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Events for May

  • Seminars in Biomedical Engineering

    Mon, May 01, 2017 @ 12:30 PM - 01:50 PM

    Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Joe Zhong, USC

    Talk Title: Microfluidics for Cancer

    Host: Qifa Zhou

    Location: Olin Hall of Engineering (OHE) - 122

    Audiences: Everyone Is Invited

    Posted By: 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, May 01, 2017 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Xiaoqing Jin , Senior Engineer, Toyota Motors North America R&D

    Talk Title: Logic Driven Data Science

    Abstract: Data science together with machine learning is prevalent in almost every sector of industry. Many popular techniques, such as deep learning with artificial neural networks, have shown their capabilities in achieving incredible performance and accuracy in helping make Cyber Physical Systems (CPS) smarter. However, data scientists or engineers usually find it challenging to interpret the artifacts learned using such procedures. Also, due to the proliferation of sensors, control engineers have to combat the data deluge problem. They need to process, analyze, and identify structure or logical relations from intractably large amounts of time series data within limited amount of time. Typical machine learning techniques rely on similarity measures defined on complex feature spaces of signals and may overlook the embedded logical structure. In this talk, we explore data analysis from the logical perspective and introduce supervised and unsupervised learning procedures that utilize Parametric Signal Temporal Logic (PSTL) templates to discover temporal and spatial relations in signal space. The resulting methods not only perform data analysis but also generate formal artifacts to give engineers abstract understanding of the results. We will demonstrate our techniques in many domains, such as automotive testing, medical devices, and online education systems.

    Biography: Xiaoqing Jin is a Senior Engineer at Toyota Motors North America R&D. She received her Ph.D. from the University of California at Riverside on topics including symbolic model checking, stochastic model checking, and formal verification and validation for hybrid systems. She began her career in doing advanced research at Toyota where she was responsible for researching and developing techniques and tools to help design and analysis of industrial cyber-physical systems, such as control systems for internal combustion engine vehicles and fuel cell electric vehicles. Her research interests are in the broad area of hybrid systems, temporal logics, machine learning, data analysis, control theory, dynamical systems, and automotive control systems.

    Host: Paul Bogdan

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

    Audiences: Everyone Is Invited

    Posted By: Estela Lopez

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  • First Mini-Workshop on Cyber-Physical Security and Privacy

    Tue, May 02, 2017 @ 09:00 AM - 12:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Workshops & Infosessions


    First Mini-Workshop on Cyber-Physical Security and Privacy
    USC Viterbi Center of Cyber-Physical Systems and the Internet of Things (CCI)
    Tuesday, May 2, 2017, 9am - 12pm, EEB 132

    Welcome to a mini-workshop consisting of exciting research talks by the following set of Viterbi faculty and researchers working on Cyber-Physical Security and Privacy from many perspectives, including cryptography, algorithms and protocols, data management, systems engineering, and CPS design.

    * Cliff Neuman, Director, Center for Computer Systems Security, USC/ISI
    * Alefiya Hussain, Computer Scientist, USC/ISI
    * Muhammad Naveed, Assistant Professor, Computer Science
    * Aleksandra Korolova, Assistant Professor, Computer Science
    * Shahram Ghandeharizadeh, Professor, Computer Science
    * Neno Medvidovic, Professor, Computer Science
    * Neil Siegel, Professor, Industrial Systems Engineering
    * Pierluigi Nuzzo, Assistant Professor, Electrical Engineering

    It is a great opportunity to hear from a stellar collection of our own
    faculty about their research in this area of growing importance.

    Don't miss it!

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

    Audiences: Everyone Is Invited

    Posted By: Brienne Moore

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  • USC Stem Cell Seminar: Ashley Seifert, University of Kentucky

    Tue, May 02, 2017 @ 11:00 AM - 12:00 PM

    Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Ashley Seifert, University of Kentucky

    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

    Posted By: Cristy Lytal/USC Stem Cell

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  • Using Theory to Reveal Function in Large Brain Circuits

    Wed, May 03, 2017 @ 10:00 AM - 12:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Friedrich Sommer, UC Berkeley

    Talk Title: Using Theory to Reveal Function in Large Brain Circuits

    Abstract: Current technology provides a virtual deluge of information about brain structure and physiology. Our laboratory focuses on developing new theoretical frameworks and analytical methods that take advantage of this accelerated rate of data influx to address central problems in neuroscience. I will discuss three different projects.
    High-density multi-electrode recordings monitor the spike trains of individual neurons with unparalleled temporal accuracy and also provide spatially distributed information about local field potentials (LFPs), slow signals generated by groups of neurons. In hippocampus, the relative timing between the spikes of a certain class of neurons (place cells) and a 10 Hz signal present in the LFP (the theta wave) carries information about the animal's position in the environment. Using data obtained in the Buzsaki laboratory, we developed a novel approach to decode the animal's position precisely from the LFP alone. Further, we were able to extract LFP place components, like place cells, neatly tile the spatial environment. The LFP is far simpler to record than spike trains, and is feasible to obtain from human patients. Thus, our results can be leveraged to build robust brain computer interfaces.
    Integration of information across regions and modalities is a fundamental working principle of the brain. We developed a novel method to estimate integrated information. The method can be applied to recordings with large numbers (thousands) of channels. We recently provided the first estimate of integrated information in a whole animal, the behaving nematode (C-elegans). Further, we found that the mesoscopic mouse connectome integrates significantly more information than other network architectures, suggesting that integrated information is a plausible force for driving evolution.
    Theoretical principles, such as Hebbian plasticity, error-based, and reward-based learning give insight into how the brain form sensory codes, object categories, and develop strategies to obtain rewards. However, we lack principles to understand how the brain guides the body to explore the environment efficiently such that it is possible to form models of the world from small numbers of observations. We proposed a novel principle that selects actions leading to the sensory observations that best improve the current model of the environment. This principle can be cast in a formal framework based on defining the information gain of the model. The resulting algorithm generates models of novel environments with greater speed than previously achieved. On one hand, the new principle generates testable predictions about how brains control action/perception loops, on the other it has technical applications in robotics and artificial intelligence.

