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人工智能拓展火灾安全研究的进展
From The Sky To The Sea
清华大学材料科学与工程研究院《材料科学论坛》:基于拓扑缺陷理论的轻合金组织设计新...
Quantum information processing based on bosonic modes
报告题目:
Algorithmic Crowdsourcing and Applications in Big Data
 报告人:
Jie Wu
professor of Temple University
报告时间:
2014-07-03 10:00
报告地点:
1-415,FIT Building
主办单位:
Research Institute of Information Technology (RIIT), Tsinghua University
  简介:

Biography:

Jie Wu is the chair and a Laura H. Carnell Professor in the Department of Computer and Information Sciences at Temple University. Prior to joining Temple University, he was a program director at the National Science Foundation and Distinguished Professor at Florida Atlantic University. His current research interests include mobile computing and wireless networks, routing protocols, cloud and green computing, network trust and security, and social network applications. Dr. Wu regularly publishes in scholarly journals, conference proceedings, and books. He serves on several editorial boards, including IEEE Transactions on Computers, IEEE Transactions on Service Computing, and Journal of Parallel and Distributed Computing. Dr. Wu was general co-chair/chair for IEEE MASS 2006, IEEE IPDPS 2008 and IEEE ICDCS 2013, as well as program co-chair for IEEE INFOCOM 2011 and CCF CNCC 2013. Currently, he is serving as general chair for ACM MobiHoc 2014.  He was an IEEE Computer Society Distinguished Visitor, ACM Distinguished Speaker, and chair for the IEEE Technical Committee on Distributed Processing (TCDP). Dr. Wu is a CCF Distinguished Speaker and a Fellow of the IEEE. He is the recipient of the 2011 China Computer Federation (CCF) Overseas Outstanding Achievement Award.

Abstract:

This talk gives a survey of crowdsourcing applications, with a focus on algorithmic solutions. The recent search for flight 370 is used first as a motivational example.  Fundamental issues in crowdsourcing, in particular, incentive mechanisms for paid crowdsourcing, and algorithms and theory for crowdsourced problem-solving, are then reviewed. Several applications of algorithmic crowdsourcing applications are discussed in detail, with a focus on big data. The talk also discusses several on-going projects on crowdsourcing at Temple University.

 

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