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Conferences, Lectures, & Seminars
Events for November

  • Experience Viterbi: Research

    Fri, Nov 01, 2019 @ 02:30 PM - 03:20 PM

    USC Viterbi School of Engineering, Viterbi School of Engineering Student Affairs

    Conferences, Lectures, & Seminars


    Speaker: Prof. Mahta Moghaddam,

    Abstract: Mahta Moghaddam, engineering professor at USC Viterbi School of Engineering, discusses her research in radar systems, microwave remote sensing for environmental applications, medical imaging, and focused microwave therapy and intraoperative monitoring systems. Discover how this work impacts society as well as how students can benefit from research experience outside the classroom.

    Host: USC Viterbi Undergraduate Programs and Women in Engineering

    Location: Seeley G. Mudd Building (SGM) - 101

    Audiences: Everyone Is Invited

    Posted By: Amanda McCraven

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  • 2019 Fred S. Grodins Keynote Lecture

    Fri, Nov 01, 2019 @ 04:00 PM - 05:30 PM

    Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Matthew Tirrell, Ph.D., Professor and Dean, Pritzker School of Molecular Engineering, University of Chicago and Argonne National Laboratory

    Talk Title: Polyelectrolyte complexation: From phase separation to self-assembly to therapeutic nanoparticles

    Abstract: Polyelectrolyte complexation expands the toolset for useful self-assembled objects and materials. Liquid-liquid phase separation can be used for man-made encapsulation applications just as it has evolved for creating membrane-less intracellular compartments in biology. Micelles formed from block copolymers with electrostatically complexed cores can be made and used for therapeutic protein and nucleic acid delivery. Examples of these properties will be discussed culminating in our work on the delivery of micro-RNA inhibitors to retard undesired vascular remodeling in atherosclerosis and arterio-venousfistulae.

    Biography: In 2011, Matthew Tirrell was appointed as the founding Pritzker Director and Dean of the Faculty of the Institute for Molecular Engineering and established the first University of Chicago engineering
    program, which he continues to oversee (now the Pritzker School of Molecular Engineering). Professor Tirrell simultaneously served as Deputy Laboratory Director for Science (September 2015 - April 2018) and Chief Research Officer (January 2017 - March 2018) at Argonne National Laboratory. Immediately prior to joining the University of Chicago, he was the Arnold and Barbara Silverman Professor and Chair of Bioengineering at the University of California, Berkeley, with additional appointments in chemical engineering and materials science & engineering, as well as a Faculty Scientist appointment at the
    Lawrence Berkeley National Laboratory. Dr. Tirrell completed ten years as Dean of Engineering at the University of California, Santa Barbara on June 30, 2009. From 1977 to 1999, he was on the faculty of Chemical Engineering and Materials Science at the University of Minnesota, where he served as department head from 1994 to 1999. Tirrell received a B.S. in Chemical Engineering at Northwestern
    University in 1973 and a Ph.D. in 1977 in Polymer Science from the University of Massachusetts. He has co-authored more than 390 papers and one book, has supervised over 95 Ph.D. students and 50 postdoctoral researchers. Professor Tirrell is a member of the National Academy of Engineering, the National Academy of Sciences, the American Academy of Arts & Sciences and the Indian National Academy of Engineering, and is a Fellow of the American Institute of Medical and Biological Engineers, the AAAS, and the American Physical Society.

    Host: Department of Biomedical Engineering

    More Info: https://bme.usc.edu/about/keynote-lecture-series/abstracts/

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

    Audiences: Department of Biomedical Engineering faculty and students

    Posted By: Greta Harrison

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

    Mon, Nov 04, 2019 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Professor Stephen Boyd, Electrical Engineering, Stanford University

    Talk Title: Convex Optimization

    Series: Cyber-Physical Systems Joint Seminar Series

    Abstract: Convex optimization has emerged as useful tool for applications that includedata analysis and model fitting, resource allocation, engineering design, network design and optimization, finance, and control and signal processing. After an overview of the mathematics, algorithms, and software frameworks for convex optimization, we turn to common theme that arise across applications, such as sparsity and relaxation. We describe recent work on real-time embedded convex optimization, in which small problems are solved repeatedly in millisecond or microsecond time frames, and large-scale distributed convex optimization, in which many solvers are coordinated to solve enormous problems.

    Biography: Stephen P. Boyd is the Samsung Professor of Engineering, Professor of Electrical Engineering in the Information Systems Laboratory, and chair of the Electrical Engineering Department at Stanford University. He has courtesy appointments in the Department of Management Science and Engineering and the Department of Computer Science, and is a member of the Institute for Computational and Mathematical Engineering. His current research focus is on convex optimization applications in control, signal processing, machine learning, and finance.

    Professor Boyd received an AB degree in Mathematics, summa cum laude, from Harvard University in 1980, and a PhD in EECS from U. C. Berkeley in 1985. In 1985 he joined the faculty of Stanford's Electrical Engineering Department. He has held visiting Professor positions at Katholieke University (Leuven), McGill University (Montreal), Ecole Polytechnique Federale (Lausanne), Tsinghua University (Beijing), Universite Paul Sabatier (Toulouse), Royal Institute of Technology (Stockholm), Kyoto University, Harbin Institute of Technology, NYU, MIT, UC Berkeley, CUHK-Shenzhen, City University of Hong Kong, and IMT Lucca. He holds honorary doctorates from Royal Institute of Technology (KTH), Stockholm, and Catholic University of Louvain (UCL).

    Professor Boyd has received many awards and honors for his research in control systems engineering and optimization, including an ONR Young Investigator Award, a Presidential Young Investigator Award, and the AACC Donald P. Eckman Award. In 2013, he received the IEEE Control Systems Award, given for outstanding contributions to control systems engineering, science, or technology. In 2012, Michael Grant and he were given the Mathematical Optimization Society's Beale-Orchard-Hays Award, given every three years for excellence in computational mathematical programming. He is a Fellow of the IEEE, SIAM, and INFORMS, a Distinguished Lecturer of the IEEE Control Systems Society, a member of the US National Academy of Engineering, and a foreign member of the Chinese Academy of Engineering. He has been invited to deliver more than 90 plenary and keynote lectures at major conferences in control, optimization, signal processing, and machine learning.

    At Stanford, he has served as director of the Information Systems Laboratory, chair of the (university wide) Library Committee, chair of the David Packard EE Building Planning & Design Committee, and as a member of the (university wide) Advisory Board.


    Host: Paul Bogdan, pbogdan@usc.edu

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

    Audiences: Everyone Is Invited

    Posted By: Talyia White

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  • Repeating EventLean Green Belt

    Tue, Nov 05, 2019 @ 09:00 AM - 05:00 PM

    Executive Education

    Conferences, Lectures, & Seminars


    Abstract: This three-day course provides an in-dept understanding of Lean enterprise principles and how to apply them within your organization.


