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Events for October 20, 2016

  • Repeating EventBiotechnology Lecture Series

    Thu, Oct 20, 2016 @ 10:30 AM - 12:00 PM

    Alfred E. Mann Department of Biomedical Engineering

    Conferences, Lectures, & Seminars

    Speaker: Various, Amgen

    Talk Title: R&D Insights from Lab Bench to Patient Bedside

    Abstract: USC researchers have the opportunity to gain research and development insights with a new biotechnology lecture series sponsored by Amgen and the Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research at USC.

    The weekly lecture series, "R&D Insights from Lab Bench to Patient Bedside" takes place Thursdays at 10:30AM-12:00PM at USC's Health Sciences Campus from September 1, 2016 through November 10, 2016.

    The talks will feature Amgen scientists speaking about:

    Identifying a possible therapeutic target and its role in disease
    Increasing therapeutic efficacy and safety
    Process development, devices and manufacturing
    Case studies from bench to clinic

    Lectures will take place at the BCC First Floor Seminar Room or ZNI Herklotz Seminar Room.

    RSVP at http://www.usc.edu/esvp (use code: amgenlecture). Space is limited. Preference will be given to SCRM master's students, PhDs, and postdocs, and attending all lectures is mandatory.

    Please contact qliumich@usc.edu or karenw03@amgen.com for further details.

    Host: USC Stem Cell/Amgen

    More Info: https://calendar.usc.edu/event/biotechnology_lecture_series_rd_insights_from_lab_bench_to_patient_bedside?utm_campaign=widget&utm_medium=widget&utm_source=USC+Event+Calendar#.V8dKNLX8vW4

    Audiences: Everyone Is Invited

    View All Dates

    Contact: Cristy Lytal/USC Stem Cell

    Event Link: https://calendar.usc.edu/event/biotechnology_lecture_series_rd_insights_from_lab_bench_to_patient_bedside?utm_campaign=widget&utm_medium=widget&utm_source=USC+Event+Calendar#.V8dKNLX8vW4

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  • PhD Defense - Jiaping Zhao

    Thu, Oct 20, 2016 @ 11:00 AM - 12:00 PM

    Thomas Lord Department of Computer Science

    University Calendar

    Title: Toward situation awareness: activity and object recognition
    Time: Oct. 20 (Thursday), 10am ~ 12pm
    Location: HNB 107

    PhD Candidate: Jiaping Zhao

    Laurent Itti (chair)
    Aiichiro Nakano
    Bartlett Mel


    Situation awareness focuses on modelling and understanding the user's environment, and helps the user to be aware of his current situation and anticipate future events. Often, situation awareness is divided into three levels: environmental perception, situation understanding and cognitive assistance. Here, we focus on the second level -"situation understanding", to understand the user's situation by analyzing and interpreting the perceived data.

    Nowadays, mobile devices with embedded IMU sensors and cameras are ubiquitous: IMU sensors capture streams of acceleration and angular speed records, while camera records video streams. The former steams are multi-variate time series, while the latter are image sequences. At current stages, we analyze time series and image frames separately to understand the user's situation: concretely, we infer user's current activities from time series, while recognize objects from images.

    First, we address activity recognition from time series. Activity recognition is naturally formulated as a time series classification problem. To achieve this goal, we developed several algorithms trying to address existing problems. First, we introduced a time series segmentation algorithm, which decomposes heterogeneous time series into homogenous segments. Then we proposed a new sequence alignment algorithm, named shapeDTW, which improves the traditional dynamic time warping (DTW) alignment by taking local temporal shapes into account. To better compare the similarity between temporal sequences, we proposed to learn multiple local distance metrics, and the measured DTW distance under the learned metrics, instead of under the default Euclidean metric, performs significantly for time series classification.

