstrate opportunities in leveraging Human-AI interaction for supporting specialized domains and helping inspect the challenges in AI itself. This event will be recorded. It will be posted on our USC/ISI YouTube page within 1-2 business days: https://www.youtube.com/user/USCISI.

    Biography: Rafał Kocielnik is a Postdoctoral Researcher at Caltech's Computing+Mathematical Sciences department, where he also collaborates with Cedars-Sinai Medical Center and Activision Blizzard gaming company. He holds an M.Sc. in Computer Science from the Polish-Japanese Academy of Information Technology, a P.D.Eng. in Industrial Design from Eindhoven University of Technology and completed his Ph.D. in Human-Centered Design & Engineering at the University of Washington, Seattle, in 2021. His focus was on designing engaging conversational interactions for health and behavior change. Awarded a CRA Computing Innovation Fellowship in 2021, his research at Caltech explores the intersection of AI and HCI with applications in surgical training, social bias testing in Generative AI, and toxicity mitigation in gaming. He has received Best Paper awards at CSCW and ML4H, with an Honorable Mention at CUI, underscoring his interdisciplinary focus and commitment to advancing AI and HCI for human-centered applications. Visit links below to subscribe and for details on upcoming seminars: https://www.isi.edu/isi-seminar-series/ https://www.isi.edu/events/

    Host: Myrl Marmarelis and Justina Gilleland + Maura Covaci

    More Info: https://www.isi.edu/events/4976/human-ai-interaction-from-supporting-surgical-training-to-inspecting-social-bias-in-llms/

    Webcast: https://usc.zoom.us/j/99601436181?pwd=d0Y5eTZPbHRjM2t3NHc5cXRMNkE1dz09

    Location: Information Science Institute (ISI) - Conf Rm#1135-1137

    WebCast Link: https://usc.zoom.us/j/99601436181?pwd=d0Y5eTZPbHRjM2t3NHc5cXRMNkE1dz09

    Audiences: Everyone Is Invited

    Contact: Pete Zamar

    Event Link: https://www.isi.edu/events/4976/human-ai-interaction-from-supporting-surgical-training-to-inspecting-social-bias-in-llms/

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