KDD’24: Call for Applied Data Science (ADS) Track Papers

Important Dates:


Scope: Deployed Applications of Data Science

The KDD’24 Applied Data Science (ADS) track chairs solicit submissions of papers describing designs and implementations of solutions and systems for practical applications in data mining, data analytics, data science, and applied machine learning. The primary emphasis is on papers that either solve or advance the understanding of issues related to deploying data science technologies in the real world. Papers demonstrating significant, verifiable business or real-world impact as a result of such deployments are encouraged. 

Papers should present the problem, its significance to the application domain, the decisions and tradeoffs made when making design choices for the solution, how any challenges in areas like data collection, modeling, and deployment in constrained environments were overcome, and the lessons learned from successes and failures. It is perfectly fine if the underlying machine learning algorithms are not fundamentally groundbreaking. Evidence must be provided that the solution has been deployed by quantifying post-launch performance. 

Papers describing deployed real world applications should be aimed at a broad audience of applied data scientists. Application areas include, but are not limited to the following:

An exception to the deployed production systems requirement may be made for papers describing systems to solve real-world problems that could not be successfully deployed in production for very compelling reasons. These papers will need to explain the attempts that were made to deploy the system in production and what lessons were learned from the failures that would be broadly applicable and serve as critical learnings for future systems in the same or related domains.

Besides common requirements such as impact, clarity of presentation, reproducibility, we encourage that submissions specify an audience or a group of users that have benefited or will benefit from the solution presented in the submission. In particular, the focus of novelty for an ADS submission is different from that of a Research Track submission in the sense that we focus more on application novelty, engineering novelty, usability, business use case and user experience novelty, and whether the work provides significant gains in the applied domain. Note that papers that do not satisfy the requirements (e.g., a research paper, a paper describing an algorithm or system tested solely on academic benchmark data) might be rejected without a formal review.

Submission Guideline


The ACM has an authorship policy stating who can be considered an author in a submission as well as the use of generative AI tools. Please note the disclosure requirements as they will be strictly enforced. Every person named as the author of a paper must have contributed substantially to the work described in the paper and/or to the writing of the paper and 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. 


The review process will be single-blind — author names and affiliations should be listed.

Submissions Site

We will use OpenReview to manage the abstract and paper submissions and reviewing. All listed authors must have an up-to-date OpenReview profile, properly attributed with current and past institutional affiliation, homepage, Google Scholar, DBLP, ORCID, LinkedIn, Semantic Scholar (wherever applicable). Here is information on how to create an OpenReview profile. The OpenReview profile will be used to handle conflict of interest and paper matching. Submissions will not be made public on OpenReview during the reviewing period.

Concurrent Submissions

Submitted papers must describe work that is substantively different from work that has already been published, or accepted for publication in an archival venue. KDD submissions must not be in concurrent submission to any archival conference or journal during the KDD review period. Papers can be submitted to arXiv with the same title and abstract during the review process.


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 during the review process, unless there is an inevitable reason that they cannot be released (e.g., proprietary data from a specific company or medical data where there is no public alternative). Algorithms and resources used in a paper should be described as completely as possible to allow reproducibility; this includes model parameters, experimental methodology, empirical evaluations, and results. The reproducibility factor will play an important role in the assessment of each submission. In the case where data cannot be released, authors are encouraged to include experiments on relevant public datasets and/or create simulated data with the same properties.

Formatting Requirements

ADS track submissions are limited to 8 pages (excluding references), must be in PDF, and use ACM Conference Proceeding template (two column format).

\documentclass[sigconf, review]{acmart}

Additional supplemental material focused on reproducibility can be provided. Proofs, pseudo-code, and code may also be included in the supplement, which has no explicit page limit. As in previous years, the supplementary material should be included in the same pdf file with the main manuscript. The main body of the paper should be self-contained, since reviewers are not required to read the supplementary material. The supplementary material will not be included in the proceedings.

Submissions violating these formatting requirements will be rejected without review.

Review Process

Review Contribution

All authors will be required to register as reviewers for KDD. Not all authors will be requested to provide reviews, but if an author is requested to provide up to three timely and good quality reviews for KDD and declines to do so when requested, their submission will be rejected.


Each submission will receive at least three independent reviews, overseen by an Area Chair (AC). At least one author per submission should commit to be a reviewer and submit all their reviews on time.  If an author of a submission does not submit all the reviews in time for the rebuttal stage, no author of that submission will see the reviews of that submission during the rebuttal stage. 


Authors will have the chance to provide a response to the reviews during an author-reviewer discussion period. The ACs will consider the authors’ responses to the points raised by the reviewers to inform acceptance decisions.


A range of factors including technical merit, originality, potential impact, quality of execution, quality of presentation, related work, reproducibility of results, and ethics, will be used by the ACs to make a recommendation. The PC Chairs will make the final decisions.


By submitting paper(s) to KDD 2024, the authors agree that the reviews, meta-reviews, and discussions will be made public in OpenReview for all accepted papers.

Conflict of Interest (COI) Policy

All authors and reviewers must declare conflicts of interest in OpenReview. A domain conflict (entered in Education & Career History) must be declared for employment at the same institution or company, regardless of geography/location, currently or in the last 12 months. A personal conflict should be declared when the following associations exist:

In general, we expect authors, PC, the organizing committee, and other volunteers to adhere to ACM’s Conflict of Interest Policy as well as the ACM’s Code of Ethics and Professional Conduct.

Publication and Presentation Policies


All accepted papers will be allowed the same maximum page length in the proceedings (12 pages, of which 9 are content pages). That is, only 3 pages for the References and Appendix are allowed for all accepted papers. Note that a bonus additional page of content is allowed for accepted papers (i.e., 9 pages compared to the 8 pages when initially submitting for review). Accepted papers will be published by ACM and will be accessible via the ACM Digital Library. Accepted papers will require a further revision to meet the requirements of the camera-ready format required by ACM. Camera-ready versions of accepted papers can and should include all information to identify authors, and should acknowledge any funding received that directly supported the presented research. The rights retained by authors who transfer copyright to ACM can be found here.


To be included in the proceedings, every accepted paper must be covered by a distinct conference registration, e.g., two multi-authored papers require two registrations, even if they have overlapping authors. This registration must be Full Conference (5-day) or Main Conference (3-day) registration, at the standard (non-student) in-person rate, payment of which must be completed by the camera-ready deadline. This registration requirement applies universally, regardless of attendance or presentation mode.


Every accepted paper must be presented at the conference. A no-show at the conference may result in the paper being withdrawn from the proceedings. 

Official Publication Date

The official publication date is the date the proceedings are made available in the ACM Digital Library. This date for KDD 2024 is on or after August 25, 2024. The official publication date affects the deadline for any patent filings related to published work.

Contact Information

Email: KDD24-ads-chairs@acm.org

Claudia Perlich (TwoSigma, New York, NY)
Rajesh Parekh (Google, Mountain View, CA)
Shipeng Yu (LinkedIn, Mountain View, CA)

ADS Track PC co-Chairs of KDD’24

KDD 2025

Going forward, KDD will have multiple submission deadlines per year.  KDD 2025 will have two deadlines, one on August 8, 2024 and another on February 8, 2025 (with abstract deadlines a week before the full paper submission deadlines).  More details will be posted soon. Email: KDD25-ads-chairs@acm.org