DSAT: Data Sciences, Analytics & Technologies

The Data Sciences, Analytics, and Technologies (DSAT) Symposium is an integral part of the overall IEEE COMPSAC conference. DSAT uniquely positions itself as a forum for both researchers and practitioners in Big Data as it relates to data sciences, data analytics, and associated technologies.  DSAT invites authors to present recent findings, innovations, theories, experiences, and ideas. Technical contributions accepted by DSAT will likely cover theory, applications, pragmatics, systems and services enabled by the Web, underlying technologies, data science, e-science, and concomitant big data analytics. The goal of DSAT is to deepen the understanding of, fostering innovation in, and sharing of practical applications around Big Data.

Topic areas to include, but not limited to: Applied data science, Anomaly detection, computational intelligence for Big Data analytics, Business analytics, Business informatics, Data information and knowledge, Data mining, Data warehousing, Exploring and visualizing data, Interactive visualization, Modeling and simulation, Privacy, and Security. Consider potential focus with the interconnected relationships of Big Data, Cloud, Fog, Edge Computing, IoT, mobile computing, and pervasive computing.

Some authors will be invited to submit expanded papers for the IEEE Transactions on Big Data journal COMPSAC special issue.

Paper Submission Site

DSAT Symposium Chairs

Kathy Grise, IEEE Future Directions Program Director, USA
Email: k.l.grise@ieee.org

Maria Lee, Shih Chien University, Taiwan
Email: maria.lee@g2usc.edu.tw

Program Committee

Boualem Benatallah, University of New South Wales, Australia
Duygu Celik, Istanbul Aydin University, Turkey
Yuen Chau, Singapore  University of Tech and Design, Singapore
Hanhua Chen, Huazhong University of Science & Technology, China
Yi Chen, New Jersey Institute of Technology, USA
Yiuming Cheung, Hong Kong Baptist University, Hong Kong
Atilla Elçi, Aksaray University, Turkey
Kathy Grise, IEEE Future Directions, USA
Hongbo Jiang, Huazhong University of Science & Technology, China
Iman Keivanloo, Concordia University, Canada
Bing Kuo, Northwestern Polytechnic University, China
Ke Li, University of Exeter, UK
Xin Liu, MDA
WIlliam Liu, Auckland University of Technology
Yue Ma, TU Dresden, Germany
Mihhail Matskin, KTH Royal Institute of Technology, Sweden
Hong Mei, Peking University, China
Leandro Minku, University of Leicester, UK
Partha P Ghosh, Microsoft Research, USA
Jun Pang, University of Luxembourg, Luxembourg
Fernando Silva Parreiras, FUMEC University, Brazil
Martin Rezk, Free University of Bozen-Bolzano, Italy
Juergen Rilling, Concordia University, Canada
Jon Rokne, University of Calgary, Canada
Roberto Saracco, ICT Labs
Mei-Ling Shyu, University of Miami, USA
Hemant Singh, Australian Defence Force Academy, Australia
Shuo Wang, University of Birmingham, UK
Honghan Wu, University of Aberdeen, UK
Jiewen Wu, IBM Research
Tian Xia, Huazhong University, China
Guohui Xiao, University of Bozen-Bolzano, Italy
Chetan Yadati, Accenture Solutions
Xin Yao, The University of Birmingham, UK
Kenichi Yoshida, University of Tsukuba, Japan
Weider Yu, San Jose State University, USA