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Conferences, Lectures, & Seminars
Events for December

  • Real-Time Brain-Machine Interface Architectures: Neural Decoding from Plan to Movement

    Thu, Dec 01, 2011 @ 10:30 AM - 11:30 AM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Maryam M. Shanechi, Harvard Medical School, MIT EECS, Massachusetts General Hospital

    Talk Title: Real-Time Brain-Machine Interface Architectures: Neural Decoding from Plan to Movement

    Abstract: Developing brain-machine interfaces (BMI) that aim to enable motor function in patients with movement disabilities is an active area of research in computational neuroscience and neuroengineering. BMIs work by recording the neural activity, mapping or decoding it into a motor command, and then controlling a device such as a robotic arm. Research in this area has largely focused on the problem of restoring the original motor function. However, performance of such BMIs needs to be significantly improved before they become clinically viable. Moreover, while developing high-performance BMIs with the goal of matching the original motor function is indeed valuable, a compelling goal is that of designing BMIs that can surpass original motor function. In this work, I first develop a novel real-time BMI for restoration of natural motor function and then introduce a BMI architecture aimed at enhancing original motor function. I demonstrate the successful implementation of both these designs in rhesus monkeys.

    To facilitate the restoration of lost motor function, I develop a two-stage decoder to decode jointly the target and trajectory of a reaching movement.
    First, the decoder predicts the intended target from the spiking activity prior to movement. Second, it combines the decoded target with the spiking activity during movement to estimate the trajectory. The second stage uses an optimal feedback-control design that emulates the sensorimotor processing underlying actual motor control and directly processes the spiking activity using point process modeling in real time. I show that the two stages of the BMI result in a significantly more robust and accurate estimation of movement than is possible by using either stage alone or by using common regression approaches.

    To enable enhancement of the original motor function, I introduce a real-time concurrent BMI architecture for performing complex tasks that involve a sequence of planned movements. In contrast to a traditional BMI, in this architecture, the BMI decodes all the elements of the sequential motor plan concurrently from working memory prior to movement. This in turn allows the BMI to analyze the complete sequence before action and find potential ways to perform the task more effectively, such as more quickly, than is possible by natural movement. I demonstrate the feasibility of such a concurrent architecture and that indeed sequential motor plans can be decoded simultaneously, accurately, robustly, and in advance of movement.

    Biography: Maryam M. Shanechi received the B.A.Sc. degree with honors in
    Engineering Science from the University of Toronto in 2004 and the S.M. and Ph.D. degrees in Electrical Engineering and Computer Science (EECS) from the Massachusetts Institute of Technology (MIT) in 2006 and 2011, respectively. She is currently a postdoctoral fellow with joint appointments at Harvard Medical School, MIT EECS, and Massachusetts General Hospital. Her research interests are at the interface of computational neuroscience, statistical signal processing, and
    information and control theories. She has received various awards for academic achievement including the Professional Engineers of Ontario (PEO) gold medal and the Wilson Medal. She is the recipient of the Natural Sciences and Engineering Research Council of Canada (NSERC) doctoral fellowship and the Hewlett-Packard (HP) doctoral scholarship.

    Host: Alice C. Parker

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

    Audiences: Everyone Is Invited

    Contact: Annie Yu

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  • Integrated Systems Seminar Series

    Fri, Dec 02, 2011 @ 03:00 PM - 04:30 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Reid Harrison, Intan Technologies, LLC

    Talk Title: Designing Low-Power Integrated Circuits for Neural Sensing Applications

    Host: Hossein Hashemi

    More Information: Seminar_Speaker_Harrison_2011_12_2.pdf

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

    Audiences: Everyone Is Invited

    Contact: Hossein Hashemi

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  • When Information Technology, Music and Medicine Converge

    Mon, Dec 05, 2011 @ 03:00 PM - 04:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Ye Wang, Ph.D., Computer Science Department, National University of Singapore (NUS)

    Talk Title: When Information Technology, Music and Medicine Converge

    Abstract: With the continuing advances in the Internet technology, there has been abundant music (e.g., from YouTube, iTune etc.) available to ordinary users. How to organize/categorize music to enable effective search or recommendation for healthcare applications becomes an important research problem. We are particularly interested in music information retrieval (MIR) and Sound and Music Computing (SMC) technologies which can make the traditionally expensive music therapy (MT) affordable for patients with limited resources to cope with chronic diseases such as Parkinson’s and stroke. In this talk, I will introduce a few computer supported music therapy (CSMT) projects at National University of Singapore, followed by live demos and a discussion of possible research collaborations, available PhD scholarships and research positions.