    Biography: Friedrich T. Sommer holds a Ph.D. in Physics from the University of Dusseldorf and a habilitation in Computer Science from the University of Ulm. After completing postocdoctoral work at MIT and the University of Tuebingen, he joined the department of Computer Science at the University of Ulm in 1998 as an Assistant Professor. He became a Principal Investigator at the Redwood Neuroscience Institute in Menlo Park in 2003 before joining the University of California, Berkeley in 2005, where he is an Adjunct Professor at the Redwood Center for Theoretical Neuroscience and the Helen Wills Neuroscience Institute.

    Host: Shrikanth Narayanan & Richard Leady

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

    Audiences: Everyone Is Invited

    Posted By: Tanya Acevedo-Lam/EE-Systems

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  • Speech Technology Research and Applications at LPTV

    Wed, May 03, 2017 @ 02:00 PM - 04:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Nestor Becerra Yoma, Universidad de Chile in Santiago

    Talk Title: Speech Technology Research and Applications at LPTV

    Abstract: In this talk I will describe the research I have carried out in the Speech Processing and Transmission Laboratory (LPTV, Laboratorio de Procesamiento y Transmisión de Voz) in the last 17 years. LPTV is located at Universidad de Chile and was founded by me in 2000. I will discuss the seminar work on uncertainty and how the first results were achieved. As far as we know, those are the first uncertainty modelling in HMM. I will talk about our experience with speech technology for telephone applications and second language learning. Some relevant papers on stochastic Weighted Viterbi, multi-classifier fusion, CAPT and VoIP will be discussed. I will describe our state-of-the-art robotic platform that we have implemented to pursue our research on voice-based human-robot interaction. In this context, the locally normalized features will be presented to address the time varying channel problem. I will show demos and discuss ideas on voice-based HRI. Finally, I will summarize our results on multidisciplinary research on signal processing.

    Biography: Néstor Becerra Yoma received the PhD degree from University of Edinburgh, UK, and the M.Sc. and B.Sc. degrees from UNICAMP (Campinas State University), Sao Paulo, Brazil, all of them in Electrical Engineering, in 1998, 1993 and 1986, respectively. From 2000, he has been a Professor at the Department of Electrical Engineering, Universidad de Chile, in Santiago, where he is currently lecturing on telecommunications and speech processing. In 2011 he was promoted to the Full Professor position. From 2016 to 2017 he was a visiting professor at CMU, USA. At Universidad de Chile he started the Speech Processing and Transmission Laboratory to carry out research on speech technology applications on human-robot interaction, language learning, Internet and telephone line. His research interest also includes multidisciplinary research on signal processing in fields such as astronomy, mining and volcanology. He is the author of about 40 journal articles, 40 conference papers and three patents. Professor Becerra Yoma was an associate editor of the IEEE Transactions on Speech and Audio Processing from for four years.

    Host: Shrikanth Narayanan

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

    Audiences: Everyone Is Invited

    Posted By: Tanya Acevedo-Lam/EE-Systems

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  • Speech Technology Research and Applications at LPTV

    Wed, May 03, 2017 @ 02:00 PM - 04:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Nestor Becerra Yoma, Universidad de Chile in Santiago

    Talk Title: Speech Technology Research and Applications at LPTV

    Abstract: In this talk I will describe the research I have carried out in the Speech Processing and Transmission Laboratory (LPTV, Laboratorio de Procesamiento y Transmisión de Voz) in the last 17 years. LPTV is located at Universidad de Chile and was founded by me in 2000. I will discuss the seminar work on uncertainty and how the first results were achieved. As far as we know, those are the first uncertainty modelling in HMM. I will talk about our experience with speech technology for telephone applications and second language learning. Some relevant papers on stochastic Weighted Viterbi, multi-classifier fusion, CAPT and VoIP will be discussed. I will describe our state-of-the-art robotic platform that we have implemented to pursue our research on voice-based human-robot interaction. In this context, the locally normalized features will be presented to address the time varying channel problem. I will show demos and discuss ideas on voice-based HRI. Finally, I will summarize our results on multidisciplinary research on signal processing.

    Biography: Néstor Becerra Yoma received the PhD degree from University of Edinburgh, UK, and the M.Sc. and B.Sc. degrees from UNICAMP (Campinas State University), Sao Paulo, Brazil, all of them in Electrical Engineering, in 1998, 1993 and 1986, respectively. From 2000, he has been a Professor at the Department of Electrical Engineering, Universidad de Chile, in Santiago, where he is currently lecturing on telecommunications and speech processing. In 2011 he was promoted to the Full Professor position. From 2016 to 2017 he was a visiting professor at CMU, USA. At Universidad de Chile he started the Speech Processing and Transmission Laboratory to carry out research on speech technology applications on human-robot interaction, language learning, Internet and telephone line. His research interest also includes multidisciplinary research on signal processing in fields such as astronomy, mining and volcanology. He is the author of about 40 journal articles, 40 conference papers and three patents. Professor Becerra Yoma was an associate editor of the IEEE Transactions on Speech and Audio Processing from for four years.