    More Info: https://viterbiexeced.usc.edu/engineering-program-areas/industrial-systems-engineering/lean-green-belt/

    Audiences: Registered Attendees

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    Posted By: Corporate & Professional Programs

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  • ISE 651 - Epstein Seminar

    Tue, Nov 05, 2019 @ 03:30 PM - 04:50 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Archis Ghate, Professor and Associate Chair

    Talk Title: Optimal Fractionation in Radiotherapy

    Host: Dr. Sze-chuan Suen

    More Information: November 5, 2019.pdf

    Location: Ethel Percy Andrus Gerontology Center (GER) - 206

    Audiences: Everyone Is Invited

    Posted By: Grace Owh

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  • Mork Family Department of Chemical Engineering and Materials Science Seminar - Distinguished Lecture Series

    Tue, Nov 05, 2019 @ 04:00 PM - 05:20 PM

    Mork Family Department of Chemical Engineering and Materials Science

    Conferences, Lectures, & Seminars


    Speaker: Professor Jason R. Trelewicz, Department of Materials Science and Chemical Engineering. Stony Brook University

    Talk Title: Controlling the Stability and Radiation Tolerance of Nanocrystalline Alloys

    Abstract: Stable nanocrystalline phases leveraging grain boundary segregation are being realized in a myriad of alloy systems and driving advances in the design of bulk nanocrystalline materials. However, augmenting the chemical state of the grain boundaries for stabilization purposes can also have marked impacts on their structure and in turn, the performance of the material in extreme environments. In this presentation, we explore nanoscale grain boundary engineering approaches for the design of tungsten as a plasma facing material for fusion reactors. Dopant species and concentrations are first identified through lattice Monte Carlo modeling and used to guide powder metallurgy synthesis of ternary nanocrystalline tungsten alloys. Through synchrotron x-ray diffraction and small angle x-ray scattering experiments, we select optimized alloy chemistries containing nanoscale compositional heterogeneities for enhanced stability and sinterability. In light of these results, we then probe the effect of grain boundary doping on the coupling between microstructural evolution and irradiation damage state using in situ heavy ion irradiation experiments. Defect evolution is mapped up to 20 dpa and bridged to high-dose stability using ex situ experiments up to 400 dpa. The addition of grain boundary dopants is shown to stabilize the nano-alloy against irradiation induced grain growth, which is correlated to evolving defect state out to the maximum dose of 400 dpa. Mechanistic insights on the role of grain boundaries in damage accumulation are gained using molecular dynamics displacement cascade simulations, demonstrating that the grain boundary character and damage proximity govern the balance between defect formation, migration, and recombination.



    Host: Dr. Hodge

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

    Audiences: Everyone Is Invited

    Posted By: Karen Woo/Mork Family

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  • Repeating EventLean Green Belt

    Wed, Nov 06, 2019 @ 09:00 AM - 05:00 PM

    Executive Education

    Conferences, Lectures, & Seminars


    Abstract: This three-day course provides an in-dept understanding of Lean enterprise principles and how to apply them within your organization.


    More Info: https://viterbiexeced.usc.edu/engineering-program-areas/industrial-systems-engineering/lean-green-belt/

    Audiences: Registered Attendees

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    Posted By: Corporate & Professional Programs

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  • PhD Academic Career Mentoring Panel Series

    Wed, Nov 06, 2019 @ 12:00 PM - 02:00 PM

    Viterbi School of Engineering Doctoral Programs

    Conferences, Lectures, & Seminars


    Speaker: Dr. Timothy Pinkston, Vice Dean for Faculty Affairs, and Faculty Panel,

    Talk Title: Applying and Interviewing for Academic Positions

    Abstract: The Viterbi School of Engineering initiated an Academic Career Mentoring Panel Series to encourage Ph.D. students and postdocs to pursue a rewarding career in academia and research. Distinguished faculty will discuss their academic paths and offer strategic advice and answer your questions. Engineering Ph.D. students and postdocs from all areas and departments are strongly encouraged to attend.

    Host: Viterbi School of Engineering

    More Info: https://viterbigrad.usc.edu/instructional-support/events-workshops/phd-academic-career-mentoring-panel-series/

    Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 116

    Audiences: Ph.D. and Postdoctoral

    Posted By: Tracy Charles

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

    Wed, Nov 06, 2019 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Prabal Dutta, University of California, Berkeley

    Talk Title: Enabling the SmartGrid with IoT Sensors and Edge-Cloud Analytics

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

    Abstract: Wireless sensors and edge-cloud analytics have the potential to gather and process vast amounts of data about the physical world, offering radical new insights about everything from critical infrastructure to interpersonal interactions. But designing, deploying, and operating geographically-distributed systems consisting a hierarchy of sensing, storage, compute, and communication elements raises interesting new challenges across the system stack. In this talk, we will discuss our experiences designing new IoT systems to address several power and power grid monitoring problems. In particular, this talk will focus on three systems-”PowerBlade, Triumvi, and GridWatch-”and their motivation, design, and deployment. PowerBlade explores how to cost-effectively characterize, capture, and classify widespread plug-load energy usage-”representing the fastest growing and least understood segment of end-use energy consumption-”across hundreds of homes and offices representing tens of thousands of sensors. Triumvi explores how to make circuit level energy metering, useful for a variety of facilities trending, energy savings, and fault detection & diagnostics applications, more efficient and scalable. Finally, GridWatch explores how to scalably and cost-effectively detect and respond to the power outages that stymie residential and business activity in under-developed power grids using mobile and fixed sensors, data analytics, and reporting systems in Sub-Saharan Africa, finding that conventional approaches to outage detection systems vastly underreport customer experiences. These systems all share a similar architecture, require new sensor devices and edge-cloud data processing, and wrestle with power management and networking. But they ultimately demonstrate both the tremendous potential and the significant challenges of this nascent computing class.


    Biography: Prabal Dutta is an Associate Professor of Electrical Engineering and Computer Sciences at the University of Calfornia at Berkeley, where he co-directors the CONIX Research Center. Previously, he was a Morris Wellman Faculty Development Associate Professor of Electrical Engineering and Computer Science at the University of Michigan. His interests span circuits, systems, and software, with a focus on mobile, wireless, embedded, networked, and sensing systems with applications to health, energy, and the environment. His work has yielded dozens of hardware and software systems, has won five Top Pick/Best Paper Awards, two Best Paper Nominations, and a Potential Test of Time 2025 Award, as well as several demo, design, and industry competitions. His work has been directly commercialized by a dozen companies and indirectly by many dozens more, has been utilized by thousands of researchers and practitioners worldwide, and is on display at Silicon Valley's Computer History Museum.

