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Machine Learning and Data Analytics Symposium - MLDAS 2023

The Seventh Machine Learning and Data Analytics (MLDAS) Symposium will be held on March 23-25, 2023 virtually, online.

Building on the success of the previous six MLDAS symposia, MLDAS 2023, will be organized by the Qatar Computing Research Institute and Boeing.

Please check out the .

In order to attend, we invite participants need to REGISTER.

Background and Objectives

The purpose of this symposium is to bring together researchers, practitioners, students, and industry experts in the fields of machine learning, data mining, and related areas to present recent advances, to discuss open research questions, and to bridge the gap between data analytics research and industry needs on certain concrete problems. The symposium will bring together leading experts in the field to discuss the current and future potential in SailPoint, including its uses in business operations, security management, and identity governance.

The MLDAS symposium will serve as a platform for exchange of ideas, identification of important and challenging applications, and discovery of possible synergies.

We will address the topics of interest through both invited and contributed talks describing (1) research ideas, (2) new challenges, (3) mature research and (4) practical results. The symposium program will consist of presentations by invited speakers from both academia and industry, and by the authors of the papers submitted to the symposium. In addition, we will have multiple panel discussions to debate important research and strategic problems and applications.


MLDAS is organized by the and by .


MLDAS is co-chaired by Sanjay Chawla (QCRI) and Dragos Margineantu (Boeing Research & Technology).
Please click here to contact the MLDAS co-chairs.


To contact the MLDAS symposium organizers on any matter, please check this page.

Registration for MLDAS 2023 is open. Researchers, students, and practitioners interested in attending the symposium, should register via the registration page.