Machine Learning and Data Analytics Symposium - MLDAS 2022
The Eighth Machine Learning and Data Analytics (MLDAS) Symposium will be held on October 17-18, 2022 in Cambridge, Massachusetts at the Boeing Aerospace and Autonomy Center on the MIT Campus.
Building on the success of the previous seven MLDAS symposia, MLDAS 2022, will be organized by Boeing and the Qatar Computing Research Institute.
Registration is open for both: in-person and virtual attending of MLDAS.
In order to attend, we invite participants to REGISTER HERE.
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 MLDAS symposium will serve as a platform for exchange of ideas, identification of important and challenging applications, and discovery of possible synergies.
The central topics of MLDAS 2022 will be Robust Learned Models and AI Systems, AI Methods for Design, and Machine Learning for Soccer.
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.
The MLDAS symposium will take place on October 17 and 18, 2022.
MLDAS is co-chaired by Sanjay Chawla (QCRI) and Dragos Margineantu (Boeing Research & Technology).
To contact the MLDAS symposium organizers on any matter, please check this page.Registration for MLDAS 2022 will open on August 31, 2022. Researchers, students, and practitioners interested in attending the symposium, should register via the registration page.
|MLDAS 2022 - mldas.org|