    His research has been recognized with an Alfred P. Sloan Research Fellowship, an NSF CAREER Award, a Popular Science Brilliant Ten Award, an Intel Early Career Faculty Fellowship, and as a Microsoft Research Faculty Fellowship Finalist. He has served as chair or co-chair of MobiSys '18, BuildSys '17, IPSN '17, ESWEEK '17 IoT Day, HotMobile '16, SenSys '14, and HotPower '11, and on the DARPA ISAT Study Group from 2012-2016, where he co-chaired numerous studies. He holds a Ph.D. in Computer Science from UC Berkeley (2009), where NSF and Microsoft Research Graduate Fellowships supported his research. He received an M.S. in Electrical Engineering (2004) and a B.S. Electrical and Computer Engineering (1997), both from The Ohio State University. Website: http://www.eecs.berkeley.edu/~prabal

    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, Nov 06, 2019 @ 03:30 PM - 04:30 PM

    Conferences, Lectures, & Seminars


    Speaker: Carlos M. Portela, Caltech

    Talk Title: Fabrication, Mechanical Characterization, and Modeling of 3D Architected Materials upon Static and Dynamic Loading

    Abstract: Architected materials have been ubiquitous in nature, enabling unique properties that are unachievable by monolithic, homogeneous materials. Inspired by natural processes, man-made three-dimensional (3D) architected materials have been reported to enable novel mechanical properties such as high stiffness- to-density ratios or extreme resilience, increasingly so when nanoscale size effects are present. However, most architected materials have relied on advanced additive manufacturing techniques that are not yet scalable and yield small sample sizes. Additionally, most of these nano- and micro-architected materials have only been studied in the static regime, leaving the dynamic parameter space unexplored.



    In this talk, we discuss advances in our understanding of architected materials by: (i ) proposing numerical and theoretical tools that predict the behavior of architected materials with non-ideal geometries, (ii ) presenting a pathway for scalable fabrication of tunable nano-architected materials, and (iii ) exploring the response of nano- and micro-architected materials under three types of dynamic loading. We first explore the mechanics of lattice architectures with features at the micro- and millimeter scales, and discuss the effect of nodes (i.e., junctions) to obtain more accurate computational and theoretical predictive tools. Going beyond lattices, we propose alternative node-less geometries that exhibit extreme mechanical resilience at the nanoscale, and we harness self-assembly processes to demonstrate a pathway to fabricate them in cubic-centimeter volumes while maintaining nanoscale resolution. Lastly, we venture into the dynamic regime by designing, fabricating, and testing micro-architected materials that exhibit vibrational band gaps in the MHz regime as well as nano-architected materials with extreme energy absorption upon microparticle supersonic impact.

    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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  • Repeating EventLean Green Belt

    Thu, Nov 07, 2019 @ 09:00 AM - 05:00 PM

    Executive Education

    Conferences, Lectures, & Seminars


    Abstract: This three-day course provides an in-dept understanding of Lean enterprise principles and how to apply them within your organization.


    More Info: https://viterbiexeced.usc.edu/engineering-program-areas/industrial-systems-engineering/lean-green-belt/

    Audiences: Registered Attendees

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    Posted By: Corporate & Professional Programs

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  • Medical Imaging Seminar

    Thu, Nov 07, 2019 @ 10:00 AM - 11:00 AM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Xucheng Zhu, University of California, Berkeley

    Talk Title: 3D Free Breathing Pediatric Pulmonary MRI

    Series: Medical Imaging Seminar Series

    Abstract: In contrast to PET and CT, MRI delivers no ionizing radiation and within a single imaging session provides a wide range of soft tissue characterization and function. Unfortunately, the innumerable air-tissue interfaces in the lung disrupt the MRI signal, rendering lung tissue invisible on conventional MRI. Furthermore, scans are highly susceptible to respiratory and bulk motion that is widely prevalent in pediatric patient populations. For these reasons, MRI is currently insufficient to provide the prognostic and diagnostic information required of imaging studies. We proposed a novel motion corrected imaging framework, combining with a ultra-short echo time(UTE) acquisition to overcome the existing challenges in pediatric lung MRI.

    Biography: Xucheng Zhu is a 5th year PhD student in the joint UC Berkeley and UCSF Bioengineering program, mentored by Dr. Peder Larson. My PhD thesis focuses on 3D high resolution free breathing lung MRI. I also have experience in PET/MR reconstruction and motion correction, dynamic hyperpolarized 13C MRI, and deep learning based medical image enhancement.

    Host: Professor Krishna Nayak, knayak@usc.edu

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

    Audiences: Everyone Is Invited

    Posted By: Talyia White

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  • Lecture of The Honorable Christopher A. Hart

    Thu, Nov 07, 2019 @ 02:00 PM - 03:00 PM

    Sonny Astani Department of Civil and Environmental Engineering

    Conferences, Lectures, & Seminars


    Speaker: The Honorable Christopher A. Hart, Ex-Chairman of the NSTB and Chaiman of the Joint Authorities Technical Review (JATR)

    Talk Title: Automation in Aviation and Automobiles: From Boeing 737 Max to Autonomous Vehicles

    Abstract: See attached

    Host: Dr. Najmedin Meshkati

    More Information: Hon Chris Hart USC ISE 370 Talk on Nov 7th - 10-28-19- Final.pdf

    Location: Seeley G. Mudd Building (SGM) - 123

    Audiences: Everyone Is Invited

    Posted By: Evangeline Reyes

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  • Astani Civil and Environmental Engineering Seminar

    Thu, Nov 07, 2019 @ 04:00 PM - 05:00 PM

    Sonny Astani Department of Civil and Environmental Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Tianzhen Hong, Lawrence Berkeley National Laboratory

    Talk Title: Modeling Urban Buildings for Improvement of Efficiency and Resiliency

    Abstract: U.S. cities consume 70% of primary energy, produces 80% of GDP, and are facing challenges of aging infrastructure, impact of climate change and extreme weather events. Urban systems are interconnected systems of buildings, microclimate, transportation, power and water supply. This talk will introduce urban systems research at the Building Technology and Urban Systems Division, focusing on modeling and simulation of urban buildings to improve their energy efficiency and resiliency, leveraging emerging opportunities in big data, artificial intelligence, and exascale computing.

    Biography: Dr. Tianzhen Hong is a Staff Scientist and Deputy Head of the Building Technologies Department of Lawrence Berkeley National Laboratory. He leads the Urban Systems Group and a research team working on data analytics, modeling, simulation, and policy for design and operation of low energy buildings and sustainable urban systems. He is an IBPSA Fellow and an editor of the Energy and Buildings journal. He has more than 200 publications. He received B.Eng. and Ph.D. from Tsinghua University, China.

