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Events for September 11, 2019

  • Repeating EventSix Sigma Green Belt for Process Improvement

    Wed, Sep 11, 2019 @ 09:00 AM - 05:00 PM

    Executive Education

    Conferences, Lectures, & Seminars


    Abstract: Learn how to integrate principles of business, statistics, and engineering to achieve tangible results. Master the use of Six Sigma to quantify the critical quality issues in your company. Once the issues have been quantified, statistics can be applied to provide probabilities of success and failure. Six Sigma methods increase productivity and enhance quality.

    More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-green-belt-process-improvement/

    Audiences: Registered Attendees

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    Posted By: Corporate & Professional Programs

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  • Networking Open Forum

    Wed, Sep 11, 2019 @ 01:00 PM - 02:00 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    Increase your career and internship knowledge on networking by attending this professional development Q&A moderated by Viterbi Career Connections staff or Viterbi employer partners.

    For more information about Labs & Open Forums, please visit viterbicareers.usc.edu/workshops.

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

    Audiences: All Viterbi Students

    Posted By: RTH 218 Viterbi Career Connections

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  • Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute Seminar

    Wed, Sep 11, 2019 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Professor Arun Kumar, Department of Computer Science & Engineering & Halicioglu Data Science Institute, University of California, San Diego

    Talk Title: Democratizing Machine Learning-based Data Analytics

    Series: Center for Cyber-Physical Systems and Internet of Things

    Abstract: As machine learning (ML) permeates data-driven applications in enterprise, Web, and scientific domains, data management and systems bottlenecks in ML are proving increasingly critical. The overarching goal of my research is to mitigate such bottlenecks and improve the efficiency of ML systems and productivity of ML users, which in turn can help reduce costs and democratize ML-based analytics. Toward this grand goal, we are building abstractions, algorithms, and systems to improve the processes of sourcing and preparing data for ML, performing iterative ML model selection, and integrating ML models with data-driven applications.

    In this talk, I will give an overview of our recent work on all these fronts, focusing specifically on a new direction that could transform how ML systems are built: multi-query optimization for ML. Drawing on the lessons of decades of work on query optimization in relational systems, I will talk about some of our recent work on connecting linear algebra, learning theory, and optimization theory with scalable system design and implementation to accelerate the model selection process in ML systems. Our approach is a step towards bridging the large gap between current ML system abstractions and the level at which ML users think, has implications for both statistical models and deep learning, and could lay a principled systems foundation for new AutoML frameworks.


    Biography: Arun Kumar is an Assistant Professor in the Department of Computer Science and Engineering and Halicioglu Data Science Institute at the University of California, San Diego. He is a member of the Database Lab and Center for Networked Systems and an affiliate member of the AI Group. His primary research interests are in data management and systems for machine learning/artificial intelligence-based data analytics. Systems and ideas based on his research have been released as part of the MADlib open-source library, shipped as part of products from EMC, Oracle, Cloudera, and IBM, and used internally by Facebook, LogicBlox, Microsoft, and other companies. He is a recipient of two SIGMOD research paper awards in 2019 and 2014, three distinguished reviewer awards from SIGMOD/VLDB in 2019 and 2017, the 2016 PhD dissertation award from UW-Madison CS, a 2016 Google Faculty Research Award, a 2018 Hellman Fellowship. Research webpage: https://adalabucsd.github.io/

    Host: Paul Bogdan

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

    Audiences: Everyone Is Invited

    Posted By: Talyia White

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  • AME Seminar

    Wed, Sep 11, 2019 @ 03:30 PM - 04:30 PM

    Aerospace and Mechanical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Eckart Meiburg, UC Santa Barbara

    Talk Title: Settling of Cohesive Sediment: Particle-resolved Simulations

    Abstract: We develop a physical and computational model for performing fully coupled, grain resolving Direct Numerical Simulations of cohesive sediment, based on the Immersed Boundary Method. The model distributes the cohesive forces over a thin shell surrounding each particle, thereby allowing for the spatial and temporal resolution of the cohesive forces during particle particle interactions.

    We test and validate the cohesive force model for binary particle interactions in the Drafting Kissing Tumbling (DKT) configuration. Cohesive sediment grains can remain attached to each other during the tumbling phase following the initial collision, thereby giving rise to the formation of flocs. The DKT simulations demonstrate that cohesive particle pairs settle in a preferred orientation, with particles of very different sizes preferentially aligning themselves in the vertical direction, so that the smaller particle is drafted in the wake of the larger one. This preferred orientation of cohesive particle pairs is found to remain influential for much larger simulations of 1,261 polydisperse particles released from rest. These simulations reproduce several earlier experimental observations by other authors, such as the accelerated settling of sand and silt particles due to particle bonding, the stratification of cohesive sediment deposits, and the consolidation process of the deposit. This final phase also shows the build-up of cohesive and direct contact intergranular stresses. The simulations demonstrate that cohesive forces accelerate the overall settling process primarily because smaller grains attach to larger ones and settle in their wakes. An investigation of the energy budget shows that the work of the collision forces substantially modifies the relevant energy conversion processes.

    Bio
    Eckart Meiburg received his Ph.D. from the University of Karlsruhe. After a postdoc at Stanford, he became an assistant professor in applied mathematics at Brown. He then moved to USC as associate then full professor. He later moved to UC Santa Barbara.

    His research interests are fluid dynamics and transport phenomena, primarily computational fluid dynamics. He uses highly resolved direct numerical simulations to investigate physical mechanisms governing the spatio temporal evolution of a wide variety of geophysical, porous media, and multiphase flow fields. Some of his current interests are gravity and turbidity currents, Hele Shaw displacements, double diffusive phenomena in particle laden flows, and internal bores.

    Meiburg has received a Presidential Young Investigator Award, a Humboldt Senior Research Award, and a Senior Gledden Fellowship (Institute of Advanced Studies, University of Western Australia). He is fellow of the American Physical Society and the ASME, was the 2012 Lorenz G. Straub Award Keynote Speaker (Univ. Minn.), gave the Ronald F. Probstein Lecture at MIT in 2018, and was Shimizu Visiting Professor at Stanford University.

    Host: AME Department

    More Info: https://ame.usc.edu/seminars/

    Location: John Stauffer Science Lecture Hall (SLH) - 102

    Audiences: Everyone Is Invited

    Posted By: Tessa Yao

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  • Association for Advancement of Artificial Intelligence Info Session

    Wed, Sep 11, 2019 @ 07:30 PM - 08:30 PM

    Viterbi School of Engineering Student Organizations

    Workshops & Infosessions


    Come kick off the semester with AAAI at our Fall 2019 Info Session!

    Join AAAI next Wednesday for an evening of good food and even better conversation. At our kickoff event for the semester, learn more about the club, meet other members, and get involved in our AI community here at USC. Enjoy free food, get to know us, get a sneak peek at some of the exciting events we have in the works for this year, and learn how you can get involved! We look forward to seeing you!

    When: 7:30 - 8:30 pm, Wednesday 9/11
    Where: GFS 106
    Free food will be provided

    RSVP HERE

    Location: GFS 106

    Audiences: Everyone Is Invited

    Posted By: USC AAAI

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