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


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