    Host: Dr. Burcin Becerik-Gerber

    More Information: Tianzhen Hong_ Abstract_Nov. 7.docx.pdf

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

    Audiences: Everyone Is Invited

    Posted By: Evangeline Reyes

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  • Grand Challenges Lecture Series

    Thu, Nov 07, 2019 @ 05:30 PM - 06:30 PM

    Conferences, Lectures, & Seminars


    Speaker: Professor Hao Li, Viterbi School of Engineering

    Talk Title: AI-Driven Human and Content Digitization

    Series: Grand Challenges Lecture Series

    Host: Viterbi Admission and Student Engagement

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

    Audiences: Everyone Is Invited

    Posted By: Myra Fernandez

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  • W.V.T. RUSCH ENGINEERING HONORS COLLOQUIUM

    Fri, Nov 08, 2019 @ 01:00 PM - 01:50 PM

    USC Viterbi School of Engineering

    Conferences, Lectures, & Seminars


    Speaker: Professor Parag Havaldar, Department of Computer Science, USC

    Talk Title: Industry exploration: Game Development and Design

    Host: EHP

    Audiences: By Invite Only

    Posted By: Amanda McCraven

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  • NextSoft @ MFD and The USC Energy Institute

    Fri, Nov 08, 2019 @ 02:00 PM - 04:00 PM

    Mork Family Department of Chemical Engineering and Materials Science

    Conferences, Lectures, & Seminars


    Speaker: John Mork and Professor Richard Roberts, Mork Family Department of Chemical Engineering & Materials Science

    Talk Title: A Colloquium on the use of DNA in Oilfield Applications

    Host: Mork Family Department of Chemical Engineering & Materials Science

    Location: Ronald Tutor Hall of Engineering (RTH) - 105

    Audiences: Everyone Is Invited

    Posted By: Greta Harrison

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  • *CANCELLED* Fall 2019 Joint CSC@USC/CommNetS-MHI Seminar Series

    Mon, Nov 11, 2019 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Andrea Serrani, Ohio State University

    Talk Title: *THIS TALK IS CANCELLED* -- A Geometric Viewpoint on Dynamic Control Allocation

    Abstract: Input redundancy in a control system is typically resolved by means of (static) control allocation strategies, where the standing assumptions prescribe that one can define a virtual control input that has the same dimensionality of the regulated output. A control strategy designed on the basis of this virtual input is then distributed across the redundant set of actuators via on-line optimization. Essentially, this scenario confines redundancy to the null-space of the input operator, which can be factored out by projection. On the other hand, for the case of input redundancy with full-rank input operators, multiple independently controllable state-trajectories exist that are compatible with a given reference output. In this talk, a comprehensive geometric characterization of input redundant linear systems is offered. It is shown that intrinsic input redundancy can be exploited in the system inverse rather than in the plant model itself, leading to the definition of novel dynamic control allocation strategies. In the proposed scheme, the steady-state behavior of the system is shaped through dynamic optimization of selected performance criteria penalizing both the control input and the state trajectory, while maintaining invariance of the error-zeroing subspace. Illustrative examples are presented to elucidate the applicability and the significance of the method.

    Biography: Andrea Serrani received the Ph.D. degree in Artificial Intelligence Systems from the University of Ancona, Italy, in 1997 and the D.Sc. degree in Systems Science and Mathematics from Washington University in Saint Louis in 2000. Since 2002, he has been with the Department of Electrical and Computer Engineering at The Ohio State University, Columbus, Ohio, where he is currently a Professor and Associate Chair. His research activity spans the fields of control and systems theory, with emphasis on nonlinear and adaptive control, tracking and regulation, and application to aerospace and automotive systems. His latest interests include modeling and control of flapping-wing micro-air vehicles, control of multi-actuated powertrain systems, and guidance and control of hypersonic vehicles. He is the author of more than 150 journal and conference publications, and the co-author (with A. Isidori and L. Marconi) of the book Robust Autonomous Guidance - An Internal Model Approach, published by Springer Verlag. Prof. Serrani serves as the Editor-in-Chief of the IEEE Transactions on Control Systems Technology, and as an Associate Editor the IEEE CSS and IFAC Conference Editorial Boards. He is a past Associate Editor for Automatica and the International Journal of Robust and Nonlinear Control. He was the Program Chair of the 2019 American Control Conference and the General Co-Chair for the 2022 IEEE Conference on Decision and Control.

    Host: Mihailo Jovanovic, mihailo@usc.edu

    More Info: http://csc.usc.edu/seminars/2019Fall/serrani.html

    More Information: 191111_Andrea Serrani_CSC.pdf

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

    Audiences: Everyone Is Invited

    Posted By: Brienne Moore

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  • Remarkable Trajectory Lecture by Gerard Medioni

    Mon, Nov 11, 2019 @ 04:00 PM - 05:30 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Prof. Gerard Medioni, USC

    Talk Title: 40+ Years of Computer Vision at USC

    Series: Remarkable Trajectory Lecture Series

    Host: Computer Science Department

    Location: University Club of USC, Scriptorium Room

    Audiences: Everyone Is Invited

    Posted By: Computer Science Department

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  • ISE 651 - Epstein Seminar

    Tue, Nov 12, 2019 @ 03:30 PM - 04:50 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Yong Huang, Professor, University of Florida

    Talk Title: Bioprinting: Implementation, Process Dynamics, and Process-Induced Cell Injury

    Host: Prof. Yong Chen

    More Information: November 12, 2019.pdf

    Location: Ethel Percy Andrus Gerontology Center (GER) - 206

    Audiences: Everyone Is Invited

    Posted By: Grace Owh

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  • Astani Civil and Environmental Engineering Seminar

    Tue, Nov 12, 2019 @ 04:00 PM - 05:00 PM

    Sonny Astani Department of Civil and Environmental Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Qizhi He, Pacific Northwest National Laboratory (PNNL)

    Talk Title: Machine Learning Enhanced Computational Mechanics: Reduced-Order Modeling and Physics-Informed Data-Driven Computing

    Abstract:
    Advances in the field of machine learning and the increasing availability of data from laboratory/field observations and high-fidelity simulation are quickly changing how the world solves important scientific problems. In this talk, I will present our research on developing integrative computational methods that leverage both physics-based models and data-centric techniques to address various challenges in computational mechanics related to civil, mechanical, and biological applications.

    First, I will introduce physics-preserving reduced order schemes that employ simulation data and subspace projection to reduce computational cost while preserving critical physical properties in modeling fracture mechanics and thermal fatigue of electronic packages. Second, I will describe a manifold learning-based data-driven computing approach for modeling complex materials, where physics-based simulation proceeds interactively with the local data manifold reconstructed from experimental data,circumventing the limitations of using phenomenological constitutive models.

    Finally, I will discuss our recent work in PNNL on developing machine learning framework based on deep neural networks for discovering hidden physics and modeling subsurface flow and transport in heterogenous porous media. The proposed approach allows the seamless fusion and integration of measurements from multiphysics systems and the information provided by the physical conservation laws, which regularize the neural networks as informative priors. The effectiveness of meshfree methods for these data-driven computing will also be demonstrated.
    This work is supported by NSF, US Army Engineer Research, and the DOE ASCR.


