VLDB 2023: Call for Contributions - Tutorials

VLDB 2023 invites submissions for tutorial proposals on all topics of potential interest to the conference attendees. Tutorial proposals should cover state-of-the-art research, development, and applications in specific data management related areas, 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 VLDB mainstream, but still very much related to VLDB mission and objectives of managing big data. We also encourage tutorials that apply advanced Machine Learning techniques to solve data management problems, and will be directly inviting a small number of tutorials from neighboring scientific communities. Tutorials should be targeted for a broad audience, and they must focus either excessively, nor exclusively, on the authors’ own work.

VLDB 2023 welcomes two types of tutorials. Lecture-style tutorials will be typically 1.5 hours in duration, while hands-on tutorials can be either 1.5 hours or 3 hours long.

Important Dates (All deadlines below are 5pm PT.)

Submission Guidelines

Tutorial submissions must be submitted electronically using CMT. Submissions should be formatted using the PVLDB style templates, with a maximum length of 4 pages, inclusive of ALL material.

Proposals should include:

Accepted Tutorials

A four-page extended abstract, with an overview including bibliographic references, will appear in PVLDB's VLDB 2023 issue. The camera-ready format version should be an updated version of the original submission that addresses suggestions from the tutorial chairs and possibly other reviewers.

Authors must agree to standard PVLDB copyright releases for the tutorial abstract overview as well as for their slides. Authors will retain the rights to reuse all their material in any form.

If the proposal is accepted, at least one of the authors listed in the proposal is expected to attend VLDB 2023 and present the tutorial.

Tutorial Chairs

Senjuti Basu Roy, New Jersey Institute of Technology
Steven E Whang, KAIST

Tutorial PC Members

Chao Zhang, Tsinghua University
Chenhao Ma, Chinese University of Hong Kong
Chuan Xiao, Osaka University and Nagoya University
Jayant Haritsa, Indian Institute of Science
Jelle Hellings, McMaster University
Jianbin Qin, Shenzhen University
Karima Echihabi, Mohammed VI Polytechnic University
Mareike Schmidt, Universität Hamburg
Ramon Antonio Rodriges Zalipynis, HSE University
Simon Razniewski, Bosch Center for AI
Suyash Gupta, UC Berkeley
Wasay Abdul, Intel Labs
Wei Wang, Hong Kong University of Science and Technology (Guangzhou)
Xiaolan Wang, Meta AI
Zoi Kaoudi, TU Berlin