Call for Papers

The 31st International Conference on Neural Information Processing (ICONIP 2024) is set to be held in Auckland, New Zealand, from December 2nd to December 6th, 2024. ICONIP serves as the annual flagship conference of the Asia Pacific Neural Network Society (APNNS).

Over the past three decades, ICONIP has emerged as a premier venue for showcasing cutting-edge research, technology, and innovations in computational modelling, data analytics, and artificial intelligence.

ICONIP 2024 aims to provide a high-level international forum for scientists, researchers, educators, industrial professionals, and students worldwide to present the state of research and development, address new challenges, and discuss trends in neural information processing theory and applications. These include computational neuroscience, machine learning, bioinformatics, health informatics, computer vision, automation and control, finance, manufacturing, transportation, cybersecurity, and more.

In addition to technical sessions with oral and poster presentations, the conference program will include special sessions, workshops, and tutorials on topics of current interest. It also features plenary/keynote and panel discussion sessions led by the world’s leading researchers and professionals, as well as awards to outstanding papers presented at the conference.

ICONIP employs a competitive paper reviewing process to ensure that only high-quality papers are accepted for publication. Proceedings will be published in the Springer series of Lecture Notes in Computer Science (LNCS) and Communications in Computer and Information Science (CCIS). Accepted papers will typically range from 12 to 15 pages in length.

Instructions on how to submit your paper will be available here soon.

For detailed author instructions including the template from Springer, please visit the link provided here.

Springer

Important dates:

Special Session Proposal Submission Deadline:
15 March 2024 2 April 2024

Workshop Proposal Submission Deadline:
15 March 2024 15 April 2024

Workshop/Special Session Proposal Acceptance:
29 March 2024 29 April 2024

Tutorial Proposal Submission Deadline:
7 June 2024

Competition Solution Submission Deadline:
7 June 2024

Paper Submission Deadline:
7 June 2024

Notification of Acceptance:
26 July 2024

Camera Ready Submission:
30 August 2024

Registration Deadline:
30 August 2024

Conference Dates:
2-6 December 2024

Topics of the conference

ICONIP2024 invites high quality contributions from, but not limited to the topics below:

Track 1: Theory and Algorithms

  • Causality and explainable AI
  • Computational intelligence
  • Control and decision theory
  • Constraint & uncertainty theory
  • Machine learning
  • Neurodynamics
  • Neural network models
  • Optimization
  • Pattern recognition
  • Time series analysis

Track 2: Cognitive Neurosciences

  • Affective and cognitive learning
  • Biometric systems/interfaces
  • Brain-machine interface
  • Computational psychiatry
  • Neuroeconomics
  • Neural data analysis
  • Reasoning and consciousness
  • Sensory perception
  • Social cognition

Track 3: Human Centred Computing

  • Bioinformatics
  • Biomedical information
  • Healthcare
  • Human activity recognition
  • Human-centred design
  • Human-computer interaction
  • Neuromorphic hardware
  • Recommender systems
  • Social networks
  • Sports and rehabilitation

Track 4: Applications

  • Big data analysis
  • Computational finance
  • Image processing & computer vision
  • Data mining
  • Information security
  • Information retrieval
  • Multimedia information processing
  • Natural language processing
  • Robotics and control
  • Web search and mining

Track 5: Special Sessions

  • Advances in Deep Learning for Biometrics and Its Applications
  • AI and Game Production
  • Trends in Swarm Intelligence Optimization Assisted by Machine Learning Techniques
  • Recent Advances in AI-empowered Oceanic Computing
  • Engineering Applications of Hybrid Artificial Intelligence Tools
  • Computational Cognitive Neuroscience
  • Reliable, Robus and Secure Machine Learning Algorithms
  • AI in Environmental, Conservation and Geospatial Applications
  • AI Education
  • Neural Models of Infants and Child Development
  • Computer Vision and Sensor Signal Processing for Enhancing Life Quality and Safety