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Events for the 1st week of March

  • CS Colloquium: Ellie Pavlick (University of Pennsylvania) - Natural Language Understanding with Paraphrases and Composition

    Mon, Feb 27, 2017 @ 11:00 AM - 12:20 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Ellie Pavlick, University of Pennsylvania

    Talk Title: Natural Language Understanding with Paraphrases and Composition

    Series: CS Colloquium

    Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.

    Natural language processing (NLP) aims to teach computers to understand human language. NLP has enabled some of the most visible applications of artificial intelligence, including Google search, IBM Watson, and Apple's Siri. As AI is applied to increasingly complex domains such as health care, education, and government, NLP will play a crucial role in allowing computational systems to access the vast amount of human knowledge documented in the form of unstructured speech and text.

    In this talk, I will discuss my work on training computers to make inferences about what is true or false based on information expressed in natural language. My approach combines machine learning with insights from formal linguistics in order to build data-driven models of semantics which are more precise and interpretable than would be possible using linguistically naive approaches. I will begin with my work on automatically adding semantic annotations to the 100 million phrase pairs in the Paraphrase Database (PPDB). These annotations provide the type of information necessary for carrying out precise inferences in natural language, transforming the database into a largest available lexical semantics resource for natural language processing. I will then turn to the problem of compositional entailment, and present an algorithm for performing inferences about long phrases which are unlikely to have been observed in data. Finally, I will discuss my current work on pragmatic reasoning: when and how humans derive meaning from a sentence beyond what is literally contained in the words. I will describe the difficulties that such "common-sense" inference poses for automatic language understanding, and present my on-going work on models for overcoming these challenges.

    Biography: Ellie Pavlick is a PhD student at the University of Pennsylvania, advised by Dr. Chris Callison-Burch. Her dissertation focuses on natural language inference and entailment. Outside of her dissertation research, Ellie has published work on stylistic variation in paraphrase--e.g. how paraphrases can effect the formality or the complexity of language--and on applications of crowdsourcing to natural language processing and social science problems. She has been involved in the design and instruction of Penn's first undergraduate course on Crowdsourcing and Human Computation (NETS 213). Ellie is a 2016 Facebook PhD Fellow, and has interned at Google Research, Yahoo Labs, and the Allen Institute for Artificial Intelligence.

    Host: CS Department

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

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair

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  • Navigating the the U.S. Recruitment Process -VIRTUAL WORKSHOP

    Mon, Feb 27, 2017 @ 12:00 PM - 01:00 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    This workshop will provide students tips on how to navigate the process of U.S. corporate recruiting and will touch on American culture norms.

    To join the workshop, go to https://bluejeans.com/746143734 at the workshop start time and login with your USC netID and password.

    Location: VIRTUAL WORKSHOP

    Audiences: All Viterbi Students

    Contact: RTH 218 Viterbi Career Connections

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  • Seminars in Biomedical Engineering

    Mon, Feb 27, 2017 @ 12:30 PM - 01:50 PM

    Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Mahnaz Shahidi, PhD, Professor of Ophthalmology and Biomedical Engineering Riffenburgh Professor in Glaucoma Vice Chair for Translational Research Department of Ophthalmology University of Southern California

    Talk Title: Multimodal Imaging of Retinal Oxygen Delivery and Metabolism

    Abstract: Retinal tissue function can be adversely affected by inadequate delivery and/or consumption of oxygen. In fact, derangements in retinal oxygenation are thought to contribute significantly to the development of common vision threatening retinal diseases. However, mechanisms that implicate oxygen in the development of retinal pathologies and impairment of retinal function are not completely understood. Therefore, technologies that allow assessment of oxygen tension in the retinal vasculature and tissue are needed to broaden knowledge of disease pathophysiology, and thereby advance diagnostic and therapeutic procedures. We have developed an optical section phosphorescence lifetime imaging technique that allows depth-resolved mapping of retinal vascular oxygen tension and measurement of inner retinal oxygen extraction fraction. Combined with fluorescent microsphere imaging for measurement of retinal blood flow, oxygen delivery by the retinal circulation and global inner retinal oxygen metabolism are derived. These technologies have been applied for assessment of retinal oxygen delivery and metabolism in experimental animal models of retinal ischemia.



