The 2nd International Conference on Artificial Intelligence Systems (AIS 2026)

12 - 15 May, 2026 | San Antonio, USA.

Call for Papers

Artificial Intelligence (AI) systems are computational frameworks designed to perform tasks that typically require human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. These systems integrate algorithms, data, and computing power to enable machines to adapt and improve their performance over time. AI systems encompass a wide range of technologies, including machine learning, natural language processing, computer vision, and autonomous robotics, and they are increasingly applied in domains such as healthcare, finance, cybersecurity, transportation, and smart cities. As they continue to evolve, AI systems are not only transforming industries and enhancing human capabilities but also raising important considerations around ethics, transparency, and trustworthiness.

The International Conference on Artificial Intelligence Systems (AIS 2026) aims to bring together leading researchers, academics, and practitioners from around the world to share their latest findings, innovations, and applications in Artificial Intelligence and intelligent systems. AIS 2026 provides a premier interdisciplinary platform for presenting advances and exchanging insights on the theoretical foundations, cutting-edge technologies, and real-world implementations of AI. AIS 2026 will feature keynote talks, technical paper sessions, workshops, and tutorials covering a wide range of AI topics. We invite submissions of high-quality research papers describing original and unpublished results in all areas of Artificial Intelligence Systems. addresses the use of advanced intelligent systems in providing cybersecurity solutions in many fields, and the challenges, approaches, and future directions. We invite the submission of original papers on all topics related to Intelligent Systems with special interest in but not limited to:

  • Machine Learning and Data-Driven Systems
    • Deep Learning, Representation Learning, and Transfer Learning
    • Reinforcement Learning and Adaptive Systems
    • Federated, Distributed, and Edge AI
    • Reinforcement Learning and Autonomous Agents
    • Federated Learning and Distributed AI Systems
    • AI Applications and Intelligent Systems
    • Scalable and High-Performance AI Architectures
    • Edge AI, Cloud AI, and Embedded Intelligence
    • Optimization and Resource-Aware AI Systems
  • Natural Language and Multimodal AI
    • Natural Language Processing and Understanding
    • Speech Recognition and Conversational Agents
    • Multimodal Learning and Vision-Language Systems
    • Knowledge Representation and Reasoning
    • Data Mining, Knowledge Discovery, and Information Retrieval
    • Automated Planning and Scheduling
  • Generative AI, Foundation Models, and Large Language Models
    • Generative AI and Large Language Models (LLMs)
    • Explainable and Responsible AI
    • Federated, Distributed, and Edge AI
    • Reinforcement Learning and Autonomous Agents
    • AI for Decision Support Systems
    • Natural Language Processing and Computational Linguistics
    • Multilingual and Low-Resource Language Models
    • Human-Computer Interaction (HCI) and Assistive Technologies
    • Conversational AI and Dialogue Systems
    • Computational Language and Human-Centered Systems
    • Prompt Engineering and Fine-tuning
    • Multimodal LLMs
    • Agentic AI
  • Computer Vision, Image and Video Processing
    • Image and Video Understanding
    • Object Detection, Recognition, and Tracking
    • Multimodal Learning and Vision-Language Systems
    • 3D Vision and Scene Understanding
    • Affective Computing and Emotion Recognition
  • Artificial Intelligence Applications
    • Robotics and Autonomous Systems
    • AI for Healthcare, Smart Cities, and Transportation
    • AI in Finance, Education, and Industry 4.0
    • AI for Cybersecurity, Privacy, and Digital Trust
    • AI Infrastructure and Engineering
    • Recommender Systems and Personalization
    • AI for Social Good and Humanitarian Applications
    • Emerging Trends and Future Directions in AI Systems
  • Artificial Intelligence Security
    • Responsible and Trustworthy AI
    • Explainable AI and Transparency
    • Ethical and Societal Implications of AI
    • AI Safety, Robustness, and Security
    • AI Policy, Regulation, and Governance

Call for Workshop Proposals

AIS will host a series of workshops and is also inviting new workshop proposals. The purpose of the workshops is to emphasize current and emerging topics of particular interest to the community.

Proposal Format

Each workshop proposal must include (maximum 4 pages, in PDF format):

  • Title of the workshop.
  • Workshop organizers (name, affiliation and short biography).
  • Scope and topics of the workshop.
  • Rationale:
    • Why the workshop is related to AIS.
    • Why the topic is important.
    • Why the workshop may attract a significant number of attendees.
  • Workshop details:
    • A draft call for papers (including organizers, program committee, and steering committee if any). Organizers are expected to be fully committed and physically present at the workshop.
    • Workshop tentative schedule (number of expected papers, duration full/half day, format talks/posters, etc.). We encourage full-day events that demonstrate the interest of the community in the proposed topic and guarantee the commitment of the organizers. Half-day proposals are also welcome but expected to provide a rationale for the proposed duration.
    • Names of potential participants and invited speakers (if any).
  • Workshop history: if there are past workshops, the history of the workshop.