Welcome to AIS 2026

12th International Conference on Artificial Intelligence and Soft Computing (AIS 2026)

July 25 ~ 26, 2026, Toronto, Canada

Hybrid--Registered authors can present their work online or face to face New

Program Committee

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Accepted Papers

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Toronto, Canada

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Scope

The 12th International Conference on Artificial Intelligence and Soft Computing (AIS 2026) will provide an excellent international forum for sharing knowledge, exchanging ideas, and presenting the latest advances in the theory, methodology, and applications of Artificial Intelligence and Soft Computing. As AI continues to evolve through breakthroughs in machine learning, generative models, intelligent systems, and computational intelligence, AIS 2026 aims to highlight both foundational research and cutting edge innovations that are shaping the future of intelligent technologies.

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Call for Papers


The conference seeks significant contributions across all major areas of Artificial Intelligence and Soft Computing, spanning theoretical developments, algorithmic advances, system architectures, and real world applications. By providing a platform for interdisciplinary dialogue and high impact research dissemination, AIS 2026 supports the continued growth of the AI community and encourages the development of intelligent systems that address complex scientific, industrial, and societal challenges.


Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works, and industrial experiences that describe significant advances in the following areas, but are not limited to the topics listed.

Topics of interest include, but are not limited to, the following


    Artificial Intelligence
  • AI Algorithms & Intelligent Decision Making
  • Knowledge Representation, Reasoning & Cognitive Architectures
  • Probabilistic Reasoning, Bayesian Models & Uncertainty Quantification
  • Multi Agent Systems, Agentic AI & Autonomous Decision Making
  • Reactive, Distributed & Self Organizing AI Systems
    • Machine Learning & Data Driven Intelligence
  • Machine Learning (Supervised, Unsupervised, Semi Supervised)
  • Deep Learning Architectures, Optimization & Training Dynamics
  • Foundation Models (LLMs, VLMs, Multimodal Models)
  • Self Supervised, Contrastive & Representation Learning
  • Continual, Lifelong & Online Learning
  • Computational Learning Theory
  • Trustworthy ML: Robustness, Safety, Fairness & Explainability
  • Efficient ML: Quantization, Distillation & Sparse Models
    • Generative AI & Creative Intelligence
  • Diffusion Models, GANs, VAEs & Generative Transformers
  • Text to Image, Text to Video, Text to 3D & Multimodal Generation
  • Synthetic Data Generation & Evaluation
  • Creative AI for Art, Music, Design & Simulation
  • Generative Agents & Autonomous Creative Systems
    • Natural Language Processing & Speech Technologies
  • Large Language Models (LLMs) & Instruction Tuned Models
  • Text Understanding, Summarization, QA & Information Extraction
  • Dialogue Systems, Conversational AI & Agentic NLP
  • Speech Recognition, Speech Synthesis & Spoken Dialogue
  • Multilingual NLP & Low Resource Language Modeling
  • NLP for Reasoning, Planning & Knowledge Integration
    • Computer Vision, Image & Video Intelligence
  • Computer Vision, Scene Understanding & Object Recognition
  • Vision Language Models (VLMs) & Multimodal Perception
  • Image Processing, Image Understanding & Pattern Recognition
  • Video Understanding, Action Recognition & Video AI
  • 3D Vision, NeRFs, 3D Reconstruction & Spatial AI
  • Biomedical Image Analysis & Medical Vision AI
    • Robotics, Autonomous Systems & Mechatronics
  • Autonomous Robotics, Planning & Navigation
  • Robot Perception, Manipulation & Control
  • Human Robot Interaction & Cognitive Robotics
  • Soft Robotics & Bio Inspired Robotics
  • Mechatronics & Intelligent Automation
  • Embodied AI & Simulation Driven Robotics
    Soft Computing & Computational Intelligence
  • Fuzzy Logic, Fuzzy Systems & Fuzzy Control
  • Evolutionary Computing, Genetic Algorithms & Swarm Intelligence
  • Rough Sets, Granular Computing & Morphic Computing
  • Hybrid Intelligent Systems (Neuro Fuzzy, Neuro Symbolic, etc.)
  • Soft Computing Theory & Applications
    • Reinforcement Learning & Decision Making
  • Reinforcement Learning (RL) & Deep RL
  • RLHF (Reinforcement Learning from Human Feedback)
  • World Models & Model Based RL
  • Multi Agent RL & Cooperative/Competitive Learning
  • RL for Robotics, Games & Autonomous Systems
    • Data Science, Mining & Knowledge Discovery
  • Data Mining, Knowledge Discovery & Big Data Analytics
  • Graph Machine Learning, GNNs & Graph Transformers
  • Knowledge Graphs, Semantic Reasoning & Web Intelligence
  • Data Visualization, Interactive Analytics & Explainability
  • ML Pipelines, MLOps & Data Centric AI
    • Bio Inspired & Bio Computing
  • Bioinformatics, Computational Biology & Genomic AI
  • Neural Computation & Brain Inspired AI
  • Nano Computing, Micro Systems & Bio Digital Interfaces
  • AI for Healthcare, Precision Medicine & Drug Discovery
    • AI Systems, Optimization & Engineering
  • ML Compilers, Accelerators & Optimization (XLA, TVM, Triton)
  • Distributed Training, Scaling Laws & Large Model Infrastructure
  • Edge AI, TinyML & On Device Intelligence
  • AI Systems Engineering & Deployment Architectures
  • Energy Efficient AI & Green Machine Learning
    • AI Safety, Ethics, Alignment & Governance
  • AI Safety, Alignment & Risk Mitigation
  • Adversarial ML, Robustness & Secure AI
  • Explainability, Transparency & Accountability
  • Fairness, Bias Mitigation & Responsible AI
  • Policy, Governance & Societal Impacts of AI
    • Emerging AI Domains & Future Directions
  • Quantum Machine Learning & Quantum AI
  • AI for Science (Physics, Chemistry, Biology, Climate)
  • AI for Telecommunications, Networking & 6G Systems
  • AI for Smart Cities, IoT & Ambient Intelligence
  • AI for Industry 4.0, Manufacturing & Automation
  • AI Driven Simulation, Digital Twins & Virtual Worlds

Paper Submission

Authors are invited to submit papers through the conference Submission System by June 13, 2026. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) series (Confirmed).

Selected papers from AIS 2026, after further revisions, will be published in the special issue of the following journal.

Important Dates

Second Batch : Submissions after May 11, 2026

Submission Deadline

June 13, 2026

Authors Notification

July 12, 2026

Registration & camera - Ready Paper Due

July 18, 2026

Other Conferences
Past Events
Invited Talk

Proceedings

Hard copy of the proceedings will be distributed during the Conference. The softcopy will be available on AIRCC Digital Library

Sponsors