Speaker Guidelines & Abstract Submission
International Conference on AI, Machine Learning & Data Science
MICAI 2027 | Barcelona, Spain | May 19–21, 2027
Speaker Guidelines
Magnova Group invites researchers, academicians, data scientists, AI engineers, machine learning specialists, software developers, industry professionals, and technology innovators to contribute to the International Conference on AI, Machine Learning & Data Science (MICAI 2027).
The conference provides a forum for sharing research findings, technical developments, practical applications, and innovative approaches in artificial intelligence, machine learning, data science, and related emerging technologies.
Prospective speakers are encouraged to submit original research, technical studies, industry case studies, review papers, and evidence-based perspectives relevant to the conference topics. All submissions are subject to the applicable conference review and acceptance process.
Abstract Submission
Authors are invited to submit abstracts presenting research, methodologies, experiments, applications, and emerging developments in AI, machine learning, and data science.
Suggested topics include: generative AI, large language models, deep learning, computer vision, natural language processing, predictive analytics, big data, responsible AI, intelligent automation, and AI applications across different industries.
Submission method: Use the official MICAI 2027 abstract submission portal or the submission contact published by the conference organizers.
Abstract Requirements
Terms & Conditions
Submitted work should be original and relevant to AI, machine learning, data science, or the conference's related subject areas.
Authors must accurately describe their research, methods, results, datasets, and contributions.
All co-authors should approve the submission and the identification of the presenting author.
Authors must identify sources, datasets, software, and third-party materials where appropriate and comply with applicable licenses.
Research involving personal, sensitive, or restricted data should follow applicable privacy, ethical, and legal requirements.
AI-generated or AI-assisted material should be used responsibly, verified for accuracy, and disclosed when required by the conference policy.
Submissions may be reviewed for relevance, technical quality, originality, clarity, and suitability for the scientific program.
Acceptance, presentation scheduling, and participation requirements are subject to the official conference instructions.
Modes of Presentation
Oral Presentation
Present research findings, algorithms, experiments, technical approaches, or real-world applications in a scheduled session.
Poster Presentation
Communicate research objectives, methodology, results, visualizations, and key contributions through a concise research poster.
Keynote / Invited Talk
Share expert perspectives on major developments, research directions, technical challenges, and future opportunities in AI and data science.
Industry Case Study
Discuss practical AI deployments, machine learning workflows, data-driven decision-making, and lessons learned from implementation.
Emerging Research Presentation
Present early-stage research, new hypotheses, experimental ideas, prototype systems, and promising technical approaches.
Panel Discussion
Explore responsible AI, data governance, innovation, industry adoption, technical limitations, and the future of intelligent systems.
Presentation Language
English is recommended for abstracts and presentation materials to support communication among the international research and professional community. Please follow the official conference instructions if additional language arrangements are announced.
Speaker Information
Speaker Confirmation
Following the review process, authors will be informed of the submission outcome using the contact details provided. Accepted speakers should follow the instructions for confirming participation, submitting presentation materials, and checking their session schedule.
Please notify the Conference Team promptly if the presenting author or presentation availability changes.
Presentation Guidelines
Clearly state the research problem and objectives.
Explain the algorithms, models, or analytical methods used.
Describe datasets, experiments, and evaluation metrics where relevant.
Present results accurately and distinguish findings from assumptions.
Discuss limitations, potential bias, and relevant ethical considerations.
Use clear visuals and readable charts, diagrams, and tables.
Credit sources and respect software, dataset, and image licenses.
Stay within the presentation time allocated by the organizers.
Presenters should not disclose confidential information or expose personal data without appropriate authorization. Research claims and AI-generated outputs should be checked for accuracy before they are included in a presentation.
Frequently Asked Questions
Researchers, faculty members, students, data scientists, AI and machine learning engineers, industry professionals, and other contributors whose work fits the conference topics may submit an abstract.
Topics may include artificial intelligence, machine learning, deep learning, generative AI, natural language processing, computer vision, data engineering, big data analytics, predictive modeling, explainable AI, and industry applications.
Industry case studies, practical deployments, technical evaluations, and data-driven projects may be considered when they are relevant and provide clear methods, findings, or lessons learned.
Yes. Include the correct names and affiliations of all authors and identify the person responsible for presenting the work.
Review studies, emerging research, prototypes, and preliminary findings may be considered, subject to the conference scope and review criteria.
Virtual presentation availability depends on the official arrangements for MICAI 2027. Check the conference instructions or contact the organizers for confirmation.
No. Submissions are subject to the applicable review and selection process. Acceptance depends on the conference criteria and available program space.
Provide the research background, objective, methodology, main findings or expected contribution, conclusion, and relevant keywords. Follow any specific word limit in the official submission instructions.
Authors remain responsible for the accuracy, originality, attribution, and integrity of their submissions. Check and follow the conference policy on disclosure of AI-assisted work.
The organizers will communicate the next steps for participation, presentation preparation, scheduling, and any applicable registration requirements.
Recommended Abstract Format
Important Note
This page provides general speaker and abstract-submission guidance for the International Conference on AI, Machine Learning & Data Science (MICAI 2027), scheduled for May 19–21, 2027, in Barcelona, Spain. Please verify the official submission deadline, abstract length, registration requirements, presentation options, and event policies with the conference organizers before submitting.
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