    Biography: Dr. Qizhi He is currently a Postdoctoral Research Associate in the Advanced Computing, Mathematics and Data Division at Pacific Northwest National Laboratory (PNNL). He obtained his B.S. in Engineering Mechanics from Wuhan University, M.S. in Computational Mechanics from Dalian University of Technology, and M.A. in Applied Mathematics and Ph.D. in Structural Engineering from the University of California, San Diego (UCSD). His research mainly focuses on the development of machine learning enhanced computational methods to model complex biological and civil systems and provide solutions to protect real-life structures from extreme hazardous events. His work combines the concepts from physics-based modeling, machine learning, and meshfree type approximation and discretization

    Host: Dr. Roger Ghanem

    Location: Kaprielian Hall (KAP) - 209

    Audiences: Everyone Is Invited

    Posted By: Evangeline Reyes

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

    Wed, Nov 13, 2019 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Nikil Dutt, Distinguished Professor, University of California, Irvine

    Talk Title: Computational Self-awareness and Self-organization: A Paradigm for Building Adaptive, Resilient Computing Platforms

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

    Abstract: Self-awareness and self-organization have a long history in biology, psychology, medicine, engineering and (more recently) computing. In the past decade this has inspired new self-aware/self-organizing strategies for building resilient computing platforms that can adapt to the (often conflicting) challenges of resiliency, energy, heat, cost, performance, security, etc. in the face of highly dynamic operational behaviors and environmental conditions. I will begin by outlining a computational self-awareness paradigm that enables adaptivity and which supports system resilience. I will show how computational self-awareness can be deployed to achieve cross-layer resilience on the exemplar CyberPhysical-Systems-on-Chip (CPSoC) platform. CPSoC is a new class of sensor-actuator rich many-core computing platform that intrinsically couples on-chip and cross-layer sensing and actuation to support computational self-awareness. Computational self-awareness is achieved through introspection (i.e., modeling and observing its own internal and external behaviors) combined with both reflexive and reflective adaptations via cross-layer physical and virtual sensing and actuations applied across multiple layers of the hardware/software system stack. Next I will outline strategies for combining computational self-awareness with self-organization for life-cycle management of dependable distributed computing platforms. Our ongoing NSF/DFG Information Processing Factory (IPF) project applies principles inspired by factory management that combine self-awareness and self-organization for continuous operation and optimization of highly-integrated-but-distributed embedded computing platforms. While each IPF computational component exhibits autonomy through self-awareness, collections of IPF entities can self-organize; the resulting emergent behavior must be controlled in order to ensure guaranteed service even under strict safety and availability requirements. I will outline strategies such as proactive reconfiguration to mitigate the risk of failures, self-optimization, self-identification using learning classifiers, and chip-level operation with flexible boundaries between critical and best effort regions, all guided by a self-aware planning component. The talk will conclude with the opportunities and challenges arising from adopting computational self-awareness and self-organization for making complex computational systems more resilient and self-adaptive.

    Biography: Nikil Dutt is a Distinguished Professor of CS, Cognitive Sciences, and EECS at the University of California, Irvine, and also a Distinguished Visiting Professor of CSE at IIT Bombay, India. He received a PhD from the University of Illinois at Urbana-Champaign (1989). His research interests are in embedded systems, EDA, computer architecture and compilers, distributed systems, healthcare IoT, and brain-inspired architectures and computing. He has received numerous best paper awards and is coauthor of 7 books. Professor Dutt has served as EiC of ACM TODAES and AE for ACM TECS and IEEE TVLSI. He is on the steering, organizing, and program committees of several premier EDA and Embedded System Design conferences and workshops, and has also been on the advisory boards of ACM SIGBED, ACM SIGDA, ACM TECS and IEEE ESL. He is an ACM Fellow, IEEE Fellow, and recipient of the IFIP Silver Core Award.

    Host: Jyotirmoy Deshmukh

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

    Audiences: Everyone Is Invited

    Posted By: Talyia White

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  • CAIS Seminar: Sheldon H. Jacobson (University of Illinois) - Creating a Transparent Environment for Political Redistricting

    Wed, Nov 13, 2019 @ 02:00 PM - 03:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Dr. Sheldon H. Jacobson, University of Illinois

    Talk Title: Creating a Transparent Environment for Political Redistricting

    Series: USC Center for Artificial Intelligence in Society (CAIS) Seminar Series

    Abstract: Political redistricting is a multi-criteria problem with conflicting objectives (based on metrics like compactness, population balance, and efficiency gaps, among others). Many of these metrics have received significant attention, though they remain controversial as to which such metrics are best suited to define fair district maps. This research uses a multi-objective optimization approach to reveal obstacles in defining fair district maps. The results obtained challenge a number of common perceptions of redistricting, suggesting that defining fair maps may not only be extremely difficult, but also, simply unrealistic.

    This lecture satisfies requirements for CSCI 591: Research Colloquium. Please note, due to limited capacity in OHE 136, seats will be first come first serve.


    Biography: Sheldon H. Jacobson is a Founder Professor of Computer Science at the University of Illinois. He has a B.Sc. and M.Sc. (both in Mathematics) from McGill University, and a M.S. and Ph.D. (both in Operations Research) from Cornell University. From 2012-2014, he was on leave from the University of Illinois, serving as a Program Director at the National Science Foundation. His research interests span theory and practice, covering decision-making under uncertainty and optimization-based artificial intelligence, with applications in aviation security, public policy, public health, and sports. He has been recognized by numerous awards, including a Guggenheim Fellowship from the John Simon Guggenheim Memorial Foundation. He is a fellow of both IISE and INFORMS.


    Host: USC Center for Artificial Intelligence in Society (CAIS)

    Location: Olin Hall of Engineering (OHE) - 136

    Audiences: Everyone Is Invited

    Posted By: Computer Science Department

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  • AME Seminar

    Wed, Nov 13, 2019 @ 03:30 PM - 04:30 PM

    Aerospace and Mechanical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Paolo Luzzatto-Fegiz,

    Talk Title: Two Problems in Wall-Bounded Flow: Fluid Energy Extraction in Wind Farms, and Surfactant Effects in Superhydrophobic Drag Reduction

    Abstract: In this talk, we consider two fluid problems directly linked to decarbonization efforts. In the first part, we investigate fundamental limits to the performance of large wind farms. Since wind turbines are often deployed in arrays of hundreds of units, wake interactions can lead to drastic losses in power output. Remarkably, while the theoretical Betz maximum has long been established for the output of a single turbine, no corresponding theory appears to exist for a generic, large-scale energy extraction system. We develop a model for an array of energy-extracting devices of arbitrary design and layout, first focusing on the fully-developed regime, which is relevant for large wind farms. We validate our model against data from field measurements, experiments and simulations. By defining a suitable ideal limit, we establish an upper bound on the performance of a large wind farm. This is an order of magnitude larger than the output of existing arrays, thus supporting the notion that large performance improvements may be possible.

    In the second part of this talk, we examine flow past superhydrophobic surfaces (SHS). These coatings have long promised large drag reductions; however, experiments have provided inconsistent results, with many textures yielding little or no benefit. By performing surfactant-laden simulations and unsteadily-driven experiments, we demonstrate that surfactant-induced Marangoni stresses can be to blame. We find that extremely low surfactant concentrations, unavoidable in practice, can drastically increase drag, at least in laminar flows. To obtain accurate drag predictions on SHS, one must therefore solve the mass, momentum, bulk surfactant and interfacial surfactant conservation equations, which is not feasible in most applications. To address this issue, we propose a theory that captures how the near-surface dynamics depend on the seven dimensionless groups for surfactant. We validate our theory extensively in 2D, and describe progress toward 3D and turbulent models. Our theory significantly improves predictions relative to a surfactant-free one, which can otherwise overestimate drag reduction by several orders of magnitude.