    Host: Qifa Zhou

    Location: Olin Hall of Engineering (OHE) - 122

    Audiences: Everyone Is Invited

    Contact: Mischalgrace Diasanta

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  • Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute for Electrical Engineering Joint Seminar Series on Cyber-Physical Systems

    Mon, Feb 27, 2017 @ 02:00 PM - 03:30 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Geir E. Dullerud, Professor, University of Illinois at Urbana-Champaign

    Talk Title: Statistical Validation and Principle-Based Simulation of Complex Cyber-Controlled Systems

    Abstract: The talk will focus on simulation and a computational approach to verification of the hybrid mathematical models that are formed when combining physics-based models with discrete-transition models, such as those which model software algorithms. Namely, the mathematical models that arise when for instance considering Cyberphysical Systems, or the Internet of Things.

    In many game theory and filtering problems it is not possible to analytically obtain solutions for statistical properties of systems under study, and in the first part of the talk we will describe our recent work on numerical approaches to obtaining estimates of these properties, and the application of the techniques developed to particle filtering. Monte Carlo simulation of Markov processes allows the numerical estimation of their statistical properties from an ensemble of sample system paths. We present methods for generating reduced-variance path ensembles for the tau-leaping discrete-time simulation algorithm, which allows mean stochastic process dynamics to be estimated with substantially smaller ensemble sizes. Our methods are based on antithetic and stratified sampling of Poisson random variates, and we provide a combination of analytical proofs and numerical evidence for their performance, which can frequently be a 2-3 orders of magnitude improvement over standard Monte Carlo. Application examples will be discussed.

    The second part of the talk will concentrate on system verification, and will present a new verification algorithm for continuous-time stochastic hybrid systems, whose specifications are expressed in metric interval temporal logic (MITL), by deploying a novel model reduction method. By partitioning the state space of the hybrid system and computing the optimal transition rates between partitions, we provide a procedure to both reduce the system to a continuous-time Markov chain, and the associated specification formulas. We prove that the unreduced formulas hold (or do not) if the corresponding reduced formula on the Markov chain is robustly true (or false) under certain perturbations. In addition, a stochastic algorithm to complete the verification has been developed. We have extended the approach of this algorithm, and have developed a direct stochastic algorithm for probabilistically verifying a certain hybrid system class, and applied this technique to an extensive benchmark problem with realistic dynamics.


    Biography: Geir E. Dullerud is the W. Grafton and Lillian B. Wilkins Professor in Mechanical Engineering at the University of Illinois at Urbana-Champaign. There he is also a member of the Coordinated Science Laboratory, where he is Director of the Decision and Control Laboratory (21 faculty); he is an Affiliate Professor of both Computer Science, and Electrical and Computer Engineering. He has held visiting positions in Electrical Engineering KTH, Stockholm (2013), and Aeronautics and Astronautics, Stanford University (2005-2006). Earlier he was on faculty in Applied Mathematics at the University of Waterloo (1996-1998), after being a Research Fellow at the California Institute of Technology (1994-1995), in the Control and Dynamical Systems Department. He has published two books: "A Course in Robust Control Theory", Texts in Applied Mathematics, Springer, 2000, and "Control of Uncertain Sampled-data Systems", Birkhauser 1996. His areas of current research interest include convex optimization in control, cyber-physical system security, cooperative robotics, stochastic simulation, and hybrid dynamical systems. In 1999 he received the CAREER Award from the National Science Foundation, and in 2005 the Xerox Faculty Research Award at UIUC. He is a Fellow of both IEEE (2008) and ASME (2011).

    Host: Paul Bogdan

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

    Audiences: Everyone Is Invited

    Contact: Estela Lopez

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  • CAIS Seminar Series: Dr. Pascal Van Hentenryck (University of Michigan) - The Case of Infrastructure Optimization

    Mon, Feb 27, 2017 @ 04:00 PM - 04:50 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Dr. Pascal Van Hentenryck, University of Michigan

    Talk Title: The Case of Infrastructure Optimization

    Series: Center for AI in Society (CAIS) Seminar Series

    Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.

    In the last decade, massive amount of information has been collected about critical infrastructures, including the transportation network and the electrical power system. These data sets, together with progress in Artificial Intelligence and Operations Research, make it possible to analyze, predict, and optimize these infrastructures with unprecedented fidelity. This talk demonstrates the societal benefits of this transformation on a number of case studies in evacuation planning, public transportation, and power restoration.

    Biography: Dr. Pascal Van Hentenryck is the Seth Bonder Collegiate Professor of Engineering at the University of Michigan. He is Professor of Industrial and Operations Engineering, Professor of Electrical Engineering and Computer Science, and core faculty in the Michigan Institute of Data Science. He is the author of the pioneering CHIP and OPL optimization systems, which have been widely used in academia and industry. Dr. Van Hentenryck is the author of five MIT Press books and is a fellow of AAAI and INFORMS.

