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Chen

教授

University

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Dr.Chen Jinjun-1Biography: Dr. Jinjun Chen is an Associate Professor from Faculty of Engineering and IT, University of Technology Sydney (UTS), Australia. He is the Director of Lab for Cloud Computing and Data Intensive Systems at UTS. He holds a PhD in Information Technology from Swinburne University of Technology, Australia. Dr. Chen’s research interests include big data, data science, data intensive systems, scalability, cloud computing, software engineering and services, workflow management, privacy and security, and related various research topics. His research results have been published in more than 130 papers in international journals and conferences, including IEEE Transactions on Service Computing, ACM Transactions on Autonomous and Adaptive Systems, ACM Transactions on Software Engineering and Methodology (TOSEM), IEEE Transactions on Software Engineering (TSE), IEEE Transactions on Parallel and Distributed Systems (TPDS), IEEE Transactions on Cloud Computing, and IEEE Transactions on Computers (TC). He received UTS Vice-Chancellor’s Awards for Research Excellence Highly Commended (2014), UTS Vice-Chancellor’s Awards for Research Excellence Finalist (2013), Swinburne Vice-Chancellor’s Research Award for early career researchers (2008), IEEE Computer Society Outstanding Leadership Award (2008-2009) and (2010-2011), IEEE Computer Society Service Award (2007), Swinburne Faculty of ICT Research Thesis Excellence Award (2007). He is an Associate Editor for ACM Computing Surveys, IEEE Transactions on Big Data, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Parallel and Distributed Systems, and IEEE Transactions on Cloud Computing. He is the Chair of IEEE Computer Society’s Technical Committee on Scalable Computing (TCSC), Vice Chair of Steering Committee of Australasian Symposium on Parallel and Distributed Computing, Founder and Coordinator of IEEE TCSC Technical Area on Big Data and MapReduce, Founder and Steering Committee Co-Chair of IEEE International Conference on Big Data and Cloud Computing, IEEE International Conference on Big Data Science and Engineering, and IEEE International Conference on Data Science and Data Intensive Systems.

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