    Host: Shrikanth Narayanan

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

    Audiences: Everyone Is Invited

    Posted By: Tanya Acevedo-Lam/EE-Systems

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  • Speech Technology Research and Applications at LPTV

    Wed, May 03, 2017 @ 02:00 PM - 04:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Nestor Becerra Yoma, Universidad de Chile in Santiago

    Talk Title: Speech Technology Research and Applications at LPTV

    Abstract: In this talk I will describe the research I have carried out in the Speech Processing and Transmission Laboratory (LPTV: Laboratorio de Procesamiento y Transmisión de Voz) in the last 17 years. LPTV is located at Universidad de Chile and was founded by me in 2000. I will discuss the seminar work on uncertainty and how the first results were achieved. As far as we know, those are the first uncertainty modelling in HMM. I will talk about our experience with speech technology for telephone applications and second language learning. Some relevant papers on stochastic Weighted Viterbi, multi-classifier fusion, CAPT and VoIP will be discussed. I will describe our state-of-the-art robotic platform that we have implemented to pursue our research on voice-based human-robot interaction. In this context, the locally normalized features will be presented to address the time varying channel problem. I will show demos and discuss ideas on voice-based HRI. Finally, I will summarize our results on multidisciplinary research on signal processing.

    Biography: Néstor Becerra Yoma received the PhD degree from University of Edinburgh, UK, and the M.Sc. and B.Sc. degrees from UNICAMP (Campinas State University), Sao Paulo, Brazil, all of them in Electrical Engineering, in 1998, 1993 and 1986, respectively. From 2000, he has been a Professor at the Department of Electrical Engineering, Universidad de Chile, in Santiago, where he is currently lecturing on telecommunications and speech processing. In 2011 he was promoted to the Full Professor position. From 2016 to 2017 he was a visiting professor at CMU, USA. At Universidad de Chile he started the Speech Processing and Transmission Laboratory to carry out research on speech technology applications on human-robot interaction, language learning, Internet and telephone line. His research interest also includes multidisciplinary research on signal processing in fields such as astronomy, mining and volcanology. He is the author of about 40 journal articles, 40 conference papers and three patents. Professor Becerra Yoma was an associate editor of the IEEE Transactions on Speech and Audio Processing from for four years.

    Host: Shrikanth Narayanan

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

    Audiences: Everyone Is Invited

    Posted By: Tanya Acevedo-Lam/EE-Systems

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  • Speech Technology Research and Applications at LPTV

    Wed, May 03, 2017 @ 02:00 PM - 04:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Nestor Becerra Yoma, Universidad de Chile in Santiago

    Talk Title: Speech Technology Research and Applications at LPTV

    Abstract: In this talk I will describe the research I have carried out in the Speech Processing and Transmission Laboratory (LPTV) in the last 17 years. LPTV is located at Universidad de Chile and was founded by me in 2000. I will discuss the seminar work on uncertainty and how the first results were achieved. As far as we know, those are the first uncertainty modelling in HMM. I will talk about our experience with speech technology for telephone applications and second language learning. Some relevant papers on stochastic Weighted Viterbi, multi-classifier fusion, CAPT and VoIP will be discussed. I will describe our state-of-the-art robotic platform that we have implemented to pursue our research on voice-based human-robot interaction. In this context, the locally normalized features will be presented to address the time varying channel problem. I will show demos and discuss ideas on voice-based HRI. Finally, I will summarize our results on multidisciplinary research on signal processing.

    Biography: Néstor Becerra Yoma received the PhD degree from University of Edinburgh, UK, and the M.Sc. and B.Sc. degrees from UNICAMP (Campinas State University), Sao Paulo, Brazil, all of them in Electrical Engineering, in 1998, 1993 and 1986, respectively. From 2000, he has been a Professor at the Department of Electrical Engineering, Universidad de Chile, in Santiago, where he is currently lecturing on telecommunications and speech processing. In 2011 he was promoted to the Full Professor position. From 2016 to 2017 he was a visiting professor at CMU, USA. At Universidad de Chile he started the Speech Processing and Transmission Laboratory to carry out research on speech technology applications on human-robot interaction, language learning, Internet and telephone line. His research interest also includes multidisciplinary research on signal processing in fields such as astronomy, mining and volcanology. He is the author of about 40 journal articles, 40 conference papers and three patents. Professor Becerra Yoma was an associate editor of the IEEE Transactions on Speech and Audio Processing from for four years.

    Host: Shrikanth Narayanan

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

    Audiences: Everyone Is Invited

    Posted By: Tanya Acevedo-Lam/EE-Systems

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  • Speech Technology Research and Applications at LPTV

    Wed, May 03, 2017 @ 02:00 PM - 04:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Nestor Becerra Yoma, Universidad de Chile in Santiago

    Talk Title: Speech Technology Research and Applications at LPTV

    Abstract: In this talk I will describe the research I have carried out in the Speech Processing and Transmission Laboratory (LPTV, Laboratorio de Procesamiento y Transmision de Voz) in the last 17 years. LPTV is located at Universidad de Chile and was founded by me in 2000. I will discuss the seminar work on uncertainty and how the first results were achieved. As far as we know, those are the first uncertainty modelling in HMM. I will talk about our experience with speech technology for telephone applications and second language learning. Some relevant papers on stochastic Weighted Viterbi, multi-classifier fusion, CAPT and VoIP will be discussed. I will describe our state-of-the-art robotic platform that we have implemented to pursue our research on voice-based human-robot interaction. In this context, the locally normalized features will be presented to address the time varying channel problem. I will show demos and discuss ideas on voice-based HRI. Finally, I will summarize our results on multidisciplinary research on signal processing.

