We invite proposals for half-day (3-4 hours) or full-day (5-8 hours) tutorials from active researchers in both academia and industry who are experienced and engaging presenters. Ideally, a tutorial will cover the state-of-the-art research, development, and applications in a specific data mining domain, to stimulate and facilitate future work. Tutorials on interdisciplinary areas, novel and fast growing directions, and significant applications are highly encouraged.
Important Dates
- Proposal due:
February 20, 2023March 6, 2023 - Tutorial notification:
April 5, 2023April 12, 2023 - Submission of tutorial notes:
April 27, 2023May 4, 2023
*All deadlines are 23:59 Pacific Standard Time (PST)
Proposal
A tutorial proposal should include the following and should not exceed 5 pages excluding references:
- Title
- Abstract
- Tutorial Outline
- Presenters’ name, affiliation, address, email, phone
- A biographical sketch of the presenter(s)
- References
Outline including a short summary of every section
- Background
- Specific goals and objectives
- Expected background of the audience
- Audio Visual equipment needed for the presentation
A list of up to 20 most important references that will be covered in the tutorial.
Paper Submission
Please submit your proposals in PDF format to the link below:
Tutorial Proposal Online Submission Link
Proposals will be evaluated by the tutorial co-chairs based on merit and relevance. The tutorial presenters will be required to provide comprehensive tutorial notes prior to the event, which will be published on the PAKDD website. Tutorials are expected to be scheduled on the day before the main PAKDD conference, May 25, 2023. Tutorials will be held entirely online. All presenters named in the proposal MUST attend online to present the tutorial; otherwise, the tutorial may be canceled. For each accepted tutorial proposal, the PAKDD organizing committee will provide support for attendance in the form of ONE full registration to the conference.
Contact Information
Tutorial Co-Chairs of PAKDD2023
Koji Maruhashi, Bin Cui
pakdd2023@gmail.com