    Biography: Ye Wang is a tenured Associate Professor in the Computer Science Department at the National University of Singapore (NUS). He established and directed the Sound and Music Computing (SMC) Lab at NUS School of Computing. Before joining NUS he was a Member of the Technical Staff at Nokia Research Center in Tampere, Finland for 9 years. His research interests are in the area of Mobile Computing, and Sound and Music Computing (SMC), in particular Sound Analysis and Music Information Retrieval (MIR). He is especially interested in developing novel applications/systems for music edutainment and e-Health, as well as determining their effectiveness via subjective and objective evaluations. His most recent research involves the design and evaluation of systems to support 1) therapeutic gait training using rhythmic auditory stimulation (RAS), and 2) ear training and singing practice via meaningful feedbacks. In the current academic year he is having his sabbatical leave at the School of Computer Science, Fudan University (17th October 2011 – 16th January, 2012), and at Harvard Medical School (1st February – 31st July 2012).

    Host: Prof. C.-C. Jay Kuo

    Location: Seaver Science Library (SSL) - 150

    Audiences: Everyone Is Invited

    Contact: Talyia Veal

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  • Epstein Institute Seminar Series / ISE 651 Seminar

    Tue, Dec 06, 2011 @ 04:00 PM - 05:20 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Xiao-Li Meng, Whipple V. N. Jones Professor of Statistics and Chair, Department of Statistics, Harvard University

    Talk Title: "Machine Learning with Human Intelligence: Principled Corner Cutting (PC2)"

    Series: Epstein Institute Seminar Series

    Abstract: With the ever increasing availability of quantitative information, especially data with complex spatial and/or temporal structures, two closely related fields are undergoing substantial evolution: Machine learning and Statistics. On a grand scale, both have the same goal: separating signal from noise. In terms of methodological choices, however, it is not uncommon to hear machine learners complain about statisticians’ excessive worrying over modeling and inferential principles to a degree of being willing to produce nothing, and to hear statisticians express discomfort with machine learners’ tendency to let ease of practical implementation trump principled justifications, to a point of being willing to deliver anything. To take advantage of the strengths of both fields, we need to train substantially more principled corner cutters. That is, we must train researchers who are at ease in formulating the solution from the soundest principles available, and equally at ease in cutting corners, guided by these principles, to retain as much statistical efficiency as feasible while maintaining algorithmic efficiency under time and resource constraints. This thinking process is demonstrated by applying the self-consistency principle (Efron, 1967; Lee, Li and Meng, 2012) to handling incomplete and/or irregularly spaced data with non-parametric and semi-parametric models, including signal processing via wavelets and sparsity estimation via the LASSO and related penalties.

    Biography: Dr. Xiao-Li Meng is the Whipple V. N. Jones Professor of Statistics and Chair, Department of Statistics at Harvard University. His research interests include:
    • Statistical inference with partially observed data, pre-processed data, and simulated data.
    • Quantifying statistical information and efficiency in scientific studies, particularly for genetic and environmental problems.
    • Statistical principles and foundational issues, such as multi-party inferences, the theory of ignorance, and the interplay between Bayesian and frequentist perspectives.
    • Effective deterministic and stochastic algorithms for Bayesian and likelihood computation; Markov chain Monte Carlo, especially perfect sampling.
    • Bayesian inference, ranking and mapping.
    • Multi-resolution modelling for signal and image data.
    • Statistical issues in astronomy and astrophysics.
    • Modelling and imputation in health and medical studies.
    • Elegant mathematical statistics.

    Education
    • 1990: Ph.D. in Statistics - Harvard University
    • 1987: M.A. in Statistics - Harvard University
    • 1986: Diploma in Graduate Study of Mathematical Statistics - Research Institute of Mathematics, Fudan University, Shanghai, P.R. China
    • 1982: B.S. in Mathematics - Fudan University, Shanghai, P.R. China

    Host: Daniel J. Epstein Department of Industrial and Systems Engineering

    More Information: Seminar-Meng.doc

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

    Audiences: Everyone Is Invited

    Contact: Georgia Lum

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  • AME Department Seminar

    Thu, Dec 08, 2011 @ 11:00 AM - 12:00 PM

    Aerospace and Mechanical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Beverley J. McKeon , Professor of Aeronautics. Graduate Aerospace Laboratories. California Institute of Technology. Pasadena, CA.

    Talk Title: Deconstructing (and Reconstructing) Wall Turbulence

    Abstract: The literature contains several distinct approaches to understanding the flow physics underlying wall turbulence, including the characterization of velocity statistics and spectra, identification of dominant coherent structures and analysis of the amplification properties of the Navier-Stokes equations, to name a few. However the detailed connections between these views of the same fluid system have proved elusive. The critical layer framework for turbulent pipe flow proposed by McKeon & Sharma (J. Fluid Mech, 2010) provides a simple model by which to understand both qualitative and quantitative aspects of the structure of wall turbulence. This framework utilizes an input-output formulation of the Navier-Stokes equations to analyze the transfer function and identify the dominant forcing and response mode shapes at each combination of frequency, streamwise and spanwise wavenumbers relevant to experimental observations. In this talk I will describe and expand the framework, demonstrating that our model gives important predictive information about both the statistical and structural make-up of wall turbulence, and can be used to understand some simple experiments designed to manipulate the spectral distribution of turbulent energy. Implications for both the classical picture of wall turbulence and control of turbulent flows will be discussed.

