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Events for March 21, 2018

  • Meet USC: Admission Presentation, Campus Tour, and Engineering Talk

    Wed, Mar 21, 2018

    Viterbi School of Engineering Undergraduate Admission

    University Calendar

    This half day program is designed for prospective freshmen (HS juniors and younger) and family members. Meet USC includes an information session on the University and the Admission process, a student led walking tour of campus, and a meeting with us in the Viterbi School. During the engineering session we will discuss the curriculum, research opportunities, hands-on projects, entrepreneurial support programs, and other aspects of the engineering school. Meet USC is designed to answer all of your questions about USC, the application process, and financial aid.

    Reservations are required for Meet USC. This program occurs twice, once at 8:30 a.m. and again at 12:30 p.m.

    Please make sure to check availability and register online for the session you wish to attend. Also, remember to list an Engineering major as your \"intended major\" on the webform!


    Location: Ronald Tutor Campus Center (TCC) - USC Admission Office

    Audiences: Prospective Freshmen (HS Juniors and Younger) & Family Members

    Contact: Viterbi Admission

  • EE Seminar: IoT in the CMOS Era and Beyond: Leveraging Mixed-Signal Arrays for Ultra-Low-Power Sensing, Computation, and Communication

    Wed, Mar 21, 2018 @ 10:30 AM - 11:30 AM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars

    Speaker: Dr. Siddharth Joshi, University of California, San Diego

    Talk Title: IoT in the CMOS Era and Beyond: Leveraging Mixed-Signal Arrays for Ultra-Low-Power Sensing, Computation, and Communication

    Abstract: Energy efficiencies obtained by analog processing are critical for next-generation \"smart\" sensory systems that implement intelligence at the edge. Such systems are widely applicable in areas like biomedical data acquisition, continuous infrastructure monitoring, intelligent sensor networks, and data analytics. However, adaptive analog computing is sensitive to nonlinearities induced by mismatch and noise, which has limited the application of analog signal processing to signal conditioning prior to quantization. This has relegated the bulk of the processing to the digital domain, or a remote server, limiting the system efficiency and autonomy. This talk highlights principled techniques to algorithm-circuit co-design to overcome these obstacles, leading to energy-efficient high-fidelity mixed-signal computation and adaptation.

    First, I will provide analytical bounds on the energetic advantages derived by alleviating the need for highly accurate and energy-consuming analog-to-digital conversion through high-resolution analog pre-processing. I will then present an embodiment of this principle in a micropower, multichannel, mixed-signal array processor developed in 65nm CMOS. Spatial filtering with the processor yields 84 dB in analog interference suppression at only 2 pJ energy per mixed-signal operation. At the algorithmic level, I will present work on a gradient-free variation of coordinate descent, Successive Stochastic Approximation (S2A). S2A is resilient to the adverse effects of analog mismatch encountered in compact low-power realizations of high-resolution, high-dimensional mixed-signal processing systems. Over-the-air experiments employing S2A in non-line-of-sight demonstrate adaptive beamforming achieving 65 dB of processing gain.

    I will conclude with my vision about the impact of mixed-signal processing on the next generation of computing systems and share my recent work spanning across devices (RRAM), architectures (compute-in memory) and emerging applications(neuromorphic computing). Crossing these hierarchies is critical to leverage emerging technologies in realizing the next generation of sensing, computing, and communicating systems.

    Biography: Siddharth Joshi is a Postdoctoral Fellow in the department of Bioengineering at UC San Diego, he completed his PhD in 2017 at the department of Electrical and Computer Engineering, UC San Diego where he also completed his M.S. in 2012. His research focuses on the co-design of custom, non-Boolean and non-von Neumann, hardware and algorithms to enable machine learning and adaptive signal processing in highly resource constrained environments. Before coming to UCSD, he completed a B. Tech from Dhirubhai Ambani Institute of Information and Communication Technology in India.

