WinDS 2018 : The Second Women in Data Science (WinDS) Workshop
Call For Papers
The Second Women in Data Science (WinDS) Workshop
Submission date: January 15th, 2018
Notification date: February 14th, 2018
Camera Ready: March 4th, 2018
The Second WinDS (Women in Data Science) workshop is a half-day event that will be held on April 24th in Lyon, France in conjunction with The Web Conference (WWW 2018).
This workshop aims to bring together female faculty, graduate students, research scientists and industry researchers for an opportunity to connect, exchange ideas and learn from each other in the field of Data Science. Underrepresented minorities, graduates, and undergraduates interested in pursuing data science, machine learning, and related research are encouraged to participate. While most presenters should be women, everybody is invited to attend.
We strongly encourage female participants --- students, post-docs, early-career and senior researchers --- in all areas of data mining, machine learning, and applications of data science related to health, finance, natural resources, and so on to participate.
Data science is an interdisciplinary field about processes and systems to extract knowledge or insights from data in various forms, either structured or unstructured, which is a continuation of some of the data analysis fields such as statistics, machine learning, data mining, and predictive analytics. Data science encompasses several areas such as data analytics, machine learning, statistics, optimization and big data management.
WinDS will bring together women researchers and practitioners in the field to bring emphasis and discuss the emerging challenges in data science and advanced analytics, including both theoretical and practical perspectives.
General areas of interest to WinDS include but are not limited to:
Big data analytics
Machine learning and knowledge discovery
Big data processing, storage, retrieval, and search
Privacy and security
Applications, practices, tools, and evaluation
The workshop solicits submissions for talks of both previously published and unpublished work. For unpublished work, authors can submit original work, unpublished ideas in the form of completed work or work-in-progress papers of up to 8 pages in length (including references). For previously published work, submitted papers must be no longer than 4 pages in length (including references). We particularly encourage papers that propose new research directions as well as interesting applications of data science.
Papers must be submitted in PDF according to the new ACM format published in ACM guidelines (http://www.acm.org/publications/proceedings-template), selecting the generic “sigconf” sample. Submissions should not exceed 8 pages (4 pages for previously published work) including any diagrams or appendices, and the list of references. The PDF files must have all non-standard fonts embedded. Submissions must be self-contained and in English. Submissions that do not follow these guidelines, or do not view or print properly, may be rejected without review.
Microsoft Word users should convert their document to the PDF format for submission.
All submissions should clearly present the author information including the names of the authors, affiliations and the emails. The main author should be a woman.
Please use the following Easychair link for submission:
Ana Paula Appel
IBM Research - email@example.com
Marisa Affonso Vasconcelos
IBM Research - firstname.lastname@example.org
Boise State University (USA) - email@example.com
Carnegie Mellon University - firstname.lastname@example.org