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Events for November 10, 2017

  • Repeating EventMeet USC: Admission Presentation, Campus Tour, and Engineering Talk

    Fri, Nov 10, 2017

    Viterbi School of Engineering Undergraduate Admission

    Receptions & Special Events

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

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

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


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

    Audiences: Prospective Freshmen & Family Members

    View All Dates

    Contact: Viterbi Admission


    Fri, Nov 10, 2017 @ 01:00 PM - 02:00 PM

    USC Viterbi School of Engineering

    Conferences, Lectures, & Seminars

    Speaker: Dr. Rosanna Smart, Associate Economist at RAND Corporation

    Talk Title: The Many Impacts of Marijuana

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

    Audiences: Everyone Is Invited

    Contact: Su Stevens

  • PhD Defense - Charith Wickramaarachchi

    Fri, Nov 10, 2017 @ 01:00 PM - 03:00 PM

    Thomas Lord Department of Computer Science

    University Calendar

    Dynamic Graph Analytics for Cyber Systems Security Applications
    Ph.D. candidate: Charith Wickramaarachchi
    Friday, November 10, 2017
    1:00PM, SAL 322
    State of the art cyber systems are becoming an organic part of our day to day life with the advancement of internet infrastructure, mobile technologies, and sensor networks. As a result, protecting cyber systems against attacks has become a task of vital importance. However, the highly complex nature of modern cyber systems makes designing of security solutions a challenging task. The mission-critical nature of these systems demands low latency solutions that identify and prevent attacks.
    Graphs are fundamental in representing complex interconnected systems and data. Thus, graph representation based security solutions will play a crucial role in future cyber systems security solutions. We propose a set of fundamental dynamic graph algorithms that can be used to develop cyber systems security solutions.
    First, we present distributed dynamic graph algorithms that can be used to prevent attacks on cyber systems. We develop distributed algorithms to monitor vertices in a dynamic network to detect if they become a part of a given graph pattern. Evaluations on a diverse set of real-world datasets demonstrate that ~99% savings in computation and communication is achieved by the proposed algorithms compared with state of the art.
    Next, to provide high accuracy subgraph pattern matching in dynamic networks, we present a distributed algorithm for exact subgraph matching (i.e., subgraph isomorphism). To improve the latency and scalability of the solution, we propose a lossless distributed graph pruning technique based on graph simulation. Evaluation results demonstrate that our proposed method is highly effective on small-world graphs.
    Finally, we present a set of dynamic Steiner tree based protection schemes to address a security vulnerability in the smart grid state estimation process. The proposed protection schemes consider the dynamic nature of the criticality of buses in power transmission networks to provide optimal cost protection recommendations. We develop scalable, highly accurate heuristic algorithms to obtain security recommendations with low latency.
    Charith Wickramaarachchi received the BSc (Hons) degree (2010) in Computer Science and Engineering from University of Moratuwa and the MS degree (2016) in Computer Science from University of Southern California. He is currently a Ph.D. candidate at the Department of Computer Science at University of Southern California. His research interests are in the areas of large-scale graph processing and data stream processing in distributed environments such as Clouds. He is a member of IEEE, an elected committer and a project management committee member of Apache Software Foundation.
    Defense Committee: Viktor K. Prasanna (chair), Rajgopal Kannan, Aiichiro Nakano, Cauligi Raghavendra