    Host: Alice Parker, parker@usc.edu, x04476

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

    Audiences: Everyone Is Invited

    Contact: Mayumi Thrasher

  • CS Colloquium: Nithya Sambasivan (Google) - Design for Autonomy and Fairness of New Technology Users in the Global South

    Wed, Mar 21, 2018 @ 11:00 AM - 12:00 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars

    Speaker: Nithya Sambasivan, Google

    Talk Title: Design for Autonomy and Fairness of New Technology Users in the Global South

    Series: CS Colloquium

    Abstract: 2017 saw half the world online. As technology penetration and ecosystem maturity increase, there is a growing intent to use technology for socio-economic development for new technology users. However, complex long-standing challenges like affordability, safety, and socio-religious diktats affect people at the cusp of the internet. My work aims to empower new technology users with increased autonomy and fairness through technology. I present my prior work on design and evaluation of a cost transparency tool intended to help new mobile Internet users; design to tackle abuse and safety vectors for women in Internet technologies; and design and deployment of an information broadcasting system for urban sex workers in India. I show how prevailing HCI assumptions of privacy, trust, and user identities need to be challenged as Internet advances to reach all edges of human society. Through these projects, I show how large problems can be practically addressed through a combination of design, policy, and algorithms.

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

    Biography: Nithya Sambasivan is a researcher focused on technology design for social, economic and political benefits in the Global South. Her research spans the areas of HCI and ICTD, and has won several recognitions at top conferences. She has been a researcher at Google since 2012, where she has co-founded a group to conduct future-facing research on under-represented topics, such as gender equity and new technology users. Her research has influenced several large-scale real-world projects for the next billion users, and has been directly translated to core libraries, metrics, and guidance for Android and Web developers at Build for Billions, design.google/nbu, and Google I/O talks. Nithya has a Ph.D. and MS in information and computer sciences for University of California, Irvine and and MS in Human Computer Interaction (HCI) from Georgia Tech. Her dissertation focused on technology design for the low-income communities of slums, urban sex workers and microentreprises in India. She is a recipient of Google\'s Anita Borg and UC Irvine Dean\'s fellowships. She has interned at Microsoft Research India, Nokia Research Center and IBM TJ Watson.

    Host: Milind Tambe

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

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair

  • INCOSE Webinar 110

    Wed, Mar 21, 2018 @ 11:00 AM - 12:00 PM

    Systems Architecting and Engineering, USC Viterbi School of Engineering

    Conferences, Lectures, & Seminars

    Speaker: Dr, Swaminathan Natarajan, Dr. Anand Kumar, and Subhro Chaudhuri, Chief Scientist, Tata Consultancy, Senior Scientist, TCS Research, and Senior Scientist, TCS Research, respectively

    Talk Title: A Conceptual Model of Systems Engineering

    Series: INCOSE Speaker Series

    Abstract: The Systems Science Working Group has started a new project to devise a conceptual model of systems that is based on key principles and concepts from systems science. This webinar presents an early draft of such a conceptual model. While systems engineering has strong empirical guidance in the form of practices, methods and standards, it is lacking theoretical foundation in comparison to other engineering disciplines. One approach to address this problem is based on the simple insight that solutions in typical engineering disciplines depend on knowledge in their own discipline, but creating a good systems engineering solution depends on bringing together knowledge from many disciplines. As a result, to create theoretical foundations for systems engineering, it is necessary to inquire into how knowledge domains come together in systems.

    This inquiry led to a distinction between domains that carry knowledge about types of wholes vs. domains that carry knowledge about aspects. Theoretical knowledge is built up in aspect domains, while type domains carry knowledge about how various aspects come together in a whole, and how wholes relate to each other. In such a case, Systems engineering can be looked at in terms of four worlds: real, system models, types knowledge and aspects knowledge worlds. Creating an engineering solution involves using type world knowledge to synthesize various aspect solutions, using systems knowledge to ensure compositionality, implementing the solution in real world, and closing gaps between model and reality.

