Organised by I-CAIR Research Group, School of Computer Engineering, KIIT University, Bhubaneswar, India
The rapid progress in machine learning and neuroscience has facilitated significant breakthroughs in the field of Brain-Computer Interfaces (BCI). The objective of this workshop is to equip participants with a thorough comprehension of incorporating machine learning methods into BCI applications. It seeks to create a dynamic learning atmosphere that combines theoretical knowledge with practical implementation. The theme "ABC with ML" invites participants to explore and create, with the goal of transforming the way we live, work, and interact with the world by fostering collaboration between human intellect and artificial intelligence. This workshop is designed for researchers, engineers, students, and professionals interested in the intersection of machine learning and brain-computer interfaces. Participants should have a basic understanding of machine learning concepts and a keen interest in exploring the possibilities of BCI technology. By integrating these additional elements into the workshop structure, we aim to create a dynamic and immersive learning experience that goes beyond traditional lecture formats, allowing participants to engage actively, build meaningful connections, and leave with practical skills they can apply in their research and professional endeavors
The workshop will also include:
two keynote speeches given by a renowned researcher on the topic of the Application of Machine Learning in Brain-Computer Interface
Birds-of-a-feather discussions, in groups aligned with the workshop themes
Poster/Work-in-progress papers
Best Paper: All the regular papers will be considered for the BEST PAPER AWARD.
Workshop Proposal Accepted: 7th May 2024
Website Launch: 30th May 2024
Paper submission opens: 1st June 2024
Paper submission closes: 15th September 2024
Notifications for Acceptance or Rejection: : 30th October, 2024
Camera Ready Paper Submission opens: 30th November
Workshop date: 1st December, 2024