    Host: Milind Tambe

    Location: John Stauffer Science Lecture Hall (SLH) - 100

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair

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  • NAVAIR Information Session

    Mon, Feb 27, 2017 @ 05:30 PM - 06:30 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    NAVAIR Overview - Overview of NAVAIR and discussion of employment opportunities as a civilian employee of the Department of the Navy

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

    Audiences: All Viterbi Students

    Contact: RTH 218 Viterbi Career Connections

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  • USC Stem Cell Seminar: Michael Rudnicki, Ottawa Hospital Research Institute

    Tue, Feb 28, 2017 @ 11:00 AM - 12:00 PM

    Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Michael Rudnicki, Ottawa Hospital Research Institute

    Talk Title: TBD

    Series: Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research at USC Distinguished Speakers Series

    Host: USC Stem Cell

    More Info: http://stemcell.usc.edu/events

    Webcast: http://keckmedia.usc.edu/stem-cell-seminar

    Location: Eli & Edythe Broad CIRM Center for Regenerative Medicine & Stem Cell Resch. (BCC) - First Floor Conference Room

    WebCast Link: http://keckmedia.usc.edu/stem-cell-seminar

    Audiences: Everyone Is Invited

    Contact: Cristy Lytal/USC Stem Cell

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  • CS Colloquium: Vinodkumar Prabhakaran (Stanford University) - NLP for Social Good: Inferring Social Context from Language

    Tue, Feb 28, 2017 @ 11:00 AM - 12:20 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Vinodkumar Prabhakaran, Stanford University

    Talk Title: NLP for Social Good: Inferring Social Context from Language

    Series: CS Colloquium

    Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.

    The vast quantities of language data online and offline offer tremendous opportunities to study society through language. In this talk, I show how natural language processing techniques can be expanded from understanding the meanings of words and sentences, to inferring the underlying social structures and processes they reflect and identifying crucial shortcomings in them. I apply these techniques to computationally detect two ways in which the social context affects the use of language: social relations affecting how people interact with one another, and social constructs shaping how institutions interact with communities. In the first part, I show how to computationally detect manifestations of social power in workplace interactions between individuals -” providing means for organizations to detect incivility at workplace. In the second part, I show how to computationally investigate the ways race shapes the interactions between the police and the communities they serve -” providing means for departments to address and monitor racial disparities in policing. My research looks beyond words and phrases, and introduce ways to infer richer rhetorical and dialog information like conversational structure and respect that reflect the social context, demonstrating the importance of deeper language processing for the computational social sciences.

    Biography: Vinodkumar Prabhakaran is a postdoctoral fellow in the computer science department at Stanford University. His research falls in the inter-disciplinary field of computational sociolinguistics, in which he builds and uses computational tools to analyze linguistic patterns that reveal the underlying social contexts in which language is used. He received his PhD in Computer Science from Columbia University in 2015. In his doctoral thesis, he studied how machine learning and natural language processing techniques can help detect the underlying social power structures that guide social interactions. As part of his research, he has also made significant contributions to core NLP problems such as extracting information from text, as well as modeling structures of dialog and discourse.

    Host: CS Department

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

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair

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  • Epstein Institute Seminar, ISE 651

    Tue, Feb 28, 2017 @ 03:30 PM - 04:50 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Mariel Lavieri , Associate Professor, University of Michigan

    Talk Title: Personalizing Management of Glaucoma Patients

    Host: Dr. Sze-chuan Suen

    More Information: February 28, 2017_Lavieri.pdf

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

    Audiences: Everyone Is Invited

    Contact: Grace Owh

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  • CS Colloquium: Fan Long (MIT CSAIL) - Learning How to Patch Software Errors Automatically

    Tue, Feb 28, 2017 @ 04:00 PM - 05:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Fan Long, MIT CSAIL

    Talk Title: Learning How to Patch Software Errors Automatically

    Series: CS Colloquium

    Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.

    Software systems are increasingly integrated into every part of our society. As the number of systems and our dependence on these systems continue to grow, making these systems reliable and secure becomes an increasingly important challenge for our society and a daunting task for software developers.