    We are in the early stages of this exploration, but would appreciate anyone who would like to join us in this journey. Please contact us for more information.
    Swaminathan Natarajan, swami.n@tcs.com
    Anand Kumar, anand.ar@tcs.com
    Subhrojyoti Roy Chaudhuri, subhrojyoti.c@tcs.com

    Biography: Dr. Swaminathan Natarajan (Swami) is a Chief Scientist with Tata Consultancy Services Research and has more than 30 years of Industrial experience in Systems architecture, Software architecture and Engineering. He obtained his B.Tech from IIT Madras in 1983 and Ph.D. in computer science from the University of Illinois in 1989. His background includes teaching software engineering at Texas A&M University and Rochester Institute of Technology, as well as applied research positions with Xerox and Motorola India. His work with TCS has focused on systems research, engineering and architecture, including a role as control systems architect for the SKA radio telescope project. He is the editor of ISO 30103, a systems engineering standard on product quality achievement and co-chair of the INCOSE systems science working group.

    Dr. Anand Kumar is a Senior Scientist with TCS Research and has more than 21 years of Industrial experience in Systems architecture, Software architecture and engineering. Anand is a member of the ISO JTC1 SC7 WG42 working group on architecture. He is the co-editor of ISO-IEC-IEEE 42020 standard on architecture processes and ISO-IEC-IEEE 42030 standard on architecture evaluation. Anand is the co-chair of INCOSE Architecture Working group, chair for INCOSE India Architecture working group and ISSS digital product-service systems working group. Anand has authored more than 40 papers in leading international journals and conferences. Anand has been granted 3 patents by US PTO and 2 patents by India PTO.

    Subrojyoti Roy Chaudhuri (Subhro) is a Senior Scientist with TCS research and has around 20 years of experience. He has been instrumental in the research, design and development of many key capabilities produced by TCS such as MasterCraft and Ignio. Subhro represented the Indian team to participate and contribute in design and development of multiple international mega science projects such as the ITER and the Square Kilometer Array (SKA). He is a member of Telescope Manager (TM), an International Consortium and provider of one of the key capabilities of SKA. He currently leads the Telescope Management work package on behalf of the SKA TM consortium and is responsible for the overall design of the monitoring and control solution for SKA. His current area of research entails developing the architecture for the next generation of enabling platforms that would automate the realization of domain specific solutions utilizing robotics and IoT.

    Host: International Council on Systems Engineering (INCOSE)

    More Info: https://incoseevents.webex.com/mw3100/mywebex/default.do?nomenu=true&siteurl=incoseevents&service=6&rnd=0.5636237872535654&main_url=https%3A%2F%2Fincoseevents.webex.com%2Fec3100%2Feventcenter%2Fevent%2FeventAction.do%3FtheAction%3Ddetail%26%26%26EMK%3D483

    Webcast: Event number 599 253 796, Event password INCOSE110

    Location: Online via WebEX

    WebCast Link: Event number 599 253 796, Event password INCOSE110

    Audiences: Everyone Is Invited

    Contact: James Moore II

    Event Link: https://incoseevents.webex.com/mw3100/mywebex/default.do?nomenu=true&siteurl=incoseevents&service=6&rnd=0.5636237872535654&main_url=https%3A%2F%2Fincoseevents.webex.com%2Fec3100%2Feventcenter%2Fevent%2FeventAction.do%3FtheAction%3Ddetail%26%26%26EMK%3D483

  • Automated Geometric Shape Deviation Modeling for Cyber-Physical Additive Manufacturing Systems via Bayesian Neural Networks

    Wed, Mar 21, 2018 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars

    Speaker: Arman Sabbaghi, Purdue University

    Talk Title: Automated Geometric Shape Deviation Modeling for Cyber-Physical Additive Manufacturing Systems via Bayesian Neural Networks

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

    Abstract: A significant challenge in dimensional accuracy control of a cyber-physical additive manufacturing (AM) system is the comprehensive specification of geometric shape deviation models for different computer-aided design (CAD) inputs on its constituent AM processes. Current deviation model building methods cannot satisfactorily address this challenge in practice because they are unable to leverage previously specified deviation models for different shapes and processes in an automated or rapid manner. We present a new model building methodology based on a class of Bayesian neural networks (NNs) that directly address the challenge of cyber-physical AM systems. Our framework enables automated and computationally efficient deviation modeling of different shapes and/or AM processes without sacrificing predictive accuracy, compared to existing modeling methods on the same samples of manufactured shapes. A fundamental innovation in our framework is the design of new and connectable NN structures that can leverage previously specified models for adaptive and principled model building. The power and broad scope of our method is demonstrated with several case studies on both in-plane and out-of-plane deviations for a wide variety of shapes manufactured under different stereolithography processes. Our Bayesian NN methodology for automated and comprehensive deviation modeling can ultimately be applied to advance fast, flexible, and high-quality manufacturing in a cyber-physical AM system. This talk is based on a paper written by Raquel De Souza Borges Ferreira, Dr. Arman Sabbaghi, and Dr. Qiang Huang.