    Biography: Nestor Becerra Yoma received his PhD degree from University of Edinburgh, UK, and the M.Sc. and B.Sc. degrees from UNICAMP (Campinas State University), Sao Paulo, Brazil, all of them in Electrical Engineering, in 1998, 1993 and 1986, respectively. From 2000, he has been a Professor at the Department of Electrical Engineering, Universidad de Chile, in Santiago, where he is currently lecturing on telecommunications and speech processing. In 2011 he was promoted to the Full Professor position. From 2016 to 2017 he was a visiting professor at CMU, USA. At Universidad de Chile he started the Speech Processing and Transmission Laboratory to carry out research on speech technology applications on human-robot interaction, language learning, Internet and telephone line. His research interest also includes multidisciplinary research on signal processing in fields such as astronomy, mining and volcanology. He is the author of about 40 journal articles, 40 conference papers and three patents. Professor Becerra Yoma was an associate editor of the IEEE Transactions on Speech and Audio Processing from for four years.

    Host: Shrikanth Narayanan

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

    Audiences: Everyone Is Invited

    Posted By: Tanya Acevedo-Lam/EE-Systems

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  • PhD Defense - Elaine Short

    Wed, May 03, 2017 @ 02:00 PM - 04:00 PM

    Computer Science

    University Calendar


    PhD Candidate: Elaine Short

    Title: Managing Multi-Party Social Dynamics for Socially Assistive Robotics

    Date: 05/03/17
    Time: 2-4pm
    Location: RTH 406

    Committee:

    Maja Matarić (Chair)
    David Traum
    Gaurav Sukhatme
    Gisele Ragusa (External)

    Abstract:

    This dissertation presents a domain-independent computational model of moderation of multi-party human-machine interactions that enables a robot or virtual agent to act as a moderator in a group interaction.
    A moderator is defined in this work as an agent that regulates social and task outcomes in a goal-oriented social interaction. This model has multiple applications in human-machine interaction: groups of people often require some management or facilitation to ensure smooth and productive interaction, especially when the context is emotionally fraught or the participants do not know each other well. A particularly relevant application domain for moderation is in Socially Assistive Robotics (SAR), where systems are frequently deployed without complex speech understanding or dialogue management, but where group interactions can benefit from a moderator's participation. The evaluation of the model focuses on intergenerational interactions, but the model is applicable to various other SAR domains as well, including group therapy, informal teaching between peers, and social skills therapy.

    Moderation is formalized as a decision-making problem, where measures of task performance and positive social interaction in a group are maximized through the behavior of a social moderator. This framework provides a basis for the development of a series of control algorithms for robot moderators to assist groups of people in improving task performance and managing the social dynamics of interactions in diverse domains. Based on reliably-sensed features of the interaction such as task state and voice activity, the moderator takes social actions that can predictably alter task performance and the social dynamics of the interaction. Thus the moderator is able to support human-human interaction in unpredictable, open-ended, real-world contexts.

    The model of moderation provides a framework for developing algorithms that enable robots to moderate group interactions without the need for speech recognition; it complements dialogue systems and human-computer interaction, providing conversational agents with additional strategies for managing dynamics of group interaction. Four algorithms are developed based on the model: a basic moderation algorithm, a task-goal-based moderation algorithm, a social-feature-based moderation algorithm, and a combined algorithm that takes into account both task goals and social features. These algorithms are validated in both peer-group interactions and inter-generational family interactions where the moderator supports interactions including members of multiple generations within the same family. The work is intended for short- and long-term deployments of socially assistive robots and virtual agents, and can be applied across assistive domains to facilitate social interactions and improve task performance.

    Location: Ronald Tutor Hall of Engineering (RTH) - 406

    Audiences: Everyone Is Invited

    Posted By: Lizsl De Leon

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  • AI Seminar

    Thu, May 04, 2017 @ 11:00 AM - 12:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Yan Liu, Associate Professor, USC

    Talk Title: Deep Learning Models for Time Series Data Analysis with Applications to Healthcare

    Abstract: Many emerging applications of big data involve time series data. We'll discuss a collection of deep learning models to effectively analyze and model large-scale time series data. We'll show experiment results to demonstrate the effectiveness of our models in healthcare.

    Biography: Yan Liu is an associate professor in Computer Science Department at University of Southern California from 2010. Before that, she was a Research Staff Member at IBM Research. She received her M.Sc and Ph.D. degree from Carnegie Mellon University in 2004 and 2007. Her research interest includes developing scalable machine learning and data mining algorithms for time series data and structured data with applications to social media analysis, computational biology, climate modeling and health care. She has received several awards, including NSF CAREER Award, Okawa Foundation Research Award, ACM Dissertation Award Honorable Mention, Best Paper Award in SIAM Data Mining Conference, Yahoo, IBM and Facebook Faculty Award and the winner of several data mining competitions, such as KDD Cup and INFORMS data mining competition.