    Automatic patch generation holds out the promise of automatically correcting software defects without the need for developers to manually diagnose, understand, and correct these defects. In this talk, I will present two novel automatic patch generation systems, Prophet and Genesis, both of which learn from past successful human patches to automatically fix defects. By collectively leveraging development efforts worldwide, Prophet and Genesis automatically generate correct patches for real-world defects in large open-source C and Java applications with up to millions lines of code. This research also demonstrates that the growing volume of software programs is not just a challenge but also a great opportunity. Exploiting this opportunity can enable revolutionary new automated techniques that enhance software reliability and security.

    Biography: Fan Long is a PhD candidate in Computer Science at Massachusetts Institute of Technology (MIT). His research to date has focused on developing automated programming systems to improve software reliability and security. He has developed systems that automatically identify and eliminate errors in large software programs and systems that enable software programs to operate successfully in spite of the presence of errors. He holds a BE from Tsinghua University and a MS from MIT.


    Host: CS Department

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

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair

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  • Detecting paralinguistic information from speech and language for clinical applications: Algorithms and information limits

    Wed, Mar 01, 2017 @ 10:00 AM - 12:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Visar Berisha, Arizona State University

    Talk Title: Detecting paralinguistic information from speech and language for clinical applications: Algorithms and information limits

    Abstract: The ability to share our thoughts and ideas through spoken
    communication is fragile. Even the simplest verbal response requires a
    complex sequence of events. It requires thinking of the words that best
    convey your message; sequencing these words appropriately; and then
    sending signals to the muscles required to produce speech. The slightest
    damage to the brain areas that orchestrate these events can manifest in
    speech and language problems. These disturbances offer a window into
    brain functioning. In the first part of this presentation, I will
    present an overview of a number of projects where we use interpretable
    measures of speech and language production as proxies for cognitive and
    motor health. The algorithms behind this work have practical utility in
    clinical applications and can help answer basic research questions
    related to dysarthric speech production.

    In the second part of the talk, I will discuss new results from
    non-parametric statistical signal processing that allow us to
    characterize the information limits in speech. In contrast to existing
    methods based on machine learning, this work provides a framework to
    answer fundamental questions such as 'What are the bounds on how well I
    can recover a parameter of interest from speech?' or 'How well should an
    optimally trained classifier work for a particular application?'

    Biography: Visar Berisha is an Assistant Professor at Arizona State
    University with a joint appointment in the School of Electrical Computer
    and Energy Engineering and the Department of Speech and Hearing Science.
    Prior to joining ASU, Berisha was a research scientist at MIT Lincoln
    Laboratory and then Principal Research Engineer for a Fortune 500
    company. His research interests include speech analytics, statistical
    signal processing, and information theory. Much of his recent work spans
    all three of these fields to answer basic questions related to the
    limits of information in speech. His research has led to many academic
    publications, several licensed patents, and a revenue-positive startup
    company. Berisha's work has been featured in the Science section of the
    New York Times, on National Public Radio, and a number of other national
    media outlets.

    Host: Shrikanth Narayanan

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

    Audiences: Everyone Is Invited

    Contact: Tanya Acevedo-Lam/EE-Systems

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  • CS Colloquium: Bistra Dilkina (Georgia Tech) -Challenges in Computational Sustainability

    Wed, Mar 01, 2017 @ 11:00 AM - 12:20 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Bistra Dilkina, Georgia Tech

    Talk Title: Challenges in Computational Sustainability

    Series: CS Colloquium

    Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.

    Computational sustainability is a new interdisciplinary research focused on computational problems that arise in the quest for sustainable development. The goal of sustainable development is to balance environmental, economic, and societal factors to "meet the needs of the present without compromising the ability of future generations to meet their own needs." In this talk, I will provide a sample of computational sustainability problems, from the areas of biodiversity conservation, energy, climate and environment monitoring. I will describe, for example, network design problems motivated by challenging planning problems in wildlife conservation. In this context, I will present a network design optimization framework for stochastic diffusion processes, such as species dispersal, fire spread, information propagation, and disease outbreak. I will also emphasize the unique opportunities for scalable constraint reasoning and optimization techniques to contribute to the new research
    area of computational sustainability and describe our recent advances in improving the state-of-the-art in large-scale optimization by leveraging machine learning techniques to inform the design of combinatorial search algorithms.

