The 19th International Conference on Multi-disciplinary Trends in Artificial Intelligence 2026   (MIWAI 2026)

MIWAI 2026 invites researchers, practitioners, and industry professionals to submit their original research contributions in the field of Artificial Intelligence (AI). MIWAI provides a platform for discussion and collaboration among AI experts from academia and industry, fostering advancements in both theoretical and applied AI research. 

MIWAI 2026 website can be accessed here: https://miwai26.miwai.org

Submission Guidelines

Submission link:  https://easychair.org/conferences/?conf=miwai2026.Both research and application papers are solicited. All submitted papers will be carefully peer-reviewed on the basis of technical quality, relevance, significance, and clarity.

Each paper should have no more than twelve (12) pages in the Springer-Verlag LNCS style. The authors' names and institutions should not appear in the paper. Unpublished work of the authors should not be cited. Springer-Verlag author instructions are available at: https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines

List of Topics

Artificial intelligence is a broad area of research. We encourage researchers to submit papers in the following areas but not limited to:

• Machine Learning & Deep Learning 
  • Neural networks and representation learning 
  • Reinforcement learning and decision-making 
  • Explainable AI and trustworthy ML
• Natural Language Processing & Speech Recognition 
  • Large language models and generative AI 
  • Multimodal AI and human-AI interaction 
  • Sentiment analysis and discourse modeling
• Computer Vision & Image Processing 
  • Object detection and scene understanding 
  • Medical imaging and biometrics 
  • AI-driven creative applications (e.g., art, design, and multimedia)
• Robotics & Autonomous Systems 
  • AI for robotics and intelligent automation 
  • Multi-agent systems and swarm intelligence 
  • Human-robot interaction
• AI for Society, Ethics & Applications 
  • AI for healthcare, finance, and smart cities 
  • Ethical AI, bias mitigation, and fairness 
  • AI-driven education and learning analytics
• AI Theory & Algorithms 
  • Computational intelligence and optimization 
  • Knowledge representation and reasoning 
  • Probabilistic modeling and uncertainty in AI
• Large Language Model 
  • Interpretability and Explainability 
  • Alignment and Safety 
  • Multilingual & Cross-Lingual Learning 
  • Agentic AI with LLM- Agentic AI 
  • Defining agency in AI 
  • Reinforcement learning in agentic AI systems 
  • Multi-agent coordination and negotiation strategies 
  • Handling uncertainty and risk in agentic AI decision-making
• Secure Edge-AI 
  • Secure AI models and architectures for edge devices 
  • Privacy-preserving AI techniques 
  • Adversarial attacks and defenses in Edge-AI 
  • Lightweight cryptographic techniques for AI at the edge 
  • Trust and authentication mechanisms in Edge-AI deployments 
  • Secure data transmission and storage for edge intelligence 
  • AI-driven intrusion detection for edge networks 
  • Blockchain and decentralized security for Edge-AI 
  • Hardware security for AI-enabled edge devices
• The AI in Industry 
  • Machine vision 
  • Optics Technologies for Vision System 
  • Defect Inspection System 
  • Visual Inspection 
  • Document Analysis and Understanding 
  • Human Action Recognition and 
  • Understanding 
  • Voice Processing 
  • Vision Language Models 
  • Evolution of cognition 
  • Evolutionary game theory 
  • Behavioural economics and psychology

Committees

Steering Committee

• Arun Agarwal, Zen Technologies Ltd, India
• Richard Booth, Cardiff University, UK
• Patrick Doherty, Linköping University, Sweden
• Rina Dechter, University of California, Irive, USA
• Leon Van Der Torre, University of Luxembourg, Luxembourg
• Peter Haddawy, Mahidol University, Thailand
• Jérôme Lang, Université Paris-Dauphine, France
• Atul Negi, University of Hyderabad, India
• Somnuk Phon-Amnuaisuk, Universiti Teknologi Brunei, Brunei
• Paul Weng, Duke Kunshan University, China
• Quan Thanh Tho, Ho Chi Minh City University of Technology, Vietnam

Conveners

• Chattrakul Sombattheera, Mahasarakham University, Thailand
• Raghava Morusupalli, CVR College of Engineering, India

General Co-Chairs

• Hung Son Nguyen, University of Warsaw, Poland
• Jun Shen, University of Wollongong, Australia
• Chattrakul Sombattheera, Mahasarakham University, Thailand

Program Co-Chairs

• Sheela Ramana, University of Winnipeg, Canada
• Mengjun Hu, University of Manitoba, Canada
• Daphne Teck Ching Lai, Universiti Brunei Darussalam, Brunei

Local Organizing Co-Chairs

• Pawan Lingras, Saint Mary's University, Canada

Web Administration

• Panich Sudkhot, Zyntelligent Co., Ltd., Thailand

Publication

As in the previous years, MIWAI proceedings will be published in Springer’s Lecture Notes in Artificial Intelligence (LNAI) series. The accepted papers of MIWAI 2026 will be indexed by major databases, such as the Conference Proceedings Citation Index (CPCI), part of Clarivate Analytics’ Web of Science; Scopus; EI Engineering Index; Google Scholar; DBLP; etc.

Venue

Halifax, Nova Scotia, Canada

Contact

All questions about submissions should be emailed to miwai2026@easychair.com