Saturday, October 15
Sponsored by
The 6th INFORMS Workshop on Data Science (DS 2022) will take place on Saturday, October 15 in conjunction with the INFORMS Annual Meeting in Indianapolis. The INFORMS Workshop on Data Science is hosted by the INFORMS College on Artificial Intelligence and is a premier research conference dedicated to developing data science theories, methods, and algorithms to solve challenging problems and benefit businesses 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, deep learning, reinforcement learning, network science, and artificial intelligence.
For topics of interest, important dates and the call for papers, please go to: INFORMS Workshop on Data Science 2022
Information for Authors
- Conference submission website: https://cmt3.research.microsoft.com/DS2022
- Submissions in the form of complete papers or short papers are welcome.
- Complete paper submissions should be a maximum of 10 pages, including tables and figures. Only complete papers are eligible for the editorial feedback roundtables (more details are provided below).
- Short paper submissions (which could be extended abstracts or work-in-progress papers) should be a maximum of 5 pages, including tables and figures.
- References (irrespective of complete paper or short paper submissions) do not count towards the page limit.
- Use single-spaced text with 12-point font and one-inch margins on four sides, printable on 8.5 x 11-inch paper.
- Submissions must be blinded. No author information should appear anywhere in the document.
- INFORMS or Workshop on Data Science does not take ownership of paper copyrights.
- When uploading papers to the submission portal, the authors can indicate 1) whether or not to participate in the editorial feedback roundtables (described below) once their paper has been accepted, and 2) whether or not the paper’s main contributor is a student (so as to be considered for the best student paper award).
Best Paper Awards
The INFORMS College on Artificial Intelligence, which hosts the Workshop on Data Science, will be sponsoring three categories of awards: the best complete paper, the best short paper, and the best student paper.
Editorial Feedback Roundtables
The goal of the editorial feedback roundtables is to pair author teams of accepted complete papers with a Senior Editor or Associate Editor from premier journals, such as MIS Quarterly, Information Systems Research, and Management Science, to identify strategies on how the authors could potentially position and/or extend their accepted workshop paper for journal submission. Note that these editorial feedback roundtables are not a fast-track submission process but rather an opportunity to seek feedback.
Workshop Registration
Students
$50
Non-students
$100
All DS 2022 participants are required to register for the 2022 INFORMS Annual Meeting in Indianapolis. The registration fees for this workshop does NOT include the registration fee for the INFORMS Annual Meeting. View Annual Meeting Registration.
Organizing Committee
Honorary Chairs
Olivia Sheng, University of Utah
Alexander S. Tuzhilin, New York University
Conference Chairs
Yong Ge, University of Arizona, yongge@arizona.edu
Gene Moo Lee, University of British Columbia, gene.lee@sauder.ubc.ca
Jingjing Zhang, Indiana University, jjzhang@indiana.edu
Program Chairs
Jingjing Li, University of Virginia, jl9rf@virginia.edu
Xiao Liu, Arizona State University, xiao.liu.10@asu.edu
Sagar Samtani, Indiana University, ssamtani@iu.edu
Publicity Chairs
Konstantin Bauman, Temple University, tuh42084@temple.edu
Dokyun (DK) Lee, Boston University, dokyun@bu.edu
Sung-Hyuk Park, KAIST, park@kaist.ac.kr
Konstantina Valogianni, IE Business School, valogianni@ie.edu
Junjie Wu, Beihang University, wujj@buaa.edu.cn
Finance Chair
Brent Kitchens, University of Virginia, bmk2a@comm.virginia.edu
Webmaster
Myunghwan Lee, University of British Columbia, myunghwan.lee@sauder.ubc.ca
Recent Past Data Science Workshops
