PAKDD 2021 Workshop on Data Assessment and Readiness for Artificial Intelligence - overview

The goal of this workshop will be to get researchers working in the fields of data acquisition, data labeling, data quality, data preparation and AutoML areas to understand how the data issues, their detection and remediation will help towards building better models. With the focus on different modalities such as structured data, time series data, text data and graph data, this workshop invites researchers from academia and industry to submit novel propositions for systematically identifying and mitigating data issues for making it AI ready. Methods of data assessment can change depending on the modality of the data. This workshop will invite submissions for data readiness for different modalities: structured (or tabular) data, unstructured (such as text) data, graph structured (relational, network) data, time series data, etc. We would like to explore state-of-the-art deep learning and AI concepts such as deep reinforcement learning, graph neural networks, self-supervised learning, capsule networks and adversarial learning to address the problems of data assessment and readiness.


Workshop Organizers (In Alphabetical Order):

  • Bortik Bandyopadhyay, Apple, Data Science (
  • Hima Patel, IBM Research AI (
  • Nitin Gupta, IBM Research AI (
  • Sambaran Bandyopadhyay, IBM Research AI (
  • Sameep Mehta, IBM Research AI (
  • Shashank Mujumdar, IBM Research AI (
  • Srikanta Bedathur, Indian Institute of Technology, Delhi (
  • Srinivasan Parthasarathy, The Ohio State University (