Call for Tutorials

KDD is the premier Data Science conference. We invite original tutorial contributions in all aspects of the data science and machine learning lifecycle, including but not limited to: data cleaning and preparation, data transformation, mining, inference, learning, scalability, explainability, data privacy, and dissemination of results.

Key Dates

  • Submission: March 23rd, 2023
  • Notification: May 1st, 2023
  • Camera-ready proceedings: June 4th, 2023
  • Tutorial materials/website: July 10th, 2023
  • Conference: August 6-10, 2023

All deadlines will be at 11:59 PM Pacific Standard Time.


Continuing the tradition of bridging the gap between research and real-world applications, we are excited to announce a call for proposals for tutorials at KDD 2023.

A tutorial submission may fall into one of the following categories:

  • Lecture-style tutorial
  • Hands-on tutorial

All tutorials will be part of the main conference technical program, and are available free of charge to the attendees of the conference.

Lecture-style tutorial

A lecture-style tutorial will cover the state-of-the-art research, development and applications in a specific data mining related area, and stimulate and facilitate future work.

Tutorials on interdisciplinary directions, bridging scientific research and applied communities, novel and fast growing directions, and significant applications are highly encouraged. We encourage tutorials in areas that may be different from the usual KDD mainstream, but are still very much related to the KDD mission and objectives of gaining insight from data.

Lecture-style tutorials will be 3 hours in duration.

Hands-on tutorial

A hands-on tutorial will feature in-depth hands-on training on cutting edge systems and tools of relevance to the data mining and machine learning community.

These sessions are targeted at novice as well as moderately skilled users. The focus should be on providing hands-on experience to the attendees. The pace of the tutorial should be set such that beginners can follow along comfortably. The tools & systems must have a proven track record of success in the community.

Tutorials should introduce the motivation behind the tool, associated fundamental concepts, and work through examples and demonstrate its application to relatable real-life use cases.

Hands-on tutorials will be 3 hours in duration.


We invite proposals from researchers, creators, experienced practitioners and tutors of data mining systems and tools. Each proposal must include the following details:

  1. A descriptive title
  2. Abstract (300 words)
  3. Target audience and prerequisites for the tutorial (e.g. audience expertise)
  4. Tutors (name, affiliation, email, address, phone)
  5. Tutors’ short bio and expertise related to the tutorial (up to 200 words per tutor)
    1. List of in-person presenters, i.e., tutors who will attend KDD and present part of the tutorial
    2. List of contributors, i.e., tutors who will only help prepare the tutorial material
  6. Corresponding tutor with her/his email address
  7. Tutorial outline. Please provide as much detail as possible.
  8. If the tutorial or a similar/highly related tutorial has been presented before (either by the same author(s) or by others): A list of forums, their event dates and locations, the number of participants, and the similarities/differences of prior tutorials to the one proposed for prior KDDs (up to 100 words for each entry)
  9. A list of up to 30 most important references that will be covered in the tutorial
  10. Strategies that you plan to employ to encourage audience participation and interactivity throughout the tutorial presentation
  11. A brief discussion of the potential societal impacts of your tutorial


Proposals should be submitted to by Tuesday, March 23, 2023.

During submission, select either the Lecture-style Tutorial or Hands-on Tutorial track.

Authors should submit a short summary of the tutorial to be included in the conference proceedings. The summary (maximum 2 pages) should include tutorial title, abstract, and presenters’ biography.

Template guidelines are here:

For tutorial materials/website, the tutorial should be made available as a Github page with the following details: Presenters’ names and bibliography, tutorial outline and what will the participants learn from the tutorial.

See examples from past tutorials:


For each accepted tutorial, we expect all the in-person presenters listed in the tutorial proposal to attend the conference in person and present the tutorial. All the tutorials should be in person, so there must be at least one in-person presenter. Authors of all accepted tutorials must prepare a summary to be included in the conference proceedings and deliver the tutorial at the conference.


The summaries of accepted tutorials 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.

Tutorial Co-Chairs, Lecture Style

Jing Gao, Purdue University

B. Ravindran, IIT Madras

Petko Bogdanov, University at Albany

Contact email:

Tutorial Co-Chairs, Hands-on

Lei Li, UC Santa Barbara

Neil Shah, Snap Research

Huan Sun, The Ohio State University

Contact email: