EpiDAMIK 6.0: The 6th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery

Bijaya Adhikari, Alexander Rodríguez, Amulya Yadav, Sen Pei, Ajitesh Srivastava, Marie Laure Charpignon, Anil Vullikanti, B. Aditya Prakash

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The epiDAMIK workshop serves as a platform for advancing the utilization of data-driven methods in the fields of epidemiology and public health research. These fields have seen relatively limited exploration of data-driven approaches compared to other disciplines. Therefore, our primary objective is to foster the growth and recognition of the emerging discipline of data-driven and computational epidemiology, providing a valuable avenue for sharing state-of-the-art research and ongoing projects. The workshop also seeks to showcase results that are not typically presented at major computing conferences, including valuable insights gained from practical experiences. Our target audience encompasses researchers in AI, machine learning, and data science from both academia and industry, who have a keen interest in applying their work to epidemiological and public health contexts. Additionally, we welcome practitioners from mathematical epidemiology and public health, as their expertise and contributions greatly enrich the discussions. Homepage: https://epidamik.github.io/

Original languageEnglish (US)
Title of host publicationKDD 2023 - Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
PublisherAssociation for Computing Machinery
Pages5847-5848
Number of pages2
ISBN (Electronic)9798400701030
DOIs
StatePublished - Aug 6 2023
Event29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2023 - Long Beach, United States
Duration: Aug 6 2023Aug 10 2023

Publication series

NameProceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Conference

Conference29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2023
Country/TerritoryUnited States
CityLong Beach
Period8/6/238/10/23

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems

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