The epiDAMIK @ SIGKDD 2022 workshop is a forum to discuss new insights into how data mining can play a bigger role in epidemiology and public health research. While the integration of data science methods into epidemiology has significant potential, it remains under studied. We aim to raise the profile of this emerging research area of data-driven and computational epidemiology, and create a venue for presenting state-of-the-art and in-progress results—in particular, results that would otherwise be difficult to present at a major data mining conference, including lessons learnt in the ‘trenches’. The current COVID-19 pandemic has only showcased the urgency and importance of this area.
Our target audience consists of data mining and machine learning researchers from both academia and industry who are interested in epidemiological and public-health applications of their work. Additionally, we are aiming to attract researchers and practitioners from the areas of mathematical epidemiology and public health, who are increasingly dealing with more complex models and novel data sources––these problems bring up novel challenges from a data science and machine learning perspective.
The past iterations of the workshop were co-located with SIGKDD 2018, SIGKDD 2019 (also part of ‘health days’), SIGKDD 2020, and SIGKDD 2021. These were a great success with insightful contributed works as well as high-quality keynotes.
To reflect the broad scope of work, we encourage submissions that span the spectrum from theoretical analysis, algorithms and implementation, to applications and empirical studies, from both data mining and public health viewpoints.
Topics of interest include, but are not limited to:
We invite the submission of full regular research papers (6-8 pages) as well as short, work-in-progress, demo or position papers (2-4 pages). Short summary versions of recently published major papers (2-4 pages) are also welcome.
We recommend papers to be formatted according to the standard double-column ACM Proceedings Style. All papers will be peer reviewed and single-blinded, thus, they should contain the name of authors and their affiliations. Authors whose papers are accepted to the workshop will have the opportunity to participate in a poster session, and some may also be chosen for oral presentation. There are no restrictions on already submitted work or authors simultaneously posting their manuscripts to any pre-print server. The accepted papers will be made available online but will not be considered archival. Therefore, authors are free to resubmit the paper to pre-print servers and future conferences and journals.
For paper submission, please proceed to the submission website.