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  • Keynote Speakers

    Abstract

    Keynote Speaker Kai Hwang Kai Hwang, Ph.D. (UC Berkeley 1972), IEEE Life Fellow Professor of EE/CS at University of Southern California kaihwang@usc.edu USC office: 1-213-740-4470 (leave voice message) KAI HWANG is a Professor of Electrical

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    Keynote Speaker

    Kai Hwang



    Kai Hwang, Ph.D. (UC Berkeley 1972), IEEE Life Fellow
    Professor of EE/CS at University of Southern California
    kaihwang@usc.edu
    USC office: 1-213-740-4470 (leave voice message)

    KAI HWANG is a Professor of Electrical Engineering and Computer Science at the Univ. of Southern California (USC). He earned the Ph.D. in Electrical Engineering and Computer Science from the Univ. of California, Berkeley in 1972. He has taught at Purdue Univ. over 11 years prior to joining USC in 1985. At present, he also serves as an EMC-endowed visiting Chair Professor at Tsinghua Univ., China.
    Dr. Hwang has engaged in academic work, creative research and higher education for 43 years in computer science, digital systems, and information technology. He specializes in computer architecture, parallel processing, distributed systems, high-performance computing, cloud computing, networking and communications, P2P networks, pervasive computing, and network security etc.
    Hwang has published 8 books and over 240 scientific papers in Computer Science/Engineering and Internet Technology. According to Google Scholar, his published work has been cited more than 15,000 times. He has a h-index of 53, meaning that 53 papers are cited at least h = 53 times each.

    Big Data Analytics or Cognitive Computing ot TensorFlow for Deep Machine Learning

    Kai Hwang, IEEE Life Fellow
    Professor of EE/CS at University of Southern California
    kaihwang@usc.edu

    Junwei Cao



    Professor and Deputy Director
    Research Institute of Information Technology
    Tsinghua National Laboratory for Information Science and Technology
    TSINGHUA UNIVERSITY

    Biography
    Junwei Cao is currently Professor and Deputy Director of Research Institute of Information Technology, Tsinghua University, China. He is also Director of Open Platform & Technology Division, Tsinghua National Laboratory for Information Science and Technology, Beijing, China. His research is focused on distributed computing technology and applications.
    Before joining Tsinghua in 2006, Junwei Cao was Research Scientist of LIGO Laboratory, Massachusetts Institute of Technology, USA. Before that he worked as Research Scientist of NEC Europe Ltd., Germany. Junwei Cao got his PhD in computer science from University of Warwick, UK, in 2001. He got his master and bachelor degrees from Tsinghua University in 1998 and 1996, respectively. Junwei Cao has published over 200 academic papers and books. He is a council member of LIGO Scientific Collaboration.

    Applying Machine Learning for Gravitational-wave Burst Data Analysis

    Junwei Cao
    Research Institute of Information Technology
    Tsinghua National Laboratory for Information Science and Technology
    Tsinghua University, Beijing 100084, China
    E-mail: jcao@tsinghua.edu.cn

    The direct detection of gravitational waves is enabled by both instrumental technology and massive data analysis. Data glitches can easily be mistaken for gravitational-wave signals, and their robust identification and removal will help any search for gravitational waves. We apply machine-learning algorithms (MLAs) to the problem, using data from auxiliary channels within the LIGO detectors that monitor degrees of freedom unaffected by astrophysical signals. Noise sources may produce artifacts in these auxiliary channels as well as the gravitational-wave channel. The number of auxiliary channel parameters describing these disturbances may also be extremely large; high dimensionality is an area where MLAs are particularly well suited. We demonstrate the feasibility and applicability of three different MLAs: artificial neural networks, support vector machines, and random forests, for veto analysis of gravitational wave bursts.

     

    Lican Huang



    Prof. Lican Huang works on challenges about Cloud Computing and P2P computing. He has worked on e-Science and Grid computing since the beginning of 2000’s. He was honored in Marquis Who’s Who in the World 2006, Marquis Who’s Who in the Science and Engineering 2006-2007, and Marquis Who’s Who in Asia 2006-2007 due to his achievement of proposing Virtual and Dynamic Hierarchical Architecture for e-Science and Grid and VIRGO protocols. He serves as program committee member of many international conferences. He has contributed over 100 technical papers to various conferences and refereed journals. He is senior IEEE member.

    Prof. Huang now is a Professor at Zhejiang Sci-Tech University (ZSTU) and founder of yvsou.com(www.yvsou.com). Prior to joining ZSTU, Prof. Huang worked as a Senior Research Associate in the School of Computer Science at Cardiff University since 2004. Before working at Cardiff University, he developed many large software systems in several companies, as technical leader or department manager. He obtained his Ph.D. in Computer Science from Zhejiang University in 2003, Bachelor’s From Nanchang University in 1982, and Master’s from Hangzhou University in 1984.

    DSCloud Platform: distributed high performance computing based on semantic P2P networks.

    Abstract— we present a novel distributed computation based on semantic P2P network, in which the peers can be grouped virtually into hierarchical classified domains and the problems are partitioned into sub-problems and scheduled to these nodes. This strategy is scalable to millions of computers effectively in theory. We have implemented distributed knapsack problem solution in our semantic P2P network platform in scale nodes. We here give the guide about how to use the software. The next is to scale to thouthands nodes.


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