    Here are links to papers/resources that form the basis for this talk:

    https://doi.org/10.1103/PhysRevFluids.3.093802
    https://doi.org/10.1073/pnas.1702469114
    https://doi.org/10.1103/PhysRevFluids.3.100507
    https://doi.org/10.1103/APS.DFD.2017.GFM.V0098
    https://arxiv.org/abs/1904.01194

    Biography: Paolo Luzzatto-Fegiz graduated with a BEng in Aerospace Engineering from the University of Southampton, where he received the Royal Aeronautical Society Prize for highest first-class degree and the Graham Prize for best experimental project in the School of Engineering Sciences. After a summer working with the ATLAS Magnet Team at CERN, he completed an MSc in Applied Mathematics at Imperial College, and an MS and PhD in Aerospace Engineering at Cornell University. His doctoral work received the Acrivos Award of the American Physical Society for outstanding dissertation in Fluid Dynamics at a U.S. university. He was awarded a Devonshire Postdoctoral Scholarship from the Woods Hole Oceanographic Institution, as well as a Junior Research Fellowship from Churchill College, Cambridge. He is currently an Assistant Professor in Mechanical Engineering at UCSB, where he has received the Northrop Grumman Teaching Award and a Gallery of Fluid Motion Award from APS-DFD. He co-invented a salinity sensor for oceanography that has been adopted by 20 institutions, and led the first microgravity experiment from NSF CBET, which successfully returned in January 2019 from the International Space Station.

    Host: AME Department

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

    Location: 102

    Audiences: Everyone Is Invited

    Posted By: Tessa Yao

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  • Theory Lunch

    Thu, Nov 14, 2019 @ 12:15 PM - 02:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Mengxiao Zhang, CS PhD Student

    Talk Title: Gradient Descent Provably Optimizes Over-Parameterized Neural Networks

    Abstract: This talk is on the paper "Gradient Descent Provably Optimizes Over-Parameterized Neural Networks," which is about how techniques like gradient descent have zero training loss even for objective functions that are non-convex and non-smooth.

    Host: Shaddin Dughmi

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

    Audiences: Everyone Is Invited

    Posted By: Cherie Carter

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  • CS Colloquium: Bryan Perozzi (Google AI) - Machine Learning on Graphs

    Thu, Nov 14, 2019 @ 03:30 PM - 04:50 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Bryan Perozzi, Google AI

    Talk Title: Machine Learning on Graphs

    Series: Computer Science Colloquium

    Abstract: Machine Learning on Graphs (also known as Relational Learning, or Graph-Based Machine Learning) is a branch of ML which focuses on problems where the data items (nodes) contain discrete relationships (edges) between themselves (usually in addition to traditional real-valued feature vectors). The structure of these links between unlabelled data items can be leveraged for both semi-supervised learning and unsupervised learning algorithms.

    In this talk, I will provide an overview of the area, and some recent results from our team in clustering and representation learning. When appropriate, I will try to motivate our research with examples of real world problems.

    This lecture satisfies requirements for CSCI 591: Research Colloquium.


    Biography: Bryan Perozzi is a Senior Research Scientist in Google AI's Algorithms and Optimization group, where he routinely analyzes some of the world's largest (and perhaps most interesting) graphs. Bryan's research focuses on developing techniques for learning expressive representations of relational data with neural networks. These scalable algorithms are useful for prediction tasks (classification/regression), pattern discovery, and anomaly detection in large networked data sets.

    Bryan is an author of 20+ peer-reviewed papers at leading conferences in machine learning and data mining (such as ICML, NeurIPS, KDD, and WWW). His doctoral work on learning network representations was awarded the 2017 KDD Dissertation Award. Bryan received his Ph.D. in Computer Science from Stony Brook University in 2016, and his M.S. from the Johns Hopkins University in 2011.


    Host: Sami Abu-El-Haija

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

    Audiences: Everyone Is Invited

    Posted By: Computer Science Department

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  • Sonny Astani Civil and Environmental Engineering Seminar

    Thu, Nov 14, 2019 @ 04:00 PM - 05:00 PM

    Sonny Astani Department of Civil and Environmental Engineering

    Conferences, Lectures, & Seminars


    Speaker: Prof. Michael Kleeman, Ph.D., University of California, Davis

    Talk Title: Long-term exposure modeling for ultrafine particulate matter

    Abstract: See attached

    Host: Dr. George Ban-Weiss

    More Information: M. Kleeman_Abstract 11-14-2019.pdf

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

    Audiences: Everyone Is Invited

    Posted By: Evangeline Reyes

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  • Processing in Memory (PIM) – Power and Thermal Challenges and Opportunities

    Fri, Nov 15, 2019 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Mircea Stan, University of Virginia

    Talk Title: Processing in Memory (PIM) -“ Power and Thermal Challenges and Opportunities

    Abstract: Memory technology is a defining component of modern computing and has a strong impact on performance, power and cost of computing systems. However, the advances in memory performance have not been able to keep up with the performance advances for CPUs, thus leading to what is known as the memory wall. Depending on the application, the memory wall manifests itself both in terms of memory latency, as well as memory bandwidth. An interesting solution to the memory wall problem is to bring memory closer to the processor, or vice-versa, to move some processing capability in the memory itself -“ this leads to variations of what is known as Near-Memory Processing, Processing in Memory (PiM), etc. This seminar will first introduce a PIM taxonomy along several dimensions of the PiM design space; it will then follow with a history of PIM, then go over several recent PIM examples. The seminar will then go in-depth into the Thermal/Power delivery challenges for PIM that are a result of the increased switching activities inherent to the moving of processing into the memory fabric, and exacerbated by the evolution towards 3D integration due to the slow-down of traditional Moore law methods. The seminar will conclude with some novel solutions that alleviate the Thermal/Power challenges for PiM.

    Biography: Mircea R. Stan received the Ph.D. (1996) and the M.S. (1994) degrees from UMass Amherst and the Diploma (1984) from the Polytechnic Institute in Bucharest, Romania. Since 1996 he has been with the ECE Department at UVa, where he is now the Virginia Microelectronics Consortium (VMEC) Professor. Prof. Stan is teaching and doing research in the areas of high-performance low-power VLSI, temperature-aware circuits and architecture, embedded systems, spintronics, and nanoelectronics. He leads the High-Performance Low-Power (HPLP) lab, is an associate director of the Center for Automata Processing (CAP) and an assistant director of the Center for Research in Intelligent Storage and Processing-in-Memory (CRISP). He was a visiting faculty at UC Berkeley in 2004-2005, at IBM in 2000, and at Intel in 2002 and 1999. He received the 2018 Influential ISCA Paper Award (For 2003 paper Temperature-aware microarchitecture), the NSF CAREER award in 1997 and was a co-author on best paper awards at LASCAS19, SELSE17, ISQED08, GLSVLSI06, ISCA03 and SHAMAN02 and IEEE Micro Top Picks in 2008 and 2003. He gave keynotes at DCAS18, SOCC16, CogArch16, WoNDP15, iNIS15 and CNNA14. He was the chair of the VSA-TC of IEEE CAS in 2005-2007, general chair for ISLPED06 and GLSVLSI04, TPC chair for SOCC18, ISVLSI17, NanoNets07 and ISLPED05, and on technical committees for numerous conferences. He is Associate Editor-in-Chief for the IEEE TVLSI, Senior Editor for the IEEE TNano, AE for IEEE Design & Test, and was an AE for the IEEE TNano in 2012-2014, IEEE TCAS I in 2004-2008 and for the IEEE TVLSI in 2001-2003. Prof. Stan is a fellow of the IEEE, a member of ACM, and of Eta Kappa Nu, Phi Kappa Phi and Sigma Xi.

