Health Day @KDD 2020 - AI for COVID

Key Dates


Covid-19 is a pandemic that has spread over 185 countries. As of this writing on May 1st there are more than 3.3M people confirmed symptomatic. A lot more people are assumed to be exposed and asymptomatic, based on the seroprevalence studies. The disease incubation period ranges from 2 to 14 days and in some cases upto 19 days, and the infectious period on an average is about 8 to 15 days. The disease characteristics range from respiratory to anorexia to digestive. The basic reproduction number Ro i.e. the average number of people infected by one person is documented to range from 2 to 6 according to various studies. All these diverse statistics make it hard to handle this disease. The therapeutic options are also very nascent till a vaccine is discovered. Given these challenging conditions, the data science community has risen to the challenges and seeking to make a difference.

Health Day at KDD is now a premier venue for leaders in AI/ML and Healthcare to discuss major issues facing all aspects of human health; from drug-discovery to epidemiology, from chronic disease management to cost prediction modeling. We invite submission of papers describing innovative research on all aspects of using AI in the fight against COVID. We would also like to see papers in all aspects of the disease including clinical, epidemiological, data driven machine learning and statistical research in developing AI for Covid. Visionary papers on new and emerging areas are also welcome, as are application-oriented papers that make innovative technical contributions for this fight against COVID-19.

All deadlines are at 11:59PM Alofi Time. There will be absolutely no exception to these deadlines.

Topics of interest include, but are not limited to:

Submission Directions

Submissions are limited to a total eight (8) pages max, including all content and references, and must be in PDF format and formatted according to the new Standard ACM Conference Proceedings Template. For LaTeX users: unzip, make, and use sample-sigconf.tex as a template.

Additional information about formatting and style files is available online at: .

Papers that do not meet the formatting requirements will be rejected without review. In addition, authors can provide an optional two (2) page supplement at the end of their submitted paper (it needs to be in the same PDF file and start at page 10) focused on reproducibility. This supplement can only be used to include :

(i) information necessary for reproducing the experimental results, insights, or conclusions reported in the paper (e.g., various algorithmic and model parameters and configurations, hyper-parameter search spaces, details related to dataset filtering and train/test splits, software versions, detailed hardware configuration, etc.), and

(ii) any pseudo-code, or proofs that due to space limitations, could not be included in the main eight-page manuscript, but that help in reproducibility (see reproducibility policy below for more details).

(iii) optionally, authors are encouraged to provide links to their source code such as github etc.

Submitted papers must not include author names and affiliations. If versions of the paper are posted in arXiv or medarXiv (but not accepted in any other peer reviewed venue) it is ok to submit for consideration.

Website for submissions:

Important Policies

SIGKDD Policy on Plagiarism, and Misrepresentation

Papers submitted to SIGKDD cannot be simultaneously under review or consideration in any other venue (or in different tracks of KDD) during the entire SIGKDD review period (i.e., from paper submission to notification dates). This includes conferences, workshops, journals, and any other venues that have published proceedings. The only exception is for papers submitted to ArXiv before the SIGKDD submission deadline.

Papers submitted to SIGKDD must have substantial novelty compared to any previous work, including other works by the same authors. Any overlap (in content, methods, writing, etc.) with prior work must be properly cited or attributed. SIGKDD also takes cases of plagiarism very seriously (including self-plagiarism), as well as author misrepresentation and inclusion of false content.

Details of the full policy and handling of potential violations can be found at:


Submitted papers will be assessed based on their novelty, technical quality, potential impact, insightfulness, depth, clarity, and reproducibility. Authors are strongly encouraged to make their code and data publicly available whenever possible. In addition, authors are strongly encouraged to also report, whenever possible, results for their methods on publicly available datasets. Algorithms and resources used in a paper should be described as completely as possible to allow reproducibility. This includes experimental methodology, empirical evaluations, and results. The authors are encouraged to take advantage of the optional two-page supplement to provide the appropriate information. The reproducibility factor will play an important role in the assessment of each submission.


Every person named as the author of a paper must have contributed substantially both to the work described in the paper and to the writing of the paper. Every listed author must take responsibility for the entire content of a paper. Persons who do not meet these requirements may be acknowledged, but should not be listed as authors. Post-submission changes to the author list are not allowed.

Dual Submissions

No dual submissions are allowed. Submitted papers must describe work that is substantively different from work that has already been published, or accepted for publication, or submitted in parallel to other conferences or journals.

Violations on the dual submission policy may lead to immediate desk rejection and further penalties including prohibition of submitting to conferences and journals sponsored by SIGKDD or/and ACM for a certain period. The employers of the violating authors may be notified. Details of the full policy and handling of potential violations can be found at:

Conflicts of Interest

During the submission process, enter the email domains of all institutions with which you have an institutional conflict of interest. You have an institutional conflict of interest if you are currently employed or have been employed at this institution in the past three years, or you have extensively collaborated with this institution within the past three years. Authors are also required to identify all PC/SPC members with whom they have a conflict of interest, e.g., advisor, student, colleague, or coauthor in the last five years.

Additional information about ACM’s Conflict of Interest policy, which KDD follows, can be found at .

Retraction Policy

KDD follows ACM’s policies, which are described at .

AttendanceFor each accepted paper, at least one author must attend the conference and present the paper. Authors of all accepted papers must prepare a final version for publication, a poster, and a three-minute short video presentation (details will be in the acceptance notification).


Accepted papers will be published in the conference proceedings by ACM and also appear in the ACM Digital Library. The rights retained by authors who transfer copyright to ACM can be found here.

AUTHORS TAKE NOTE: The official publication date is the date the proceedings are made available in the ACM Digital Library. This date for KDD 2020 is on or after July 15, 2020. The official publication date affects the deadline for any patent filings related to published work.

Contact Information


Ankur Teredesai, KenSci Inc. & UW, and Taposh Dutta Roy, Kaiser Permanente

Health Day Chairs of KDD-2020

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