Connectionists: [CFP] ACM KDD epiDAMIK'19 - International Workshop on Epidemiology meets Data Mining and Knowledge Discovery (Anchorage, Alaska)

[Epidamik Workshop]

** Call for Papers ** for

International Workshop on Epidemiology meets Data Mining and Knowledge
Discovery (epiDAMIK) 2019

Anchorage, Alaska, August 5, 2019.

held in conjunction with the ACM SIGKDD 2019 conference.

URL: http://people.cs.vt.edu/~badityap/epidamik/


***Organizers***
- B. Aditya Prakash, Computer Science, Virginia Tech.
- Anil Vullikanti, Computer Science and Biocomplexity Institute, Univ. of
Virginia
- Shweta Bansal, Biology, Georgetown University
- Adam Sadilek, Google


***Call for Papers***
This 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
epiDAMIK at KDD in London, 2018 was a great success.

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 mining and machine learning perspective.

To reflect the broad scope of work, we encourage submissions that span the
spectrum from theoretical analysis to 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:
- Epidemiologically-relevant data collection
- Advances in modeling, simulation and calibration of disease spread models
- Syndromic surveillance using social media, search and other data sources
- Challenges in model validation against ground truth
- Outbreak detection and inference
- Visualization of epidemiological data
- Planning for public health policy
- Data-driven advances in control and optimization (like immunization)
- Forecasting disease outcomes
- Graph mining and network science approaches to epidemiology
- Crowdsourced methods for detection and forecasting
- Use of novel datasets for prediction and analysis (including EHR records)
- Data mining data for hospital acquired infections like C.Diff, MRSA etc.
- Identifying health behaviors
- Handling missing and noisy data
- Disease forecasting challenge (like the CDC Flu Challenge) experiences

We invite the submission of regular research papers (6-8 pages) as well as
work-in-progress, demo or vision papers (2-4 pages). We also welcome
shorter version of papers already published elsewhere (say in a public
health focused journal). We recommend papers to be formatted according to
the standard double-column ACM Proceedings Style. All papers will be peer
reviewed and single-blinded. Authors whose papers are accepted to the
workshop will have the opportunity to participate in a poster session, and
some set may also be chosen for oral presentation. The accepted papers will
be published online and will not be considered archival.

For paper submission, please proceed to the submission website:
https://easychair.org/conferences/?conf=epidamik2019

Please send any enquiries to epidamik at gmail.com.


****Important Dates****
All deadlines are set at 11:59 PM Pacific Daylight Time.
    - Submission site open: April 10, 2019
    - Workshop paper submissions: May 20, 2019
    - Workshop paper notifications: June 14, 2019
    - Camera-ready papers due: July 1, 2019
    - Workshop date: August 5, 2019
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