    Host: Mayank Kejriwal

    More Info: http://webcastermshd.isi.edu/Mediasite/Play/5447fbec7809488a9444c23f8b3619ce1d

    Location: Information Science Institute (ISI) - 11th floor large conference room

    Audiences: Everyone Is Invited

    Posted By: Kary LAU

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  • The FuzzyLog Approach to Building Distributed Services

    Thu, May 04, 2017 @ 04:00 PM - 05:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Mahesh Balakrishnan, Yale University

    Talk Title: The FuzzyLog Approach to Building Distributed Services

    Abstract: Control plane applications such as coordination services, SDN controllers, filesystem namespaces, and big data schedulers have strong requirements for consistency as well as performance. Building such applications is currently a black art, requiring a slew of complex distributed protocols that are inefficient when layered and difficult to combine. The shared log approach (seen in the Corfu, Tango, and CorfuDB systems) achieves simplicity for distributed applications by replacing complex protocols with a single shared log; however, it does so by introducing a global ordering over all updates in the system, which can be expensive, unnecessary, and sometimes impossible. We propose the FuzzyLog abstraction, which provides applications the simplicity of a shared log without its drawbacks. The FuzzyLog allows applications to construct and access a durable, iterable partial order of updates in the system. FuzzyLog applications retain the simplicity of their shared log counterparts while extracting parallelism, providing a range of consistency guarantees and tolerating network partitions.

    Biography: Mahesh Balakrishnan is an Associate Professor (pre-tenure) at Yale University since Fall 2015. He received a PhD in Computer Science from Cornell University in 2009. He worked at Microsoft Research Silicon Valley from 2008 to 2014, where he co-led the CORFU and Tango projects on shared log systems, and briefly at VMware Research in 2015. His research interests span distributed systems, storage and networking. Currently, his research centers on new abstractions that simplify the construction of fast, reliable and consistent systems, while hiding the complexity of concurrency, failures and hardware details from programmers. He has published 35+ peer-reviewed papers in systems conferences such as SOSP, NSDI and FAST and journals such as TOCS. His current research is funded by NSF, Facebook Awards, and a VMware Early Career faculty grant.

    Host: Xuehai Qian, x04459, xuehai.qian@usc.edu

    Audiences: Everyone Is Invited

    Posted By: Gerrielyn Ramos

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  • Computer Science Doctoral Preview Day

    Fri, May 05, 2017 @ 10:00 AM - 02:00 PM

    Viterbi School of Engineering Graduate Admission

    Receptions & Special Events


    Join us in Los Angeles on May 5th for our Computer Science Department Doctoral Preview at the USC Viterbi School of Engineering.

    This event is a great opportunity for students to learn about the PhD program and the various research areas in CS at one of the top-ranked institutions in the nation. Travel grants may be available for highly qualified students traveling from outside the Southern California area.
    More info and registration

    Location: Ronald Tutor Hall of Engineering (RTH) -

    Audiences: Everyone Is Invited

    Posted By: USC Viterbi Graduate & Professional Programs

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  • NL Seminar - REPRESENTATION LEARNING FOR HUMAN AFFECT RECOGNITION-PhD Proposal Practice Talk

    Fri, May 05, 2017 @ 03:00 PM - 04:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Sayan Ghosh, USC/ICT

    Talk Title: REPRESENTATION LEARNING FOR HUMAN AFFECT RECOGNITION-PhD Proposal Practice Talk

    Series: Natural Language Seminar

    Abstract: Recent advances in end-to-end representation learning have made impressive strides in achieving state-of-the-art results in perception problems on speech, image and natural language. However, the area of affect understanding has mostly relied on off-the-shelf features to solve problems in emotion recognition, multi-modal fusion and generative modeling of affective speech and language. The potential impact of representation learning approaches to this area remains ripe for exploration. My thesis proposal is an important step in this direction. Firstly, I present an overview of my work on AU (Action Unit) detection, speech emotion recognition and glottal inverse filtering through speech modeling. Secondly, I introduce Affect LM, a novel neural language model for affective text generation which exploits prior knowledge through a dictionary of emotionally colored words such as the LIWC tool. Finally, I state some upcoming problems in representation learning for affect from speech and multi-modal language modeling which I plan to work on for the remainder of my degree.



    Biography: Sayan is a fourth-year PhD student at the University of Southern California, working at the Behavior Analytics and Machine Learning Group at the ICT Institute for Creative Technologies with Prof. Stefan Scherer. He is working on research towards building learning systems for better sensing of human behavior and emotion, and integrating deep learning techniques with human affect. His areas of interest include, but are not limited to deep learning, machine perception, affective computing, speech/signal processing, and generative modeling.

    Host: Nima Pourdamghani

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

    Location: Information Science Institute (ISI) - 11th Flr Conf Rm # 1135, Marina Del Rey

    Audiences: Everyone Is Invited

    Posted By: Peter Zamar

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  • Six Sigma Green Belt for Process Improvement

    Mon, May 08, 2017 @ 09:00 AM - 05:00 PM

    Executive Education

    Conferences, Lectures, & Seminars


    Speaker: TBD, TBD

    Talk Title: Six Sigma Green Belt for Process Improvement

    Abstract: Earn Six Sigma Green Belt Certification through the USC Viterbi School of Engineering, with Trojan Family pricing available. This is a 3-day course offered Monday-Wednesday from 9am-5pm. Please contact professional@gapp.usc.edu or call (213) 740-4488 for more details.