    Location: 322

    Audiences: Everyone Is Invited

    Contact: Lizsl De Leon

  • Seminars in Biomedical Engineering

    Fri, Nov 10, 2017 @ 02:00 PM - 03:00 PM

    Alfred E. Mann Department of Biomedical Engineering

    Conferences, Lectures, & Seminars

    Speaker: Ho Sung Kim, PhD, Assistant Professor of Neurology, Neurology

    Talk Title: TBA

    Abstract: TBA

    Biography: My research spans an interdisciplinary cross-section of Medical Image Processing, Machine learning and Neuroscience covering clinical neurology and neuropsychiatry. In the fields of medical image processing and analysis, I have studied on multicontrast image registration and segmentation, surface modeling of cortical/subcortical structures which are the prerequisite techniques to proceed the analysis of structural and functional brain imaging studies.
    My projects that has been recently launched at USC-INI and USC-LONI include mainly two domains of the research field: 1) Prediction of neurodevelopmental outcome in neonates with various clinical conditions such as preterm birth, hypoxia-ischemia and congenital heart disease: This project rapidly expands in line with my team's expertise of neurodevelopment, neuroimaging, computational imaging feature modeling and machine learning (particularly DEEP learning); 2) Neuroimaging data quality controls (image QC): My team dedicates its efforts to implementation of online-based LONI-QC system that allows the public to evaluate their own data as well as to automated QC feature that will ultimately predict the accuracy of brain image post-processing and the sensitivity in the subsequently biological / clinical analysis to given target pathophysiology.
    In clinical / neuroscientific applications, my team has applied various advanced analytic frameworks, including cortical morphometry, voxel-based morphometry, deformation-based morphometry and structural network analysis, to assessment of brain structure in healthy conditions as well as pathological conditions, which often present anatomical variations beyond the range of normal structures.
    My team continues to expand aforementioned techniques to the analysis of BIG DATA of brain imaging data of patients with various diseases and disorders such as stroke, epilepsy, dementia and sleep disorders.

    Host: Brent Liu, PhD

    More Information: hosungkim.jpg

    Location: Corwin D. Denney Research Center (DRB) - 145A

    Audiences: Everyone Is Invited

    Contact: Mischalgrace Diasanta

  • NL Seminar-On Real-Time Graph Transducers

    Fri, Nov 10, 2017 @ 03:00 PM - 04:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars

    Speaker: Anssi Yli-Jyrä , Univ of Helsinki

    Talk Title: On Real-Time Graph Transducers

    Series: Natural Language Seminar

    Abstract: Finite computers and universal computers. Often a practical solution combines both of these two extremes because formally powerful models are simulated by physical machines that approximate them. This is especially true for recurrent neural networks whose activation vector is the key to deeper understanding of their emergent finite state behavior. However, we currently have only a very loose characterization for the finite-state property in neural networks. In order to construct a hypothesis for a possible bottom up organization of the state space of activation vectors of RNNs, I compare neural networks with bounded Turing machines and finite state machines, and quote recent results on finite state models for semantic graphs. These models enjoy the nice closure properties of weighted finite state machines. In the end of the talk, I sketch my vision for neural networks that perform finite state graph transductions in real time. Such transductions would have a vast variety of applications in machine translation and semantic information retrieval involving big data.

    Biography: Anssi Yli Jyrä has the titles of Adjunct Professor Docent in Language Technology at the University of Helsinki and Life Member of Clare Hall College at the University of Cambridge. He is currently a PI and a Research Fellow of the Academy of Finland in a project concerning universality of finite state syntax. He has published a handbook on Hebrew and Greek morpheme alignments in the Finnish Bible translation together with a group of Digital Humanists, and then served the Finnish Electronic Library at CSC IT Centre of Science where he built an internet harvester and a search engine for the Finnish WWW. In 2005, he earned his PhD from the University of Helsinki and then worked as a coordinator for the Language Bank of Finland at CSC. There he contributed to pushing his employer to what is now known as the CLARIN European Research Infrastructure Consortium. He became the first President of SIGFSM in 2009, after fostering and organizing FSMNLP conferences for several years. In 2012-2013, he served as a Subject Head of Language Technology in his home university before visiting the Speech Group at the Department of Engineering, Cambridge University. He has supervised theses and contributed to the theoretical basis of Helsinki Finite State Transducer HFST library. In his own research, Yli Jyrä constantly pursues unexplored areas, applying finite-state transducers to graphical language processing tasks such as autosegmental phonology, constraint interaction, and dependency syntax and neural semantics. He is a qualified teacher and interested in the occurrence of flow in agile programming and simultaneous translation.

    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

    Contact: Peter Zamar

    Event Link: http://nlg.isi.edu/nl-seminar/