-------- Weitergeleitete Nachricht -------- Betreff: [AISWorld] CFP - Informs Workshop on Data Science (DS2017) Datum: Thu, 18 May 2017 15:29:55 +0000 Von: Zheng, Zhiqiang ericz@utdallas.edu An: 'aisworld@lists.aisnet.org' aisworld@lists.aisnet.org

You are cordially invited to submit a paper to the first Informs Workshop on Data Science (DS2017) http://meetings2.informs.org/wordpress/houston2017/conference-on-data-scienc....

The deadline for submission is June 20, 2017, one month away. DS2017 is a pre-conference of the annual INFORMS meeting and is to be held on October 21, 2017 in Houston, Texas. The CFP is available at http://2017.dsconf.org/wp-content/uploads/sites/18/2017/01/INFORMS-Workshop-....

The Informs Workshop 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 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 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 scien ce, 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, ecommerce, 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 at 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

Best Regards,

Eric Zheng

Professor of Information Systems

Jindal School of Management

University of Texas at Dallas

Richardson, TX 75080

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