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KDD 2018 Call for Tutorials

Key Dates

  • Submission: February 23, 2018
  • Notification: April 6, 2018
  • Website due: July 29, 2018
  • (slides, program outline)
  • Conventional Tutorial date: August 19, 2018

Continuing the tradition of bridging the gap between research and application, we are excited to call for proposals in two flavors of tutorials at KDD 2018:

  • Traditional Tutorials
  • Hands-on Tutorials.

A Traditional 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 also encourage tutorials in areas that are somewhat different from the usual KDD mainstream, but still very much related to KDD mission and objectives of gaining insight from data.

A Hands-on Tutorial will feature in-depth hands-on training on cutting edge systems and tools of relevance to 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 themselves must be available under open-source licenses (e.g. Apache 2.0, MIT, BSD etc.) and have 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

All tutorials will be part of the main conference technical program, and are available free of charge to the attendees of the conference. Traditional tutorials will be of 3 hours in duration while Hands-on tutorials can be either 3 hours or 6 hours long.


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

  1. A Descriptive Title
  2. Abstract (300 words)
  3. Target audience and prerequisite for the tutorial (e.g. audience expertise)
  4. Tutors (name, affiliation, email, address, phone)
  5. Tutors’ short bio and their expertise related to the tutorial (up to 200 words per tutor)
  6. Corresponding author with her/his email address
  7. Tutorial outline. Provide as much detail as possible.
  8. A list of forums and their time and locations if the tutorial or a similar/highly related tutorial has been presented by the same author(s) before, and highlight the similarity/difference between those and the one proposed for KDD’18 (up to 100 words for each entry)
  9. A list of the most important references that will be covered in the tutorial
  10. Equipment you will bring (e.g. laptop, projector)
  11. Equipment you will need (e.g. table, poster board, power sockets)
  12. Equipment attendees should bring (e.g. laptop)
  13. Hands-on-Tutorial: Tutorial duration – 3 hours OR 6 hours
  14. Hands-on Tutorial: Operating system and required installed tools on attendees’ devices.
  15. Hands-on Tutorial: List of software licenses required for the tools.
  16. Hands-on Tutorial: Setup instructions for attendees. (Should not take more than 1 hour to complete it)
  17. Selected tutorial must provide slides and related materials for tutorial website by the “Slides due” date below.
  18. Optional: Video snippet of you teaching a tutorial or giving a talk.

Proposals should be received by Friday, Feb 23, 2018. Please submit proposals for traditional tutorials to and for hands-on tutorials to


KDD 2017 Traditional Tutorials:
KDD 2017 Hands-On Tutorials:


Leman Akoglu (Carnegie Mellon University)
Ian Davidson (University of California Davis)
Contact email:


Ritwik Kumar (Netflix)
Lei Li (Bytedance)
Contact email:

Save the Date

KDD 2018 - London, United Kingdom. 19 - 23 August 2018

The annual KDD conference is the premier interdisciplinary conference bringing together researchers and practitioners from data science, data mining, knowledge discovery, large-scale data analytics, and big data.

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