    Biography: Arman Sabbaghi is an Assistant Professor in the Department of Statistics at Purdue University. His research interests include model building for improved control of complex engineering systems, Bayesian data analysis, experimental design, causal inference, and statistical analysis with missing data.

    Host: Prof. Paul Bogdan

    More Information: sabbaghi-t.jpg

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

    Audiences: Everyone Is Invited

    Contact: Talyia White

  • Aerospace and Mechanical Engineering Seminar

    Wed, Mar 21, 2018 @ 03:30 PM - 04:30 PM

    Aerospace and Mechanical Engineering

    Conferences, Lectures, & Seminars

    Speaker: Peter Hagedorn, Professor, Mechanical Engineering, Technische Universität Darmstadt, Germany

    Talk Title: New Results on Self-Excitation in Circulatory and Parametrically Excited Systems

    Abstract: In mechanical engineering systems, self-excited vibrations are in general unwanted and sometimes dangerous. There are many systems exhibiting self-excited vibrations which up to this day cannot be completely avoided, such as brake squeal, the galloping vibrations of overhead transmission lines, the ground resonance in helicopters and others. Most of these systems have in common that in the linearized equations of motion the self-excitation terms are given by non-conservative, circulatory forces and/or parametric excitation. The presentation will discuss some recent results in linear and nonlinear systems of this type.

    Self-excited vibrations have of course been mathematically modelled and studied at least since the times of van der Pol. The van der Pol oscillator is a one degree of freedom system; its linearized equations of motion correspond to an oscillator with negative damping. Sometimes also other self-excited systems present negative damping, which can be made responsible for self-excited vibrations. In all the engineering systems mentioned above however, the self-excitation mechanism is mainly related to the interaction between different degrees of freedom (modes), and the linearized equations of motions contain circulatory terms. This together with parametric resonance is the main excitation mechanism discussed in this paper. Destabilization by \'negative damping\' will not be considered. Also stick-slip phenomena are not in the focus of this presentation; they also do not seem to play an important role in all the examples given above.

    The systems analyzed in this presentation therefore are characterized by the M, D, G, K, N matrices (mass, damping, gyroscopic, stiffness and circulatory matrices, respectively) which may all be time-dependent. In the unstable case, additional nonlinear terms do of course limit the vibration amplitudes. Different types of bifurcations relevant for these systems have recently been studied in the literature.

    In the first part, MDGKN-systems with constant coefficients will be discussed. For a long time it has been well known, that the stability of such systems can be very sensitive to damping, and also to the symmetry properties of the mechanical structure. Recently, several new theorems were proved concerning the effect of damping on the stability and on the self-excited vibrations of the linearized systems. The importance of these results for practical mechanical engineering systems will be discussed. It turns out that the structure of the damping matrix is of utmost importance, and the common assumption, namely representing the damping matrix as a linear combination of the mass and the damping matrices, may give completely misleading results for the problem of instability and the onset of self-excited vibrations.

    The second case considered deals with MDGKN-systems with time-periodic coefficients. The stability of these systems can be studied via Floquet theory. A typical property of parametric instability behavior is the existence of combination resonances. However, if parametric excitation in the system is simultaneously present in the K and the N matrices and/or there are excitation terms which are not all in phase, an atypical behavior may occur: The linear system may then for example be unstable for all frequencies of the parametric excitation, and not only in the neighborhood of certain discrete frequencies. Such atypical parametric instability happens even for M, D, G constant and zero mean values for the matrices K(t) and N(t). This was recently observed at the linearized equations of motion for a minimal model of a squealing disk brake. It turns out, that an even much simpler example of such a situation was given about 70 years ago by Lamberto Cesari, but seems to have fallen into oblivion. Until recently it was thought that such out of phase terms in the parametric excitation would not occur in engineering systems. In the presentation it is shown that they may indeed occur for example in the model of a squealing brake and probably in many other mechanical engineering systems, as long as there is slip with friction between solid bodies.