    Biography: Bistra Dilkina is an assistant professor in the College of Computing at the Georgia Institute of Technology and a Fellow at the Brook Byers Institute for Sustainable Systems. She received her PhD from Cornell University in 2012, and was a Post-Doctoral associate at the Institute for Computational Sustainability until 2013. Her research focuses on advancing the state of the art in combinatorial optimization techniques for solving real-world large-scale problems, particularly ones that arise in sustainability areas such as biodiversity conservation planning and urban planning. Her work spans discrete optimization, network design, stochastic optimization, and machine learning. She is also the co-director of the Data Science for Social Good (DSSG) Atlanta summer program, which partners student teams with government and nonprofit organizations to help solve some of their most difficult problems using analytics, modeling, prediction and visualization. Bistra has (co-)authored over 30 publications, and has won several awards, including Best Student Paper runner up at KDD 2016, Best Paper of the INFORMS ENRE Section, Lockheed Inspirational Young Faculty Award, Raytheon Faculty Fellowship, and Georgia Power Professor of Excellence Award.

    Host: CS Department

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

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair

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  • MHI CommNetS Seminar

    Wed, Mar 01, 2017 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Arpan Chattopadhyay, USC

    Talk Title: Sequential decision algorithms for as-you-go deployment of wireless relay network along a line

    Series: CommNetS

    Abstract: We are motivated by the need, in some applications, for impromptu or as-you-go deployment of wireless sensor networks. A person walks along a line, starting from a sink node (e.g., a base-station), and proceeds towards a source node (e.g., a sensor) which is at an a priori unknown location. At equally spaced locations, he makes link quality measurements to the previous relay, and deploys relays at some of these locations, with the aim to connect the source to the sink by a multihop wireless path. In this paper, we consider two approaches for impromptu deployment: (i) the deployment agent can only move forward (which we call a pure as-you-go approach), and (ii) the deployment agent can make measurements over several consecutive steps before selecting a placement location among them (the explore-forward approach). We consider a very light traffic regime, and formulate the problem as a Markov decision process, where the trade-off is among the power used by the nodes, the outage probabilities in the links, and the number of relays placed per unit distance. We obtain the structures of the optimal policies for the pure as-you-go approach as well as for the explore-forward approach. We also consider natural heuristic algorithms, for comparison. Numerical examples show that the explore-forward approach significantly outperforms the pure as- you-go approach in terms of network cost. Next, we propose learning algorithms for the explore-forward approach and the pure as-you-go approach, based on single and two timescale Stochastic Approximation, which asymptotically converge to the set of optimal policies, without using any knowledge of the radio propagation model. We demonstrate numerically that the learning algorithms can converge (as deployment progresses) to the set of optimal policies reasonably fast and, hence, can be practical model-free algorithms for deployment over large regions. Finally, we demonstrate the end-to-end traffic carrying capability of such networks via field deployment.

    Biography: Arpan Chattopadhyay obtained his B.E. in Electronics and Telecommunication Engineering from Jadavpur University, Kolkata, India in the year 2008, and M.E. and Ph.D in Telecommunication Engineering from Indian Institute of Science, Bangalore in the year 2010 and 2015, respectively. Then he worked as a postdoc in the group DYOGENE of INRIA/ENS Paris. He joined EE department, USC as a postdoc from November 2016. His host is Prof. Urbashi Mitra. His research interests include optimization, learning and control of wireless networks and cyber-physical systems.

    Host: Prof. Ashutosh Nayyar

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

    Audiences: Everyone Is Invited

    Contact: Annie Yu

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  • Introduction to Viterbi Gateway Workshop

    Wed, Mar 01, 2017 @ 04:30 PM - 05:30 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    Come to this presentation to learn how to navigate the Viterbi Career Gateway,a powerful job & internship search tool available ONLY to Viterbi students.

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

    Audiences: All Viterbi

    Contact: RTH 218 Viterbi Career Connections

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  • Interview Strategies and Technique- VIRTUAL WORKSHOP

    Thu, Mar 02, 2017 @ 04:00 AM - 05:00 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    Discover tips on how to prepare for both technical and behavioral interviews, as well as the proper steps for follow-up!

    To join the workshop, go to https://bluejeans.com/826731286 at the workshop start time and login with your USC netID and password.