    Host: Xuehai Qian, xuehai.qian@usc.edu

    More Information: 191115_Mircea Stan_CENG.pdf

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

    Audiences: Everyone Is Invited

    Posted By: Brienne Moore

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  • Fall 2019 Joint CSC@USC/CommNetS-MHI Seminar Series

    Mon, Nov 18, 2019 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Steven Brunton, University of Washington

    Talk Title: Machine Learning and Sparse Optimization for Modeling, Sensing, and Controlling Fluid Dynamics

    Abstract: Many tasks in fluid mechanics, such as design optimization, sensor selection, modeling, and control, are challenging because fluids are nonlinear and exhibit a large range of scales in both space and time. This range of scales necessitates exceedingly high-dimensional measurements and computational discretization to resolve all relevant features, resulting in vast data sets and time-intensive computations. Indeed, fluid dynamics is one of the original big data fields, and many high-performance computing architectures, experimental measurement techniques, and advanced data processing and visualization algorithms were driven by decades of research in fluid mechanics. Despite the increasing volumes of fluid data, low-dimensional patterns often exist, and there are considerable efforts to model the evolution of these dominant coherent structures that are important for engineering objectives. In this talk, I will explore a number of emerging techniques in machine learning and sparse optimization that complement existing numerical and experimental efforts in fluid mechanics. Machine learning comprises a powerful set of techniques to uncover these low-dimensional flow patterns, which in turn enables sparse optimization for efficient sampling and computations. The resulting models are parsimonious, balancing model complexity with descriptive ability while avoiding overfitting. Because fluid dynamics is central to transportation, health, energy, and defense systems, I will emphasize the importance of machine learning solutions that are interpretable, generalizable, and that respect known physics.

    Biography: Steven L. Brunton is the James B. Morrison Associate Professor of Mechanical Engineering at the University of Washington. He is also Adjunct Associate Professor of Applied Mathematics and a Data Science Fellow at the eScience Institute. Steve received the B.S. in mathematics from Caltech in 2006 and the Ph.D. in mechanical and aerospace engineering from Princeton in 2012. His research combines machine learning with dynamical systems to model and control systems in fluid dynamics, biolocomotion, optics, energy systems, and manufacturing. He is a co-author of three textbooks, received the Army and Air Force Young Investigator Program (YIP) awards, and the Presidential Early Career Award for Scientists and Engineers (PECASE).

    Host: Prof. Si-Zhao Qin, sqin@usc.edu

    More Info: http://csc.usc.edu/seminars/2019Fall/brunton.html

    More Information: 191118_Steven Brunton_CSC.pdf

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

    Audiences: Everyone Is Invited

    Posted By: Brienne Moore

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  • CILQ Faculty Seminar

    Mon, Nov 18, 2019 @ 04:00 PM - 05:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Alan Willner, Professor/USC

    Talk Title: High-Capacity Free-Space Communication Links Using Mode-Division Multiplexing

    Abstract: Multiple orthogonal beams, each located on a different spatial mode and carrying independent data, can be simultaneously transmitted between two apertures. This form of spatial multiplexing, known as mode multiplexing, has the potential to significantly increase communication system capacity and spectral efficiency. Of particular note is the multiplexing of orbital-angular-momentum modes for high-capacity free-space optical and millimeter-wave links. We will discuss transmission results, design guidelines, mitigation of turbulence and crosstalk, and classical and quantum channels.

    Host: CSI

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

    Audiences: Everyone Is Invited

    Posted By: Corine Wong

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  • CS Colloquium: Iacopo Masi (USC ISI) - Towards Visual Understanding of Humans for Recognition, Reconstruction, and Synthesis

    Tue, Nov 19, 2019 @ 11:00 AM - 12:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Iacopo Masi, USC

    Talk Title: Towards Visual Understanding of Humans for Recognition, Reconstruction, and Synthesis

    Abstract: Computer vision is arguably the most rapidly evolving topic in computer science, undergoing drastic and exciting changes. A primary goal is teaching machines how to understand and model humans from visual information.

    The main thread of my research is giving machines the capability to (1) build an internal representation of humans, as seen from a camera in uncooperative environments, that is highly discriminative with respect to identity (e.g., person re-identification and face recognition); and (2) to semantically analyze human faces to detect, segment, reconstruct, and synthesis them (e.g., occlusion detection and face completion).

    In this talk, I demonstrate how we can effectively design and learn discriminative representations for person re-identification and how face recognition can improve without the need for massive human supervision or labeled data, using face-specific augmentation. Then I show how to enforce smoothness in a deep neural network for better, structured face occlusion detection and how this occlusion detection can ease the learning of the face completion task.

    This lecture satisfies requirements for CSCI 591: Research Colloquium


    Biography: Iacopo Masi is a Research Computer Scientist at the USC Information Sciences Institute (ISI). He received a Ph.D. in Computer Engineering at the University of Firenze, Italy. He was a postdoctoral scholar at the University of Southern California, USA. Iacopo has been Area-Chair of several WACVs and currently serves as Associate Editor for The Visual Computer - International Journal of Computer Graphics. He organized an International Workshop on Human Identification at ICCV'17 and was Workshop Chair at SIBGRAPI'18. His main research interest lies in solving the computer vision problem, specifically, the subjects of tracking, person re-identification, 2D/3D face recognition, and modeling.

    Host: Bill Swartout

    Location: Ronald Tutor Hall of Engineering (RTH) - 115

    Audiences: Everyone Is Invited

    Posted By: Cherie Carter

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  • ISE 651 - Epstein Seminar

    Tue, Nov 19, 2019 @ 03:30 PM - 04:50 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Michael R. Wagner, Associate Professor, University of Washington

    Talk Title: Profit Estimation Error in the Newsvendor Model

    Host: Dr. Phebe Vayanos

    More Information: November 19, 2019.pdf

    Location: Ethel Percy Andrus Gerontology Center (GER) - 206

    Audiences: Everyone Is Invited

    Posted By: Grace Owh

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  • Mork Family Department of Chemical Engineering and Materials Science Seminar - Distinguished Lecture Series

    Tue, Nov 19, 2019 @ 04:00 PM - 05:20 PM

    Mork Family Department of Chemical Engineering and Materials Science

    Conferences, Lectures, & Seminars


    Speaker: Dr. Baron Peters, University of Illinois Urbana Champaign

    Talk Title: Single atom catalysts on amorphous supports: a wild frontier for ab initio calculations

    Host: Dr. Sharada

    More Information: DLS_Peters.pdf

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

    Audiences: Everyone Is Invited

    Posted By: Karen Woo/Mork Family

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  • AME Seminar

    Wed, Nov 20, 2019 @ 03:30 PM - 04:30 PM

    Aerospace and Mechanical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Eliot Fried, Okinawa Institute of Science and Technology Graduate University(OIST)

    Talk Title: Closed Nonorientable Ribbons from Unstretchable Helicoidal Material Surfaces

    Abstract: A material surface is unstretchable as a two-dimensional physical object if the intrinsic length between each pair of its material points cannot change during any deformation. Intuitively, such a surface can bend and twist but its material filaments can never extend or contract. The constraint that models this intense kinematic idealization must affirm that no surface strain can be developed in any possible deformation, and it must allow for the existence of constraint reactions and the consequential development of related tractions in any deformation. This talk will focus on a theory for determining the shape of closed ribbons made from bending and twisting a unstretchable helicoidal material surface. Surprising connections to the kinematics of underconstrained linkages, the dynamics of closed vortex filaments, and the chemistry of cyclic hydocarbon compounds will be discussed.