    Host: Professional Programs

    More Info: https://gapp.usc.edu/professional-programs/short-courses/industrial-systems/six-sigma-green-belt-process-improvement

    Audiences: Registered Attendees

    Posted By: Viterbi Professional Programs

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  • Six Sigma Green Belt for Process Improvement

    Mon, May 08, 2017 @ 09:00 AM - 05:00 PM

    Executive Education

    Conferences, Lectures, & Seminars


    Speaker: TBD, TBD

    Talk Title: Six Sigma Green Belt for Process Improvement

    Abstract: Earn Six Sigma Green Belt Certification through the USC Viterbi School of Engineering, with Trojan Family pricing available. This is a 3-day course offered Monday-Wednesday from 9am-5pm. Please contact professional@gapp.usc.edu or call (213) 740-4488 for more details.

    Host: Professional Programs

    More Info: https://gapp.usc.edu/professional-programs/short-courses/industrial-systems/six-sigma-green-belt-process-improvement

    Audiences: Registered Attendees

    Posted By: Viterbi Professional Programs

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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, May 08, 2017 @ 11:00 AM - 12:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Ram D. Sriram , Chief of Software and Systems, National Institute of Standards and Technology

    Talk Title: The Internet of Everything and Industrie 4.0

    Abstract: The Internet, which has spanned several networks in a wide variety of domains, is having a significant impact on every aspect of our lives. These networks are currently being extended to have significant sensing capabilities, with the evolution of the Internet of Things (IoT). With additional control we are entering the era of Cyber-physical Systems (CPS). In the near future the networks will go beyond physically linked computers to include multimodal-information from biological, cognitive, semantic, and social networks. This paradigm shift will involve symbiotic networks of people (social networks), smart devices, and smart phones or mobile personal computing and communication devices that will form smart net-centric systems and societies (SNSS), which is also known as Internet of Everything in the U.S. and Industrie 4.0 in Europe. These devices -“ and the network -- will be constantly sensing, monitoring, interpreting, and controlling the environment. In this talk, I will provide a unified framework for Internet of Things, Cyber-Physical Systems, and Smart Networked Systems and Societies, along with a brief introduction to Industrie 4.0. I will discuss the various research issues and representative projects at NIST.

    Biography: Ram D. Sriram is currently the chief of the Software and Systems Division, Information Technology Laboratory, at the National Institute of Standards and Technology. Before joining the Software and Systems Division, Sriram was the leader of the Design and Process group in the Manufacturing Systems Integration Division, Manufacturing Engineering Laboratory, where he conducted research on standards for interoperability of computer-aided design systems. Prior to joining NIST, he was on the engineering faculty (1986-1994) at the Massachusetts Institute of Technology (MIT) and was instrumental in setting up the Intelligent Engineering Systems Laboratory. Sriram has co-authored or authored more than 250 publications, including several books. Sriram was a founding co-editor of the International Journal for AI in Engineering. Sriram received several awards including: an NSF's Presidential Young Investigator Award (1989); ASME Design Automation Award (2011); ASME CIE Distinguished Service Award (2014); the Washington Academy of Sciences' Distinguished Career in Engineering Sciences Award (2015); ASME CIE division's Lifetime Achievement Award (2016). Sriram is a Fellow of ASME, AAAS, IEEE and Washington Academy of Sciences, and a member (life) of ACM and AAAI. Sriram has a B.Tech. from IIT, Madras, India, and an M.S. and a Ph.D. from Carnegie Mellon University, Pittsburgh, USA

    Host: S.K. Gupta

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

    Audiences: Everyone Is Invited

    Posted By: Estela Lopez

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  • USC Stem Cell Seminar: Arthur Lander, University of California, Irvine

    Tue, May 09, 2017 @ 11:00 AM - 12:00 PM

    Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Arthur Lander, University of California, Irvine

    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

    Posted By: Cristy Lytal/USC Stem Cell

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  • PhD Defense - Hao Wu

    Wed, May 10, 2017 @ 01:00 PM - 03:00 PM

    Computer Science

    University Calendar


    PhD Candidate: Hao Wu


    Committee:
    Kristina Lerman (chair)
    Kevin Knight
    Florenta Teodoridis (external)



    Title: Learning Distributed Representations from Network Data and Human Navigation

    Time: May 10 (Wed) 1:00-3:00pm


    Room: SAL 322


    Abstract:
    The increasing growth of network data in online social networks and linked documents on the Web, presents challenges for automatic feature generation for data analysis. We study the problem of learning representations from network data, which is of critical importance for real world applications, including document search, personalized recommendation and role discovery. Most existing approaches do not characterize the surrounding network structure that serves as context for each data point, or they cannot scale well to massive data in real world scenarios. We present novel neural network algorithms that learn distributed representations of network data by exploiting network structure and human navigation. The algorithms embed data into a common low-dimensional continuous vector space, which facilitates predictive tasks, such as classification, relational learning and analogy. Efficient optimization and sampling methods improve the scalability of our algorithms.

    First, we propose a neural embedding algorithm to learn distributed representations of generic graphs with global context. To capture the local network structure of each data point, we use random walks to sample nodes in a network neighborhood. Our algorithm is scale-invariant and the learned global representations can be used for similarity measurement of networks. We evaluate our model against state-of-the-art methods on node classification, role discovery and analogy tasks.

