INFORMS Conference on Data Science
October 21, 2017. Houston, Texas
Website: 2017.dsconf.org
INFORMS Conference on Data Science is a premier research conference dedicated to developing novel data science theories, algorithms, and methods to solve challenging and practical problems that benefit business and society at large. The conference 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 conference invites original research addressing challenges ranging from marketing and finance problems to problems in health care, energy, cybersecurity, fraud detection, social network services, talent analytics, privacy, credibility, etc. Contributions on novel methods may be motivated by insightful observations on the shortcomings of state-of-the art data science methods in addressing practical challenges, or may propose 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.
Research contributions may include:
. Novel predictive modeling approaches
. Novel performance measures of data science methods that account for important practical implications
. Data science methods for health care: chronic disease management, preventative care, etc.
. Prediction of rare events and anomaly detection
. Methods for induction and inference with missing values
. Data science for industrial applications: energy, education, finance, supply chain, e-commerce, etc.
. Data-driven methods for effective risk management
. Data-driven methods for cyber security
. Data acquisition, integration, cleaning, and best practices
. Visualization analytics for business data
. Novel methods for social network analysis
. Mobile analytics
. Large-scale recommendation systems and social media systems
. Novel methods for text analytics and natural language processing
. Experiences with big data project deployments
. Deep learning and AI business applications
Important Dates:
Paper submission Open: April 10th, 2017
Paper submission Deadline: June 20th, 2017
Notification of Acceptance: August 20th, 2017
We look forward to receiving your paper submissions, and to seeing you at the conference!
Information to authors:
. Maximum of 15 pages (excluding abstract, references, tables and figures), printable on 8.5 x 11-inch paper
. 12-point font with one-inch margins on four sides
. Double-spaced
. Indicate on the front cover whether the bulk of the work was done by a student
. Blind submissions are encouraged but not required
Organizing Committee:
Honorary Chairs
Olivia Sheng, University of Utah
Alexander S. Tuzhilin, New York University
Conference Chairs
Xiao Fang, University of Delaware
Hui Xiong, Rutgers University
Zhiqiang (Eric) Zheng, University of Texas, Dallas
Program Chairs
Ahmed Abbasi, University of Virginia
Weiguo (Patrick) Fan, Virginia Tech
Maytal Saar-Tsechansky, University of Texas, Austin
Publicity Chairs
Leman Akoglu, Carnegie Mellon University
Shawn Mankad, Cornell University
Paul Pavlou, Temple University
Nachiketa Sahoo, Boston University
Qiang Ye, Harbin Institute of Technology, China
Kang Zhao, University of Iowa
Web Chair
Harry Wang, University of Delaware
Finance Chair
Alan Wang, Virginia Tech
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Kang Zhao
Assistant Professor
University of Iowa
www.kangzhao.net------------------------------