AI & Machine Learning Conference

All times are in Anywhere on Earth (AoE) time zone.

Topics of Interest

• Deep Learning: Neural network architectures for representation learning, including convolutional, recurrent, and transformer-based models, with an emphasis on scalability, training efficiency, and generalization across domains.
• Multi-Agent and Hybrid Intelligence: Systems that combine multiple learning agents, symbolic reasoning, or human-in-the-loop decision-making to solve problems no single model or agent can handle alone.
• Generative AI: Models that synthesize text, images, audio, or structured data, including diffusion and autoregressive approaches, and their evaluation, safety, and real-world deployment.
• Explainable AI: Techniques for making model predictions interpretable to end users and stakeholders, including feature attribution, surrogate models, and human-centered explanation design.
• Large Language Models (LLMs): Pretraining, fine-tuning, prompting, and retrieval augmentation of large-scale language models, along with evaluation of their reasoning capabilities and failure modes.
• Machine Learning: Core supervised, unsupervised, and semi-supervised learning methods, model selection, and theoretical foundations underpinning applied AI systems.
• Reinforcement Learning: Sequential decision-making methods including value-based, policy-gradient, and model-based approaches, applied to control, games, and real-world optimization problems.
• Applied AI: Domain-specific deployments of AI methods in industry and government settings, covering integration challenges, evaluation in production, and lessons from real deployments.
• AI in Healthcare: Diagnostic support, clinical decision systems, medical imaging analysis, and patient outcome prediction using machine learning, with attention to safety and regulatory constraints.
• AI for Climate and Sustainability: Machine learning applications to climate modeling, emissions tracking, resource optimization, and environmental monitoring.

Submission Guidelines

• We accept initial submission in PDF format only.
• In adherence to the double-blind peer review policy, please ensure your paper contains no identifying author information like author details, university and country information.
• Authors are responsible for ensuring their papers are thoroughly checked and proofread prior to submission. No revisions are permitted during the review process. If accepted, the authors may make minor revisions before final publication to address any identified areas for improvement.
• You will be able to include full author details in the camera-ready submission, following the specified format. Author names, email addresses, and their sequence will be considered final as per the submitted camera-ready version.
• Submissions are expected to be primarily original. While up to 25% of the text may be drawn from prior publications by the same authors, provided proper citation is included, at least 75% of the manuscript must consist of new, unpublished material.

Downloads

• MS Word Paper Format
• LaTeX Paper Format
• Presentation Format

Formatting Guidelines

• The maximum manuscript length is 18 pages for the main text, exclusive of references and appendices up to 7 pages. Submissions exceeding this limit may be considered by the chair, particularly in the case of review or survey articles.
• Submissions must present original research relevant to the conference topics.
• Authors must ensure the accuracy of all sections in their paper.
• The abstract should adhere to the 150-250 word limit as per the conference guidelines.
• Place figures and tables where they are discussed in the text, and make sure they are clear and easy to read.
• All figures, tables, references, appendices, algorithms, annexures, and supplementary materials must be clearly numbered, properly cited in the text.
• Tables must be neatly aligned within the page margins and must not overflow the page boundaries.
• Figure captions and table headings should be concise, unique, and ideally limited to a maximum of two lines.
• References should be formatted correctly and consistently, including all the necessary details such as, author names, paper titles, publication sources, and years. Every reference listed must be cited in the main text.
• The use of foreign languages in the manuscript is not allowed unless accompanied by a corresponding English translation.
• Manuscripts are required to adhere to the formatting guidelines specified in the provided template.

Review Process

Submissions will undergo double-blind peer review. To ensure anonymity, please omit all author-identifying information from your manuscript, including names, affiliations, and any funding or other acknowledgments. Citations and mentions of closely related prior work should also be anonymized.

All submitted papers will be reviewed by a minimum of three regular program committee members or two senior program committee members. Acceptance decisions will be based on assessments of novelty, technical depth, elegance, impact (both practical and theoretical), and presentation quality.

• Original: Exploring a new idea, project, issue, or offering new insights/perspectives on existing research/information.
• Engaging: Interactive and audience-engaging, or addressing research community needs.
• Significant: Addressing key issues related to improving current techniques' effectiveness, with easily understood and widely applicable content.
• Quality: Substantiated by adequate data, referencing relevant existing work, and honestly acknowledging limitations.
• Relevant: Aligned with at least one of the conference's designated tracks.

Use of AI-Assisting Tools

The conference permits the responsible use of Generative AI (GenAI) tools in manuscript preparation. Authors are required to observe the following:

• Declare Usage – Any use of GenAI must be disclosed in the manuscript (e.g., in a Declaration on Generative AI section).
• Maintain Responsibility – Authors must critically review and edit AI-assisted text; unedited AI output is not acceptable.
• No AI Authorship – GenAI tools cannot be listed as authors. Authorship is limited to humans who take full responsibility for the work.
• Limit Role of AI – GenAI may support drafting and language refinement, but the development of scientific ideas, arguments, results, and conclusions must be carried out by human authors.
• Accountability – Authors remain fully accountable for the accuracy, originality, and integrity of their manuscripts.

Note: Non-compliance with these guidelines will be treated as academic misconduct and may result in the removal of published work.

Other Tracks at 11th Future Technologies Conference 2026

• Human-Computer Interaction
• Data Science
• Ambient Intelligence
• Future Computing Architectures
• Robotics
• Security
• Learning Technologies

View the full Call for Papers for 11th Future Technologies Conference 2026 »