    Biography: Beverley McKeon is a Professor of Aeronautics in the Graduate Aerospace Laboratories at Caltech (GALCIT). Her research interests include interdisciplinary approaches to manipulation of boundary layer flows using morphing surfaces and fundamental investigations of wall turbulence at high Reynolds number. She was the recipient of a Presidential Early Career award (PECASE) in 2009 and an NSF CAREER award in 2008. Prior to joining GALCIT, she was a Royal Society Dorothy Hodgkin Research Fellow and postdoc in the Department of Aeronautics at Imperial College London, after receiving a B.A. and M.Eng. from the University of Cambridge (1996) and Ph.D. in Mechanical and Aerospace Engineering from Princeton University (2003) under the guidance of Lex Smits.

    More Info: http://ae-www.usc.edu/seminars/index.shtml#upcoming

    Location: Ronald Tutor Hall of Engineering (RTH) - 526

    Audiences: Everyone Is Invited

    Contact: April Mundy

    Event Link: http://ae-www.usc.edu/seminars/index.shtml#upcoming

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  • Lyman L. Handy Colloquium Series

    Lyman L. Handy Colloquium Series

    Thu, Dec 08, 2011 @ 12:45 PM - 01:45 PM

    Mork Family Department of Chemical Engineering and Materials Science

    Conferences, Lectures, & Seminars


    Speaker: Paul Nealy, Chemical and Biological Engineering, University of Wisconsin - Madison

    Talk Title: Directed Assembly of Block Copolymers to Advance the Performance of Conventional Lithography

    Series: Lyman L. Handy Colloquium Series

    Abstract: Our research program aims to integrate self-assembling block copolymers into current manufacturing practice. The fundamental concepts of the approach are that 1) the most advanced production-oriented exposure tools (e.g. 193 nm, EUV, or electron beam lithography) and resist materials are used to create patterns of differing chemical functionality on the substrate, and 2) films of block copolymers can be directed to assemble in the presence of the chemical pattern into predictable and desirable morphologies, thereby augmenting and enhancing the lithographic process. In comparing the pattern in resist to the pattern of domains induced to assemble in the block copolymer film, directed assembly has been demonstrated to achieve high degrees of pattern perfection, placement of features at the precision of the lithographic tool used to make the chemical pattern, improved dimensional control of features, improved line edge and line width roughness, and resolution enhancement by factors of two to four. In addition, the approach has been demonstrated to robustly achieve non-regular device-oriented geometries used in the fabrication of integrated circuits also with resolution enhancement by multiplication of feature density by interpolation on low duty cycle chemical patterns. After describing current capabilities, remaining technological questions and pathways towards implementation in specific applications will be discussed.

    Host: Malancha Gupta

    Location: James H. Zumberge Hall Of Science (ZHS) - 159

    Audiences: Everyone Is Invited

    Contact: Petra Pearce

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  • USC Physical Sciences in Oncology Monthly Seminar Series

    USC Physical Sciences in Oncology Monthly Seminar Series

    Fri, Dec 16, 2011 @ 11:45 AM - 01:00 PM

    Alfred E. Mann Department of Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Owen McCarty, Ph.D., Associate Professor of Biomedical Engineering, Oregon Health & Science University

    Talk Title: The Physical Biology of Circulating Tumor Cells and Thrombosis

    Abstract: The vascular system represents an exquisite feat of bioengineering. Fluid (blood) flow and mass transfer are intimately integrated with and actively regulate vascular cell responses. We aim to characterize the molecular nature of cellular processes in the dynamic setting of the vasculature through the synthesis of engineering fundamentals with the tools of cell biology. Our research is focused on understanding the interplay between cell biology and fluid mechanics in the cardiovascular system. My research into the balance between hydrodynamic shear forces and chemical adhesive interactions has great relevance to the underlying processes of cancer metastasis, cardiovascular disease, and inflammation. As part of this seminar, I present some of our latest work on the development of a novel imaging technique to characterize the physical biology of peripheral blood cells, including circulating tumor cells. Moreover, I will present some research on the role that circulating tumor cells play in triggering the blood coagulation cascade.

    Biography: USC was selected to establish a $16 million cancer research center as part of a new strategy against the disease by the U.S. National Institutes of Health and its National Cancer Institute. The new center is one of 12 in the nation to receive the designation. During the five-year initiative, the Physical Sciences-Oncology Centers will take new, nontraditional approaches to cancer research by studying the physical laws and principles of cancer; evolution and the evolutionary theory of cancer; information coding, decoding, transfer and translation in cancer; and ways to de-convolute cancer’s complexity. As part of the outreach component of this grant, the Center for Applied Molecular Medicine is hosting a monthly seminar series.



