Scope of the workshop

Multimodal Data Analysis (MDA) is an emerging field of research that aim to address this challenge. It focuses on the integration and analysis of data from multiple sources and modalities to provide a more comprehensive understanding of the data. This can provide more accurate and detailed analysis and insights of data, as well as support better decision-making. Multimodal data analysis has many important applications both in academia and industry, such as education, health care, entertainment, social media, recommender systems, and sentiment analysis. However, multimodal data analysis also many research challenges that require novel and innovative solutions such as (1) collecting, preprocessing, transforming, and merging multimodal data that may be heterogeneous noisy and uncertain, (2) how to combine different aspects of information that can complement, contradict, be untrustworthy or amgiguous, (3) how to leverage the rich information from multimodal data to design better machine learning models and data analysis techniques for tasks such as retrieval, recommendation, and reasoning, (4) and how to evaluate multimodal models and methods.

The major goal of the MDA workshop is to bring together researchers who currently contribute to different aspects of multimodal data analysis to identify new research directions and innovative applications that could generate profound impact on the machine learning and data science community. This workshop will focus on real world experiences, inherent challenges, as well as new research methods/applications.

The Workshop on Mult-modal Data Analysis (MDA 2023) will discuss a broad variety of topics related to multimodal data analysis, including but not limited to:

  • Anomaly detection in multimodal data
  • Deep learning for multimodal
  • Multimodal neural network architectures
  • Few-shot learning, unsupervised and semi-supervised learning for multimodal data
  • Reinforcement learning, transfer learning and representation learning for multimodal data
  • Multimodal data classification
  • Multimodal data clustering
  • Multimodal generative models
  • Multimodal natural language processing
  • Multimodal data visualization
  • Multimodal sentiment analysis
  • Emerging multimodal applications in industry and academia such as finance, medicine and education

The MDA 2023 workshop will be held on December 4, 2023 at part of the IEEE ICDM 2023 conference.

All accepted papers will be published in the IEEE ICDM 2023 Workshop proceedings (published by IEEE and EI-indexed)

Moreover, a special issue will be planned (to be confirmed).

A best paper award will be awarded.

For any questions, please contact the organizing committee.

Important dates

  • Paper submission deadline: September 3, 2023
  • Paper notifications: September 24, 2023
  • Camera-ready deadline and copyright forms: October 1, 2023
  • Workshop date: December 4, 2023
  • **All times are at 11:59PM Beijing Time**


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