About Data Science 2018
INFORMS Workshop on Data Science is a premier research conference dedicated to developing data science theories, methods, and algorithms to solve challenging and practical problems that benefit business and society at large. The workshop invites innovative data science research contributions that address business and societal challenges from the lens of statistical learning, data mining, machine learning, and artificial intelligence. The workshop invites original research addressing challenges in marketing, finance, and supply chain applications to problems in healthcare, energy, cybersecurity, social network services, privacy, credibility, etc. Contributions on novel methods may be motivated by insightful observations on the limitations of existing data science methods to address practical challenges, or by studying entirely novel data science problems. Research contributions on theoretical and methodological foundations of data science, such as optimization for machine learning and new algorithms for data mining, are also welcome.
Organizing Committee
Honorary Chairs
Olivia Sheng, University of Utah
Alexander S. Tuzhilin, New York University
Conference Chairs
Weiguo (Patrick) Fan, University of Iowa
Maytal Saar-Tsechansky, University of Texas, Austin
Raghu T. Santanam, Arizona State University
Program Chairs
Ting Li, Erasmus University Rotterdam
Xiaobai (Bob) Li, University of Massachusetts Lowell
Balaji Padmanabhan, University of South Florida
Publicity Chairs
Syam Menon, University of Texas at Dallas
Paul Pavlou, Temple University
Galit Shmueli, National Tsing Hua University
Qiang Ye, Harbin Institute of Technology
Kang Zhao, University of Iowa
Leon Zhao, City University of Hong Kong
Web Chair
Harry Wang, University of Delaware
Finance Chair
Alan Wang, Virginia Tech