    Host: Center for Applied Molecular Medicine

    Location: Clinical Science Center (CSC) - #250 Harkness Auditorium

    Audiences: Everyone Is Invited

    Contact: Kristina Gerber

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  • Ph.D. Defense

    Tue, Dec 20, 2011 @ 09:00 AM - 11:00 AM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Joshua Train, Computer Engineering

    Talk Title: Routing Fountains: Leveraging Broadcast Channels to Improve The Dissemination of Control Information For Large Inter-Domain Networks

    Abstract: The utility of a large inter-domain network depends on neighboring networks exchanging routing control information and using that information to compute next-hop forwarding decisions. While this approach of hop-by-hop information dissemination has proven very useful for the incremental expansion of the Internet, it is limited in providing the necessary performance to accommodate for future network growth, mobility, and security.

    To address these challenges, we present a novel architecture that leverages broadcast channels for disseminating routing information. The key components of our architecture are devices called `Routing Fountains’ that perform the task of collecting routing information from each of the participant networks and then simultaneously redistributing this information back to the greater set of networks through a wide area broadcast channel, like a satellite downlink. By complementing existing routing infrastructures with Routing Fountains, we augment the route distribution graph in a way that: 1.) Drastically reduces the number of transmissions needed to communicate routing updates, 2.) Provides synchronization to the route distribution process, and 3.) Facilitates the validation of routing data. Our architecture is designed to augment and therefore coexist with current routing infrastructures so that incremental performance gains can be achieved without disruption to existing infrastructures.

    Utilizing a broadcast based architecture provides compelling opportunities to improve the performance of today’s inter-domain routing architectures. To demonstrate the utility of this approach we have applied it to the following three inter-domain routing tasks: 1.) Distributing routing updates across the entire Internet topology, 2.) Facilitating minimal loss network transitions for mobile networks while maintaining shortest path connectivity, and 3.) Protecting against the distribution of fictitious routing information. The results from our Internet graph and routing traffic analysis, simulations, and testbed prototypes demonstrate that utilizing broadcast channels has remarkable value in improving the performance and robustness of existing route distribution infrastructures, even when only a subset of the larger network is actively receiving the broadcasted information.


    Biography: Josh Train received a M.S. (2002) in Electrical Engineering from the University of Southern California, and a B.S. in Computer Science from Biola University in 2001. He is currently employed by The Aerospace Corporation and leads a team of researchers investigating topics including network modeling, satellite networking, networking security, and high speed data processing.



    Host: Prof Raghu Raghavendra (Chair)

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

    Audiences: Everyone Is Invited

    Contact: Janice Thompson

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  • Oral Dissertation Defense

    Wed, Dec 21, 2011 @ 10:00 AM - 12:00 PM

    Sonny Astani Department of Civil and Environmental Engineering

    Conferences, Lectures, & Seminars


    Speaker: Sara Abedi, CEE Ph.D, Candidate

    Talk Title: Meso- Scale Kinemetics in Shear Bands and Impact of Material Heterogeneity on Shear Band Development in Sand

    Abstract:
    This study aims to improve our understanding of strain localization in sands from the meso-scale perspective. First, this research contributes to characterizing and quantifying experimentally the micro- and meso-scale kinematic mechanisms associated with force chains and vortex structures in shear bands in real granular materials. The Digital Image Correlation (DIC) technique is used to obtain the two-dimensional, incremental surface displacements from digital images of deforming plane strain sand specimens. The aim herein is to use DIC results as a means to 1) evaluate meso-scale kinematic behavior inside shear bands through the course of large deformation, 2) infer the kinematic manifestation of force chains and vortex-structures and study their evolution and dissolution in sheared sands, and 3) conduct a preliminary investigation of length scales in granular shear. Second, we studied the physical mechanism underlying shear band formation in a supposedly uniform soil specimen, apart from the boundary influences or loading non-uniformities. The technique of X-Ray Compute Tomography (CT) is used to capture meso-scale density variations in plane strain specimens of sand. Digital image processing techniques are then used to transfer the CT results as input to the three-dimensional FE models. Finally, Digital Image Correlation (DIC) enables tracking of the in plane displacement of the sand specimen throughout plane strain compression tests performed on the CT specimens. The laboratory results are then compared with numerical predictions. This direct comparison should enable refinement in numerical models to achieve better predictability.

    Adviser: Dr. Amy Rechenmacher


    Location: Kaprielian Hall (KAP) - 209 Conference Room

    Audiences: Everyone Is Invited

    Contact: Evangeline Reyes

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