Call for Tutorials
Call for Tutorials
KDD is the premier Data Science conference. We invite original tutorial contributions in all aspects of the data science lifecycle including but not limited to: data cleaning and preparation, data transformation, mining, inference, learning, explainability, data privacy, and dissemination of results.
Key Dates
Description
Continuing the tradition of bridging the gap between research and real-world applications, we are excited to call for proposals for tutorials at KDD 2022:
A tutorial submission may fall into one of the following categories:
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.
If you need a full day tutorial (6 hours), please indicate this in the submission.
Proposal
We invite proposals from researchers, creators, experienced practitioners and tutors of data mining systems and tools. Each proposal must include the following details:
Submission
Proposals should be submitted to https://cmt3.research.microsoft.com/KDDtutorials2022/ by Tuesday, March 23, 2022.
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: https://www.acm.org/publications/proceedings-template
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:
Attendance
For each accepted tutorial, at least one author must attend the conference and present the tutorial. Authors of all accepted tutorials must prepare a summary to be included in the conference proceedings and deliver the tutorial at the conference.
Copyright
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
Jing Gao, Purdue University
Shenghua Bao, Amazon
Wee Hyong Tok, Microsoft
Contact email: tutorials2022@kdd.org