    Second, we present a neural language model for generating text in networked documents. The model can capture both the local context of word sequences and the semantic influence between linked documents. The approach is based on an intuition that authors are influenced by words in the documents they cite and readers usually read the words in paragraphs by referring to those cited concepts or documents. We show improved performance in document classification and link prediction with our model.

    Third, the information of how people navigate the network data online provides clues about missing links between cognitively similar concepts. Learning human navigation can also help characterizing human behavior and improving recommendation. We devise another neural network algorithm that accounts for human navigation patterns to learn better representations of text documents. We present empirical results of our algorithm on online news and movie review data, and show its effectiveness on real world applications.

    Location: Henry Salvatori Computer Science Center (SAL) - 322

    Audiences: Everyone Is Invited

    Posted By: Lizsl De Leon

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  • Viterbi School of Engineering PhD Hooding and Awards Ceremony

    Thu, May 11, 2017 @ 08:30 AM - 12:00 PM

    Viterbi School of Engineering Doctoral Programs

    Receptions & Special Events


    The Viterbi PhD Hooding and Awards Ceremony will take place on Thursday, May 11, 2017, from 8:30-11:00am in Bovard Auditorium. Tickets are required. The ceremony will be followed by a reception in Associates Park.

    Location: George Finley Bovard Administration Building (ADM) -

    Audiences: Everyone Is Invited

    Posted By: Jennifer Gerson

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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

    Thu, May 11, 2017 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Yongdae Kim , Professor, Korea Advanced Institute of Science and Technology (KAIST)

    Talk Title: Hacking Sensors

    Abstract: Sensors are designed to measure sensor inputs (e.g., physical quantities) and transfer sensor outputs (e.g. voltage signal) into the embedded devices. In addition, sensor-equipped embedded systems (called sensing-and-actuation systems) decide their actuations according to these sensor outputs, and the systems have no doubt whether the sensor outputs are legitimate or not. Sensors are essential components for safety-critical systems such as self-driving cars, drones and medical devices. Breaking safety in these systems may cause loss of life or disasters. Because of these safety reasons, sensors are often designed to be robust against failure or faults. However, can they maintain safety under adversarial conditions? In this talk, I detail how sensors can be spoofed or prevented from providing correct operation through regular and side-channels. Attacks on various devices such as medical devices, drones, autonomous vehicles and smart wearables will be shown. I'll complete the talk with a few directions and guides to prevent these attacks with a few open problems.

    Biography: Yongdae Kim is a Professor in the Department of Electrical Engineering and an Affiliate Professor in the GSIS at KAIST. He received his PhD from the computer science department at the University of Southern California in 2002. Between 2002 and 2012, he was an Associate/Assistant Professor in the Department of Computer Science and Engineering at the University of Minnesota Twin Cities. Before coming to the US, he worked 6 years in ETRI for securing Korean cyberinfrastructure. Between 2013 and 2016, he served as a KAIST endowed Chair Professor. He received an NSF career award on storage security and a McKnight Land-Grant Professorship Award from the University of Minnesota in 2005. Currently, he is serving as a steering committee member of NDSS and Associate Editor for ACM TISSEC. His current research interests include security issues for various systems such as cyber physical systems, social networks, cellular networks, P2P systems, medical devices, storage systems, mobile/ad hoc/sensor networks, and anonymous communication systems.

    Host: Bhaskar Krishnamachari and Paul Bogdan

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

    Audiences: Everyone Is Invited

    Posted By: Estela Lopez

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  • 2017 MFD Commencement Reception

    Fri, May 12, 2017 @ 12:15 PM - 02:00 PM

    Mork Family Department of Chemical Engineering and Materials Science

    Receptions & Special Events


    Location: Hedco Pertroleum and Chemical Engineering Building (HED) - 116

    Audiences: Department Only

    Posted By: Aleessa Atienza

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  • USC Stem Cell Seminar: Owen Witte, University of California, Los Angeles

    Tue, May 16, 2017 @ 11:00 AM - 12:00 PM

    Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Owen Witte, University of California, Los Angeles

    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

    Posted By: Cristy Lytal/USC Stem Cell

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  • Mork Family Department Graduate Seminar

    Thu, May 18, 2017 @ 11:00 AM - 12:00 PM

    Mork Family Department of Chemical Engineering and Materials Science

    Conferences, Lectures, & Seminars


    Speaker: Dr. Alexandre Shvartsburg, Wichita State University, Department of Chemistry

    Talk Title: High-Definition FAIMS for Proteomics, Metabolomics, and Structural Characterization Using Isotopologic Shifts

    Host: Dr. Nicholas Graham

    More Information: Shvartsburg abstract and bio.docx

    Location: Hedco Pertroleum and Chemical Engineering Building (HED) - 116

    Audiences: Everyone Is Invited

    Posted By: Aleessa Atienza

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  • PhD Defense - Luenin Barrios

    Thu, May 25, 2017 @ 10:00 AM - 12:00 PM

    Computer Science

    University Calendar


    PhD Candidate: Luenin Barrios

    Committee: Wei-Min Shen (chair), Stephan Haas, Aiichiro Nakano.

