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

doi:10.1145/3580305.3599220

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

College of Information Sciences and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English (US)
Title of host publication	KDD 2023 - Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Publisher	Association for Computing Machinery
Pages	5847-5848
Number of pages	2
ISBN (Electronic)	9798400701030
DOIs	https://doi.org/10.1145/3580305.3599220
State	Published - Aug 4 2023
Event	29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2023 - Long Beach, United States Duration: Aug 6 2023 → Aug 10 2023

Publication series

Name	Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
ISSN (Print)	2154-817X

Conference

Conference	29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2023
Country/Territory	United States
City	Long Beach
Period	8/6/23 → 8/10/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

Software
Information Systems

Access to Document

10.1145/3580305.3599220

Cite this

Adhikari, B., Rodríguez, A., Yadav, A., Pei, S., Srivastava, A., Charpignon, M. L., Vullikanti, A., & Prakash, B. A. (2023). EpiDAMIK 6.0: The 6th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery. In KDD 2023 - Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 5847-5848). (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining). Association for Computing Machinery. https://doi.org/10.1145/3580305.3599220

Adhikari, Bijaya ; Rodríguez, Alexander ; Yadav, Amulya et al. / EpiDAMIK 6.0 : The 6th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery. KDD 2023 - Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, 2023. pp. 5847-5848 (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

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

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/",

author = "Bijaya Adhikari and Alexander Rodr{\'i}guez and Amulya Yadav and Sen Pei and Ajitesh Srivastava and Charpignon, \{Marie Laure\} and Anil Vullikanti and Prakash, \{B. Aditya\}",

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doi = "10.1145/3580305.3599220",

language = "English (US)",

series = "Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining",

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Adhikari, B, Rodríguez, A, Yadav, A, Pei, S, Srivastava, A, Charpignon, ML, Vullikanti, A & Prakash, BA 2023, EpiDAMIK 6.0: The 6th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery. in KDD 2023 - Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Association for Computing Machinery, pp. 5847-5848, 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2023, Long Beach, United States, 8/6/23. https://doi.org/10.1145/3580305.3599220

EpiDAMIK 6.0: The 6th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery. / Adhikari, Bijaya; Rodríguez, Alexander; Yadav, Amulya et al.
KDD 2023 - Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, 2023. p. 5847-5848 (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - EpiDAMIK 6.0

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AU - Adhikari, Bijaya

AU - Rodríguez, Alexander

AU - Yadav, Amulya

AU - Pei, Sen

AU - Srivastava, Ajitesh

AU - Charpignon, Marie Laure

AU - Vullikanti, Anil

AU - Prakash, B. Aditya

PY - 2023/8/4

Y1 - 2023/8/4

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AB - 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/

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M3 - Conference contribution

AN - SCOPUS:85171355526

T3 - Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

SP - 5847

EP - 5848

BT - KDD 2023 - Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

PB - Association for Computing Machinery

Y2 - 6 August 2023 through 10 August 2023

ER -

Adhikari B, Rodríguez A, Yadav A, Pei S, Srivastava A, Charpignon ML et al. EpiDAMIK 6.0: The 6th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery. In KDD 2023 - Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery. 2023. p. 5847-5848. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining). doi: 10.1145/3580305.3599220

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

Abstract

Publication series

Conference

UN SDGs

All Science Journal Classification (ASJC) codes

Access to Document

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Cite this