    In the unstable case, additional nonlinear terms do of course limit the vibration amplitudes. Different types of bifurcations relevant for these systems are studied using normal form theory, in particular for the \'Cesari equations\' with additional nonlinearities.

    Host: Department of Aerospace and Mechanical Engineering

    Location: Seaver Science Library (SSL) - 150

    Audiences: Everyone Is Invited

    Contact: Ashleen Knutsen

  • CAIS Seminar: Dr. Ian Holloway (UCLA) - Social Networking Site Data Mining to Understand Substance Use and HIV Risk Among Gay, Bisexual and Other Men Who Have Sex With Men

    Wed, Mar 21, 2018 @ 04:00 PM - 05:00 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars

    Speaker: Dr. Ian Holloway, UCLA

    Talk Title: Social Networking Site Data Mining to Understand Substance Use and HIV Risk Among Gay, Bisexual and Other Men Who Have Sex With Men

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

    Abstract: Dr. Holloway\'s presentation will outline the development of a culturally congruent data collection and mining module (DCMM) to study the social networking site (SNS) use patterns, substance use and HIV risk and protective behaviors of gay, bisexual and other men who have sex with men (MSM). Data gathered through the DCMM will be used to inform just-in-time adaptive interventions to prevent incidence of new HIV cases among this population disproportionately impacted by HIV/AIDS.

    This lecture satisfies requirements for CSCI 591: Research Colloquium

    Biography: Dr. Holloway is an Assistant Professor in the Department of Welfare at the UCLA Luskin School of Public Affairs and the Director of the Southern California HIV/AIDS Policy Research Center. His applied behavioral health research examines the contextual factors that contribute to heath disparities among sexual and gender minority populations. Dr. Holloway is particularly interested in how social media and new technologies can be harnessed for health promotion and disease prevention. He holds dual master\'s degrees in social work and public health from Columbia University and a doctorate in social work from the University of Southern California.

    Host: Milind Tambe

    Location: Seeley Wintersmith Mudd Memorial Hall (of Philosophy) (MHP) - 101

    Audiences: Everyone Is Invited

    Contact: Computer Science Department

  • CS Colloquium: Mark Bun (Princeton University) - Finding Structure in the Landscape of Differential Privacy

    Wed, Mar 21, 2018 @ 04:00 PM - 05:00 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars

    Speaker: Mark Bun, Princeton University

    Talk Title: Finding Structure in the Landscape of Differential Privacy

    Series: CS Colloquium

    Abstract: Differential privacy offers a mathematical framework for balancing two goals: obtaining useful information about sensitive data, and protecting individual-level privacy. Discovering the limitations of differential privacy yields insights as to what analyses are incompatible with privacy and why. These insights further aid the quest to discover optimal privacy-preserving algorithms. In this talk, I will give examples of how both follow from new understandings of the structure of differential privacy.

    I will first describe negative results for private data analysis via a connection to cryptographic objects called fingerprinting codes. These results show that an (asymptotically) optimal way to solve natural high-dimensional tasks is to decompose them into many simpler tasks. In the second part of the talk, I will discuss concentrated differential privacy, a framework which enables more accurate analyses by precisely capturing how simpler tasks compose

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

    Biography: Mark Bun is a postdoctoral researcher in the Computer Science Department at Princeton University. He is broadly interested in theoretical computer science, and his research focuses on understanding foundational problems in data privacy through the lens of computational complexity theory. He completed his Ph.D. at Harvard in 2016, where he was advised by Salil Vadhan and supported by an NDSEG Research Fellowship.

    Host: Aleksandra Korolova

    Location: Ronald Tutor Hall of Engineering (RTH) - 217

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair