The 2019 INFORMS Workshop on Data Science
Hosted by The INFORMS College on Artificial Intelligence
Seattle, WA, USA
October 19, 2019
The INFORMS Workshop on Data Science is a premier research conference dedicated to developing data science theories, methods, and algorithms to solve challenging problems and 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 welcomes original research addressing challenges in marketing, finance, and supply chain applications and 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 welcomed.
Research Contributions May Include:
- Models for data science and predictive analytics
- Performance measures in data science with important practical implications
- Computational methods for big data, text mining, and natural language processing
- Innovative methods for social network analytics
- Data acquisition, cleaning, integration, and best practices
- Data-driven methods for cybersecurity and data privacy problems
- Prediction of rare events, anomaly detection, and fraud detection
- Methods for induction and inference with missing values
- Data-driven methods for effective risk management
- Data science for healthcare: chronic disease management, preventative care, etc.
- Data science for industrial applications: energy, education, finance, supply chain, e-commerce, etc.
- Large-scale recommendation systems and social media systems
- Visual analytics for business data
- Mobile analytics
- Experiences with big data project deployments
- Deep learning and business applications of AI
Important Dates:
Paper submission Open: April 22, 2019
Paper submission Deadline: July 1, 2019
Notification of Acceptance: August 5, 2019
We look forward to receiving your paper submissions, and to seeing you at the conference!
Information for Authors:
- Maximum of 10 single-spaced pages, printable on 8.5 x 11-inch paper
- 12-point font with one-inch margins on four sides
- Blind submissions
- INFORMS Workshop on Data Science or INFORMS do not take ownership of paper copyrights.
Organizing Committee:
Honorary Chairs
Olivia Sheng, University of Utah
Alexander S. Tuzhilin, New York University
Conference Chairs
Xiaobai (Bob) Li, University of Massachusetts Lowell
Balaji Padmanabhan, University of South Florida
Yong Tan, University of Washington
Program Chairs
Zhepeng (Lionel) Li, York University
Nachiketa Sahoo, Boston University
Kang Zhao, University of Iowa
Publicity Chairs
Shawn Mankad (Cornell University)
Dirk Neumann (University of Freiburg)
Paul Pavlou (Temple University)
Junjie Wu (Beihang University)
Qiang Ye (Harbin Institute of Technology)
Leon Zhao (City University of Hong Kong)
Finance Chair
Alan Wang, Virginia Tech
Webmaster
Kexin Yin, University of Delaware
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Kang Zhao, Ph.D.
Associate Professor
University of Iowa
www.kangzhao.net------------------------------