    Then we did object recognition from natural images. Although contemporary deep convolutional networks advanced objection recognition by a big step, the underneath mechanism is still largely unclear. Here, we attempted to explore the mechanism of object recognition using a large-scale image dataset, iLab20M, which contains 20 million images shot under controlled turntable settings. Compared with the ImageNet dataset, iLab20M is parametric, with detailed pose and lighting information for each image. Here we showed the auxiliary information could benefit object recognition. First, we formulate object recognition in a CNN-based multi-task learning framework, designed a specific skip connection pattern, and showed its superiority to single task learning theoretically and empirically. Moreover, we introduced an two-stream CNN architecture, which disentangles object identity from its instantiation factors (e.g., pose, lighting), and learned more discriminative identity representations. We experimentally showed that the learned feature from iLab20M generalizes well to other datasets, including ImageNet and Washington RGB-D.

    Location: 107

    Audiences: Everyone Is Invited

    Contact: Lizsl De Leon

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  • CS Colloquium and RASC seminar: Ali Agha (Caltech, JPL) - Quantifiably safe robot motion planning under motion and sensing uncertainty

    Thu, Oct 20, 2016 @ 03:30 PM - 05:00 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars

    Speaker: Ali Agha, Caltech, JPL

    Talk Title: Quantifiably safe robot motion planning under motion and sensing uncertainty

    Series: RASC Seminar Series

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

    Planning robot motions amidst obstacles, while actively enhancing localization, is a key component for true autonomy. With a growing number of autonomous robots and safety-critical applications, it is of paramount importance to design planners with the ability to guarantee and quantify the system's safety. In this talk, we explore planning methods that reason about the acquisition of future perceptual knowledge and incorporate this knowledge in planning to accurately quantify the success probability and safety of the plan. In particular, I present a planning framework under motion and sensing uncertainty, called Feedback-based Information RoadMap (FIRM). FIRM is a multi-query graph in belief space (space of probability distributions), which can be viewed as the belief space variant of the celebrated PRM (probabilistic roadmap). Each node of FIRM is a belief. Each edge (belief-to-belief transition) is realized via composition of closed-loop controllers that behave like funnels in belief space. We also discuss the feedback nature and scalability of the generated plan. We will demonstrate this approach in the context of robot navigation in indoor GPS-denied environments.

    Biography: Ali-Akbar Agha-Mohammadi is a Robotics Research Technologist at NASA JPL/California Institute of Technology. Previously, he was a research engineer at Qualcomm Research and a post-doctoral researcher at LIDS/ACL at MIT. He has received his Ph.D. in Computer Science and Engineering from Texas A&M. He also holds B.S. and M.S. degrees in Electrical Engineering (Control Systems). His research interests include robotics, stochastic systems, control systems, estimation, and filtering theory.

    Host: CS Department

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

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair

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  • Preparing for Technical Interviews

    Thu, Oct 20, 2016 @ 03:30 PM - 04:30 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions

    Join Electronic Arts Representatives as they go over insider tips on technical interviewing as well as the best strategies for success.

    Location: Mark Taper Hall Of Humanities (THH) - 201

    Audiences: Viterbi CSCI & CECS Majors

    Contact: RTH 218 Viterbi Career Connections

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  • EE 598 Computer Engineering Seminar

    Thu, Oct 20, 2016 @ 04:00 PM - 05:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars

    Speaker: Subhasish Mitra, Professor, Stanford University

    Talk Title: Robust Systems: From Today to the N3XT 1,000X

    Abstract: Today's mainstream electronic systems typically assume that transistors and interconnects operate correctly over their useful lifetime. With enormous complexity and significantly increased vulnerability to failures compared to the past, future system designs cannot rely on such assumptions. At the same time, there is explosive growth in our dependency on such systems.

    Robust system design is essential to ensure that future systems perform correctly despite rising complexity and increasing disturbances. For coming generations of silicon technologies, several causes of hardware failures, largely benign in the past, are becoming significant at the system-level. Furthermore, emerging nanotechnologies such as carbon nanotubes are inherently highly subject to imperfections. Such Nano-Engineered Computing Systems Technologies (N3XT) are key to building transformative nanosystems since future computing demands far exceed the capabilities of today's electronics.
    This talk will address the following major robust system design goals:
    • New approaches to thorough test and validation that scale with tremendous growth in complexity.
    • Cost-effective tolerance and prediction of failures in hardware during system operation.
    • A practical way to build nanosystems that can overcome substantial inherent imperfections in emerging nanotechnologies and deliver three orders of magnitude energy efficiency improvements for future data-intensive applications.
    Significant recent progress in robust system design impacts almost every aspect of future systems, from ultra-large-scale networked systems all the way to their nanoscale components.