    Biography: Eliot Fried earned his Ph.D. in Applied Mechanics from the California Institute of Technology in 1991. He received a National Science Foundation Mathematical Sciences Postdoctoral Fellowship, a Japan Society for the Promotion of Science Postdoctoral Research Fellowship, and a National Science Foundation Research Initiation Award. Currently he heads the Mathematics, Mechanics, and Materials Unit. Previously, at McGill University, he was a Professor of Mechanical Engineering and the Tier 1 Canada Research Chair in Interfacial and Defect Mechanics. Before that he held tenured positions in the Department of Theoretical and Applied Mechanics at the University of Illinois at Urbana-Champaign and the Department of Mechanical Engineering & Materials Science at Washington University in St. Louis. At Illinois, he was a Fellow of the Center of Advanced Study and was awarded a Critical Research Initiative Grant. In his research, he uses statistical and continuum mechanics and thermodynamics, geometry, asymptotic analysis, bifurcation theory, and scientific computing to study fundamental and applied problems involving novel material systems and processes.

    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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  • NL Seminar-Machine Reading for Precision Medicine

    Thu, Nov 21, 2019 @ 11:00 AM - 12:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Hoifung Poon, MSR/UW

    Talk Title: Machine Reading for Precision Medicine

    Series: Natural Language Seminar

    Abstract: The advent of big data promises to revolutionize medicine by making it more personalized and effective, but big data also presents a grand challenge of information overload. For example, tumor sequencing has become routine in cancer treatment, yet interpreting the genomic data requires painstakingly curating knowledge from a vast biomedical literature, which grows by thousands of papers every day. Electronic medical records contain valuable information to speed up clinical trial recruitment and drug development, but curating such real world evidence from clinical notes can take hours for a single patient. NLP can play a key role in interpreting big data for precision medicine. In particular, machine reading can help unlock knowledge from text by substantially improving curation efficiency. However, standard supervised methods require labeled examples, which are expensive and time-consuming to produce at scale. In this talk, I'll present Project Hanover, where we overcome the annotation bottleneck by combining deep learning with probabilistic logic, and by exploiting self supervision from readily available resources such as ontologies and databases. This enables us to extract knowledge from millions of publications, reason efficiently with the resulting knowledge graph by learning neural embeddings of biomedical entities and relations, and apply the extracted knowledge and learned embeddings to supporting precision oncology.


    Biography: Hoifung Poon is the Director of Precision Health NLP at Microsoft Research and an affiliated professor at the University of Washington Medical School. He leads Project Hanover, with the overarching goal of advancing machine reading for precision health, by combining probabilistic logic with deep learning. He has given tutorials on this topic at top conferences such as the Association for Computational Linguistics ACL and the Association for the Advancement of Artificial Intelligence AAAI. His research spans a wide range of problems in machine learning and natural language processing NLP, and his prior work has been recognized with Best Paper Awards from premier venues such as the North American Chapter of the Association for Computational Linguistics NAACL, Empirical Methods in Natural Language Processing EMNLP, and Uncertainty in AI UAI. He received his PhD in Computer Science and Engineering from University of Washington, specializing in machine learning and NLP.

    Host: Emily Sheng

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

    Webcast: https://bluejeans.com/165124022

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

    WebCast Link: https://bluejeans.com/165124022

    Audiences: Everyone Is Invited

    Posted By: Peter Zamar

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  • Ming Hsieh Institute Seminar Series on Integrated Systems

    Fri, Nov 22, 2019 @ 02:00 PM - 03:30 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Firooz Aflatouni, Skirkanich Assistant Professor, University of Pennsylvania

    Talk Title: Electronic-photonic Co-design; from Imaging to Optical Phase Control

    Host: Profs. Hossein Hashemi, Mike Chen, Dina El-Damak, Manuel Monge, Constantine Sideris, and Mahta Moghaddam

    More Information: MHI Seminar Series IS - Firooz Aflatouni.pdf

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

    Audiences: Everyone Is Invited

    Posted By: Jenny Lin

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  • Astani Civil and Environmental Engineering Seminar

    Fri, Nov 22, 2019 @ 03:00 PM - 04:00 PM

    Sonny Astani Department of Civil and Environmental Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Shamin Pazkad, Lehigh University

    Talk Title: Mobile Sensing Platform for Structural Monitoring

    Abstract:
    The rapid revolution in sensing, computation, and communication
    technology in the past twenty years has provided exciting opportunities for the integration of sensing systems to contribute in addressing one of the key questions of the engineering community in realizing resilient systems. It is hard to imagine a future for resilient civil structures and
    infrastructure without embedded interactive sensory networks that can provide comprehensive feedback about the condition of structures, and produce information that can be used in operation, maintenance,rehabilitation and functionality of structures and infrastructure. One of the new sources of data is through mobile sensing. The application of these sensing mechanisms in structural systems is the focus of this presentation.

    =======================================
    Shamim N. Pakzad, Ph.D.,
    Associate Professor and Director of Graduate Studies
    Civil and Environmental Engineering
    Lehigh University

    http://pakzad.atlss.lehigh.edu/
    email: pakzad@lehigh.edu



    Biography: Shamim Pakzad is an Associate Professor of Structural Engineering and Director of Graduate Studies at Lehigh University's Civil and Environmental Engineering Department.

    He completed his doctorate in 2008 at the University of California Berkeley where he worked on development and large scale implementation of low power wireless sensor networks for civil structural systems. His research isfocused on sensing methods, mobile sensing,structural identification,damage detection, structural dynamics, and in a more general sense,structural health monitoring,methods and models for bigdata analysis instructural systems, and realizing resilient communities in smart andconnected cities.


    Host: Dr. Bora Gencturk

    Location: Ray R. Irani Hall (RRI) - 101

    Audiences: Everyone Is Invited

    Posted By: Evangeline Reyes

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  • ***NO ISE 651, Epstein Seminar - Thanksgiving Recess***

    Tue, Nov 26, 2019 @ 03:30 PM - 04:50 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars


    Location: Ethel Percy Andrus Gerontology Center (GER) - 206

    Audiences: Everyone Is Invited

    Posted By: Grace Owh

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