    WebCast Link: https://bluejeans.com/309510374

    Audiences: Everyone Is Invited

    Contact: RTH 218 Viterbi Career Connections

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  • Astani Civil and Environmental Engineering Seminar

    Thu, Mar 02, 2017 @ 03:00 PM - 04:00 PM

    Sonny Astani Department of Civil and Environmental Engineering

    Conferences, Lectures, & Seminars


    Speaker: Prof. Tzahi Cath, Colorado School of Mines

    Talk Title: Challenges of Water Treatment on Watershed Behavior: Insights Gained Using Geophysical Methods

    Abstract: TBA

    Host: Dr. Amy Childress

    Location: TBA

    Audiences: Everyone Is Invited

    Contact: Evangeline Reyes

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  • Big Data, Streaming Graphs, and the Need for Innovations in Architecture

    Fri, Mar 03, 2017 @ 10:30 AM - 11:30 AM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Peter Kogge, University of Notre Dame

    Talk Title: Big Data, Streaming Graphs, and the Need for Innovations in Architecture

    Abstract: This talk will start with some insights gleaned from looking at real-world big data problems and how they are affected by architecture. The Emu migrating thread architecture is then introduced and compared. A general template for integrated big graph batch and streaming analytic processing is developed, and key graph operations, especially streaming, listed. A discussion follows on how the Emu architecture meshes well with such a dual-mode computing template, with some specific emphasis on machine learning functions.


    Biography: Peter M. Kogge received his Ph.D. in EE from Stanford in 1973. From 1968 until 1994 he was with IBM's Federal Systems Division, and was appointed an IBM Fellow in 1993. In August, 1994 he joined the University of Notre Dame as first holder of the endowed McCourtney Chair in Computer Science and Engineering. He has served as both Department Chair and Associate Dean for Research, College of Engineering. He is an IEEE Fellow, a Distinguished Visiting Scientist at JPL, and a founder and Chief Scientist of Emu Solutions, Inc. His research interests are in massively parallel computing paradigms, processing in memory, and the relationship between massive non-numeric applications, emerging technology, and computer architectures.

    He holds over 40 patents and is author of two books, including the first text on pipelining. His Ph.D. thesis led to the Kogge-Stone adder used in many microprocessors. Other projects included EXECUBE - the world's first multi-core processor and first processor on a DRAM chip, the IBM 3838 Array processor which was for a time the fastest floating point machine marketed by IBM, and the IOP - the world's second multi-threaded parallel processor which flew on every Space Shuttle. In 2008, he led DARPA's Exascale technology study group, which resulted in a widely referenced report on technologies and architectures for exascale computing, and has had key roles on many other HPC programs. His startup, Emu Solutions, has demonstrated the first scalable system that utilizes mobile threads to attack large-scale big data and big graph problems.

    Dr. Kogge has received the Daniel Slotnick best paper award (1994), the IEEE Seymour Cray award for high performance computer engineering (2012), the IEEE Charles Babbage award for contributions to the evolution of massively parallel processing architectures (2014), the IEEE Computer Pioneer award (2015), and the Gauss best paper award for high performance computers (2015).

    Host: Viktor Prasanna, EEB 200, prasanna@usc.edu

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

    Audiences: Everyone Is Invited

    Contact: Gerrielyn Ramos

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  • Big Data, Streaming Graphs, and the Need for Innovations in Architecture

    Fri, Mar 03, 2017 @ 10:30 AM - 11:30 AM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Peter Kogge, University of Notre Dame

    Talk Title: Big Data, Streaming Graphs, and the Need for Innovations in Architecture

    Abstract: This talk will start with some insights gleaned from looking at real-world big data problems and how they are affected by architecture. The Emu migrating thread architecture is then introduced and compared. A general template for integrated big graph batch and streaming analytic processing is developed, and key graph operations, especially streaming, listed. A discussion follows on how the Emu architecture meshes well with such a dual-mode computing template, with some specific emphasis on machine learning functions.

    Biography: x

    Host: Viktor Prasanna, EEB 200, prasanna@usc.edu

    Location: 248

    Audiences: Everyone Is Invited

    Contact: Gerrielyn Ramos

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  • W.V.T. Rusch Engineering Honors Program Colloquium

    Fri, Mar 03, 2017 @ 01:00 PM - 01:50 PM

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

    University Calendar


    Join us for a presentation by Prof. Paul Rothemund, Dept. of Bioengineering at California Institute of Technology, titled "DNA Origami: Folded DNA as a Building Material for Molecular Devices."

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

    Audiences: Everyone Is Invited

    Contact: Ramon Borunda/Academic Services

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  • Ming Hsieh Institute Seminar Series on Integrated Systems

    Fri, Mar 03, 2017 @ 02:30 PM - 04:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Scott Powell, VP Engineering at Jariet Technologies

    Talk Title: CMOS Digital Microwave

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

    More Information: MHI Seminar Series IS - Scott Powell.pdf

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

    Audiences: Everyone Is Invited

    Contact: Jenny Lin

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