    Biography: Professor Subhasish Mitra directs the Robust Systems Group in the Department of Electrical Engineering and the Department of Computer Science of Stanford University, where he is the Chambers Faculty Scholar of Engineering. Before joining Stanford, he was a Principal Engineer at Intel.
    Prof. Mitra's research interests include robust systems, VLSI design, CAD, validation and test, nanosystems, and neurosciences. His X-Compact technique for test compression has been key to cost-effective manufacturing and high-quality testing of a vast majority of electronic systems, including numerous Intel products. X-Compact and its derivatives have been implemented in widely-used commercial Electronic Design Automation tools. He, jointly with his students and collaborators, demonstrated the first carbon nanotube computer, and it was featured on the cover of NATURE. The US NSF presented this work as a Research Highlight to the US Congress, and it also was highlighted as "an important, scientific breakthrough" by the BBC, Economist, EE Times, IEEE Spectrum, MIT Technology Review, National Public Radio, New York Times, Scientific American, Time, Wall Street Journal, Washington Post, and numerous others worldwide.

    Prof. Mitra's honors include the Presidential Early Career Award for Scientists and Engineers from the White House, the highest US honor for early-career outstanding scientists and engineers, the ACM SIGDA/IEEE CEDA A. Richard Newton Technical Impact Award in Electronic Design Automation, "a test of time honor" for an outstanding technical contribution, the Semiconductor Research Corporation's Technical Excellence Award, and the Intel Achievement Award, Intel's highest corporate honor. He and his students published several award-winning papers at major venues: IEEE/ACM Design Automation Conference, IEEE International Solid-State Circuits Conference, IEEE International Test Conference, IEEE Transactions on CAD, IEEE VLSI Test Symposium, Intel Design and Test Technology Conference, and the Symposium on VLSI Technology. At Stanford, he has been honored several times by graduating seniors "for being important to them during their time at Stanford."

    Prof. Mitra has served on numerous conference committees and journal editorial boards. He served on DARPA's Information Science and Technology Board as an invited member. He is a Fellow of the ACM and the IEEE.

    Host: Xuehai Qian

    Location: OHE 100D

    Audiences: Everyone Is Invited

    Contact: Estela Lopez

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  • EA Tech Talk

    Thu, Oct 20, 2016 @ 06:00 PM - 07:30 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions

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

    Audiences: All Viterbi

    Contact: RTH 218 Viterbi Career Connections

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  • Information Session in Beijing, China

    Thu, Oct 20, 2016 @ 07:00 PM - 09:00 PM

    Viterbi School of Engineering Graduate Admission

    Workshops & Infosessions

    Interested in graduate studies in engineering or computer science?

    Candidates with a strong academic background and a Bachelor's degree in engineering, computer science, applied mathematics, or physical science (such as physics, biology, or chemistry) are welcome to attend an information session to learn more about applying to graduate engineering programs at the University of Southern California.

    These events will be hosted by Ray Xu, Director of the USC Viterbi Shanghai Office, and joined by Camillia Lee, Assistant Dean for Graduate Recruitment at the USC Viterbi School of Engineering.

    Topics to be covered:

    - Master's & Ph.D. Programs in Engineering and Computer Science
    - How to Apply
    - Scholarships and Funding
    - Student Life at USC and in Los Angeles
    - Application Tips

    There will also be sufficient time for questions during the information session.

    For questions about these events, please contact us at viterbi.gradprograms@usc.edu.


    Location: Crowne Plaza Beijing Zhongguancun, Beijing, China

    Audiences: Prospective students with a background in engineering, math or hard science

    Contact: Mary Kae/Graduate and Professional Programs

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