    Title: Simultaneous Center of Mass Estimation and Foot Placement Selection in Complex Planar Terrains for Legged Architectures

    Time: Thursday, May 25 at 10am

    Room: SAL 213

    Abstract:
    Center of Mass (CoM) path planning and foot placement selection in complex and rough terrains remains an important goal in the development of motion plans for legged robots. Precise CoM measurements and percipient foot placements are essential in understanding the behavior of a system, for example in gait selection or in extreme locomotion maneuvers. However, operating and maneuvering in difficult terrains has remained a challenging problem due to the diversity of environments and the complex interplay of foot placements and CoM motions. These locomotion maneuvers involve complex forces and movements that make analysis of CoM behavior a challenging task. Nevertheless, understanding CoM dynamics remains pivotal in locomotion planning for both humans and robots. Indeed, the critical element in robot and human motion planning revolves around the ability to accurately measure and describe the CoM. But given the cyclopean space of natural terrains available and the large number of kinematic shapes and sizes possible, the question arises: Is it conceivable to create a generalized framework for CoM construction and estimation with optimal foot placement selection that incorporates the large variety of kinematic architectures and terrains? The work described in this research addresses this issue by presenting a generalized geometric framework from which accurate CoM estimates are produced for the case of bipedal locomotion in complex planar terrains. This framework allows for the simultaneous treatment of CoM estimation and foot placement selection in legged architectures in an efficient and straightforward manner. This is a marked change from current methods for CoM position estimation that rely heavily on expensive and ungainly tools, for example force plates and motion capture video. These render CoM analysis impractical and time consuming and serve as an impediment to understanding locomotion maneuvers in uneven terrains. To tackle these challenges, this work proposes a reliable geometric approach for CoM estimation that delivers accurate CoM behavior in complex planar terrains. The geometric approach depends only on terrain geometry information and essential kinematic data of the moving body. Using this key information in conjunction with an Optimized Geometric Hermite (OGH) curve, a model is developed that produces accurate CoM position and phase space behavior. This phase space behavior is simultaneously optimized during CoM estimation to find candidate foot locations that produce an overall plan with minimum energy. This provides a way to synthesize complex maneuvers in rough terrains and to develop accurate CoM estimates and foot placement plans. Various human case studies were analyzed to validate the effectiveness of the approach. The results show that for natural walking over complex planar terrains, the geometric approach generates accurate CoM path approximations and state space trajectories and is a powerful tool for understanding CoM behavior and foot placements in irregular planar terrains.

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

    Audiences: Everyone Is Invited

    Posted By: Lizsl De Leon

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  • Repeating EventCNSL 2017 Conference on Nonconvex Statistical Learning

    Fri, May 26, 2017 @ 08:00 AM - 05:00 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars


    Speaker: Multiple, Multiple

    Talk Title: CNSL 2017 Conference on Nonconvex Statistical Learning

    Host: Epstein Department of Industrial & Systems Engineering

    More Information: CNSL2017_poster_lores.pdf

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

    Audiences: Everyone Is Invited

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    Posted By: Michele ISE

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  • NL Seminar-BUILDING ADAPTABLE AND SCALABLE NATURAL LANGUAGE GENERATION SYSTEMS

    Fri, May 26, 2017 @ 03:00 PM - 04:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Yannis Konstas, Univ. of Washington

    Talk Title: BUILDING ADAPTABLE AND SCALABLE NATURAL LANGUAGE GENERATION SYSTEMS

    Series: Natural Language Seminar

    Abstract: Traditionally, computers communicate with humans by converting computer readable input to human interpretable output, for example via graphical user interfaces. My research focuses on building programs that automatically generate textual output from computer-readable input. The majority of existing Natural Language Generation NLG systems use hard-wired rules or templates in order to capture the input for every different application and rely on small manually annotated corpora. In this talk, I will present a framework for building NLG systems using Neural Network architectures. The approach makes no domain specific modifications to the input and benefits from training on very large unannotated corpora. It achieves state of the art performance on a number of tasks, including generating text from meaning representations and source code. Such a system can have direct applications to intelligent conversation agents, source code assistant tools, and semantic based Machine Translation.



    Biography: A postdoctoral researcher at the University of Washington, Seattle, collaborating with Prof. Luke Zettlemoyer since 2015. His main research interest focuses on the area of Natural Language Generation NLG with an emphasis on data-driven deep learning methods. He has received BSc in Computer Science from AUEB Greece in 2007, and MSc in Artificial Intelligence from the University of Edinburgh 2008. He continued his study at the University of Edinburgh and received his PhD. degree in 2014. He has previously worked as a Research Assistant at the University of Glasgow 2008, and as a postdoctoral researcher at the University of Edinburgh 2014.



    Host: Marjan Ghazvininejad and Kevin Knight

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

    Location: Information Science Institute (ISI) - 11th Flr Conf Rm # 1135, Marina Del Rey

    Audiences: Everyone Is Invited

    Posted By: Peter Zamar

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  • Repeating EventCNSL 2017 Conference on Nonconvex Statistical Learning

    Sat, May 27, 2017 @ 08:00 AM - 05:00 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars


    Speaker: Multiple, Multiple

    Talk Title: CNSL 2017 Conference on Nonconvex Statistical Learning

    Host: Epstein Department of Industrial & Systems Engineering

    More Information: CNSL2017_poster_lores.pdf

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

    Audiences: Everyone Is Invited

    View All Dates

    Posted By: Michele ISE

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  • Amgen Seminar: Murielle Veniant-Ellison

    Wed, May 31, 2017 @ 11:00 AM - 12:00 PM

    Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Murielle Veniant-Ellison, Amgen

    Talk Title: FGF21 as a potential therapy for diabetes/obesity

    Series: USC/Amgen Seminar Series

    Host: USC/Amgen

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

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

    Audiences: Everyone Is Invited

    Posted By: Cristy Lytal/USC Stem Cell

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