Call for Submissions
Call for Papers
The International Conference on Machine Intelligence and Nature-inspireD Computing (MIND) solicits original submissions that present innovative research and development outcomes in the fields of Machine Intelligence and Nature-inspired Computing.
Submission guidance:
• Submission portal: TBD
[Acknowledgment]: The Microsoft CMT service was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.
• Submission of papers include LONG papers (up to 6 pages), SHORT papers (up to 2 pages), and ABSTRACT (up to 1 page), including all text, figures, and references. LONG and SHORT papers will be peer-reviewed and published in the conference proceedings if accepted and registered. The proceedings will be indexed by IEEE XPLORE.
• ABSTRACT will only be reviewed by the Program Chair and will not be presented at the conference. A soft-copy collection of ABSTRACTS will be made available.
• Formatting guidelines and templates are available on: https://www.ieee.org/conferences/publishing/templates.html
• Supplementary material (e.g., appendices, data, source code, resubmission information) can optionally be submitted by the paper submission deadline.
• Generative AI models, including ChatGPT, LLaMA, DeepSeek, or similar LLMs, do not satisfy the criteria for authorship of papers published in MIND 2026. If authors use LLMs in any part of the paper-writing process, they assume full responsibility for all content, including checking for plagiarism and correctness of the entire submission.
• All submissions will be thoroughly reviewed by experts in the fields, and accepted papers will be presented at the conference and included in the proceedings.
Topics of interest include (but not limited to) the following tracks:
Brain-inspired Computing
  • Brain-inspired Models and Learning Algorithms
  • Brain-Computer Interfaces
  • Neuromorphic Hardware
  • Neuromorphic Datasets and Software Frameworks
Embodied AI and Robotics
  • Agents and Multi-Agent Systems
  • Embodied AI
  • Robotic Learning
  • Robotic Systems
Deep Learning and Large Foundation Models
  • Artificial Neural Networks
  • Explainable AI and Ethics
  • Foundation Models
  • Generative AI
  • Machine Learning
Nature-inspired Intelligence
  • Evolutionary Algorithms
  • Evolutionary Multi-objective Optimization
  • Evolutionary Transfer Optimization
  • Fuzzy Logic and Systems
  • Swarm Intelligence
Machine Intelligence Applications
  • Applications of Generative AI
  • Autonomous Driving
  • Financial Technology
  • Healthcare and Biomedical
  • Industrial applications
  • Intelligent Manufacturing
  • Logistics and Supply Chain Management
  • Smart Cities and IoT