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Events for September 26, 2019

  • Medical Imaging Seminar

    Thu, Sep 26, 2019 @ 10:30 AM - 11:30 AM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars

    Speaker: Ye Tian, University of Utah

    Talk Title: Radial Simultaneous Multi-slice MRI for Cardiac Perfusion Assessment

    Series: Medical Imaging Seminar Series

    Abstract: First-pass myocardial perfusion MRI is a powerful tool to detect and evaluate coronary artery disease. In this work, we use undersampled radial simultaneous multi-slice (SMS) acquisitions to achieve greater slice coverage and reduced sensitivity to motion, compared to current standard techniques. I will present two acquisition frameworks for myocardial perfusion. One that uses radial SMS and a pixel-tracking method to produce multi-view perfusion images. The other framework uses continuous acquisition without gating or magnetization preparation. This work employed patch-based locally low-rank constraints and temporal total variation constraints.

    Biography: Ye Tian recently completed his Ph.D. at the University of Utah (2014 -“ 2019). He has been working in the cardiovascular MRI group of Utah Center of Advanced Imaging Researches (UCAIR) since May 2016 under the guidance of Edward DiBella and Ganesh Adluru. His interests include myocardial perfusion DCE-MRI, radial SMS, image reconstruction, fast imaging, and myocardial T1 mapping.

    Host: Professor Krishna Nayak

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

    Audiences: Everyone Is Invited

    Contact: Talyia White

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  • NL Seminar Question Answering by Reasoning Across Documents with Graph Convolutional Networks

    Thu, Sep 26, 2019 @ 11:00 AM - 12:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars

    Speaker: Nicola De Cao, University of Amsterdam

    Talk Title: Question Answering by Reasoning Across Documents with Graph Convolutional Networks

    Series: Natural Language Seminar

    Abstract: Most research in reading comprehension has focused on answering questions based on individual documents or even single paragraphs. We introduce a neural model which integrates and reasons relying on information spread within documents and across multiple documents. We frame it as an inference problem on a graph. Mentions of entities are nodes of this graph while edges encode relations between different mentions e.g. within and cross document co reference. Graph convolutional networks GCNs are applied to these graphs and trained to perform multi-step reasoning. Our Entity GCN method is scalable and compact, and it achieves state of the art results on a multi-document question answering dataset, WikiHo.

    Biography: Nicola is a first year Ph.D. candidate at the Institute for Logic, Language and Computation ILLC at the University of Amsterdam.

    He is appointed at the School of Informatics at the University of Edinburgh supervised by Prof Ivan Titov, and he is part of the Edinburgh NLP group. His work focuses on unstructured Machine Reading Comprehension also know as Question Answering.

    Host: Emily Sheng

    More Info: https://nlg.isi.edu/nl-seminar

    Webcast: https://bluejeans.com/s/sgwNF/

    Location: Information Science Institute (ISI) - CR #689

    WebCast Link: https://bluejeans.com/s/sgwNF/

    Audiences: Everyone Is Invited

    Contact: Peter Zamar

    Event Link: https://nlg.isi.edu/nl-seminar

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  • Astani Civil and Environmental Engineering Seminar

    Thu, Sep 26, 2019 @ 04:00 PM - 05:00 PM

    Sonny Astani Department of Civil and Environmental Engineering

    Conferences, Lectures, & Seminars

    Speaker: Prof. William Arnold, Ph.D., University of Minnesota

    Talk Title: Stuck in the muck: Historical insights into emerging contaminants from sediment cores

    Abstract: While many studies on the presence and fate of emerging contaminants have been performed over the past 15+ years, these compounds have been in use for decades. Information about past use provides insight into long term impacts on aquatic systems. Sediment cores provide information about historical use and processing of emerging contaminants. Using cores collected from a lakes with varying degrees of wastewater impact, the records of various antibacterial and antibiotic compounds are analyzed. For triclosan, the levels observed in sediments track with increasing use in a variety of consumer products. The reaction products formed from the chlorination of wastewater and photolysis are also captured in the cores. For antibiotic/antibacterial chemicals used in human and veterinary medicine, sediments also capture the dates of introduction and usage patterns of the chemicals. Quaternary ammonium compounds, used in many consumer products, are also captured in sediment cores. The results provide insight into where efforts should be focused to minimize the introduction of antibiotic/antibacterial chemicals into the environmental.

    Biography: William Arnold is a Distinguished McKnight University Professor and the Joseph T. and Rose S. Ling Professor and Associate Head of the Department of Civil, Environmental, and Geo- Engineering at the University of Minnesota. His research focuses on the fate of organic chemicals in natural and engineered aquatic systems. He received his S.B. in Chemical Engineering from MIT (1994), M.S. in Chemical Engineering from Yale (1995), and Ph.D. in Environmental Engineering from the Johns Hopkins University (1999). He then joined the U of MN faculty. He has won both the AEESP Frontiers in Research Award and Outstanding Publication Award.

    Host: Dr. Daniel McCurry

    More Information: Arnold abstract and bio USC.pdf

    Location: Michelson Center for Convergent Bioscience (MCB) - 102

    Audiences: Everyone Is Invited

    Contact: Evangeline Reyes

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  • Careers in Data Infosession

    Thu, Sep 26, 2019 @ 04:00 PM - 05:00 PM

    USC Viterbi School of Engineering

    Workshops & Infosessions

    Sriram, a USC Alum, Program Director, Data Engineer, currently working at Insight Data Science, will discuss the growing demand for Data Scientists and Data Engineers at companies across the US, and some tips and strategies for how to make the transition into industry. All backgrounds welcome!

    Insight is a tuition-free, 7-week fellowship for high-achieving scientists and engineers looking to transition to thriving careers in data. Insight is committed to increasing diversity in the tech industry. We support fellows from underrepresented communities with mentoring, need-based scholarships, and inclusive practices.

    RSVP Here: USC Infosession on Careers in Data

    Location: Henry Salvatori Computer Science Center (SAL) - 101

    Audiences: Everyone Is Invited

    Contact: Ryan Rozan

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