14th Joint Symposium on Computational Intelligence (JSCI14)

The Joint Symposium on Computational Intelligence (JSCI) is an event that was first organized in 2016. The event was initiated by the IEEE Computational Intelligence Society Thailand Chapter (IEEE-CIS Thailand Chapter), which aims to support research students and young researchers to create a place that enables participants to share and discuss their research before publishing their works. The event is open to all researchers who want to broaden their knowledge of computational intelligence. The symposium will feature student paper presentations as well as invited talks.

JSCI is a rehearsal platform for students who want to extend their work to present and publish at Scopus conference proceedings or submit for Scopus-Indexed Journals. JSCI is a stage for undergraduate and graduate students to practice their research work under the supervision of professors in the community. It is an activity organized by the IEEE Computational Intelligence Society Thailand Chapter. Students who participated in this event will gain some experience in both the presentation and written academic papers for conferences and journals.

This is a very good opportunity to share and discuss your work with other researchers in computational intelligence. If you are interested in presenting your work at this symposium, please submit a paper at https://easychair.org/conferences/?conf=jsci14. The paper must conform to the standard of IEEE Manuscript Templates for Conference Proceedings, which is available to download at https://www.ieee.org/conferences/publishing/templates.html or https://www.overleaf.com/latex/templates/ieee-conference-template/grfzhhncsfqn. A 4-6-page paper must be submitted to be reviewed. The papers will be double-blind peer-reviewed (please do not include authors’ names for the first-round submission).

Areas of Interest:

Our focus areas encompass a wide spectrum of cutting-edge topics in the field of computational intelligence. These include:

• Neural Networks: Research into the development and application of neural networks, exploring their various architectures and functionalities.
• Connectionist Systems: Investigations into connectionist systems, examining their role in modeling and simulating complex cognitive processes.
• Fuzzy Systems: Studies related to fuzzy systems emphasizing their use in decision-making and uncertainty management.
• Hybrid Intelligent Systems: The intersection of various intelligent systems, exploring the synergistic benefits of combining different approaches.
• Evolutionary Computation: Research in nature-inspired optimization techniques, such as genetic algorithms, particle swarm optimization, firefly algorithm, and more.

We welcome contributions in the following subdomains within computational intelligence, with a particular emphasis on their theory, design, application, and development:

• Explainable AI (XAI): An increasingly prominent area of research focusing on methods and techniques to make AI systems more interpretable and transparent. Subtopics include:
  • Model-specific XAI Techniques: Approaches tailored to specific AI models.
  • Model-agnostic XAI Techniques: Techniques applicable across different AI models.
  • Evaluation Metrics for XAI: Metrics for assessing the effectiveness of XAI methods.
  • Visualizing AI Model Decisions: Methods for visually representing AI model outputs.
  • Rule-based Explanations: Systems that provide explanations based on predefined rules.
  • Natural Language Explanations: Techniques enabling AI systems to explain their decisions in human-readable language.
  • Ethical Considerations in XAI: Discussions on the ethical implications of XAI.
  • XAI in Healthcare: Applications of XAI in the healthcare domain.
  • XAI in Finance: Implementations of XAI in financial systems and decision-making.
  • XAI in Autonomous Systems: The use of XAI in autonomous vehicles and other systems.
  • Human-AI Interaction with XAI: Exploring how users interact with XAI systems.
  • Trust and Adoption of XAI: Research on building trust and increasing the adoption of XAI.
  • XAI for Deep Learning: Specific considerations and techniques for XAI in deep learning models.

Important Dates

• Paper submission deadline: September 23, 2023
• Author notification: September 30, 2023
• Camera-ready copies: October 7, 2023
• Presenter Registration: October 7, 2023
• Symposium dates: October 26 (Hybrid)

Organizing Committee

Advisory

• Chanboon Sathitwiriyawong (King Mongkut’s Institute of Technology Ladkrabang)
• Jonathan H. Chan (King Mongkut’s University of Technology Thonburi)
• Phayung Meesad (King Mongkut’s University of Technology North Bangkok)

General Chair

• Kuntpong Woraratpanya (King Mongkut’s Institute of Technology Ladkrabang)

Organizing Committee

• Kitsuchart Pasupa (King Mongkut’s Institute of Technology Ladkrabang)
• Maleerat Maliyaem (King Mongkut’s University of Technology North Bangkok)
• Nat Dilokthanakul (King Mongkut’s Institute of Technology Ladkrabang)
• Pramuk Boonsieng (Thai-Nichi Institute of Technology)
• Sansanee Auephanwiriyakul (Chiang Mai University)
• Sarayut Nonsiri (Thai-Nichi Institute of Technology)
• Soradech Krootjohn (King Mongkut’s University of Technology North Bangkok)
• Vithida Chongsuphajaisiddhi (King Mongkut’s University of Technology Thonburi)

SCHEDULE ON October 26, 2023