The MMAL 2027 will bring together leading academic scientists, researchers and scholars in the fields of multimodal artificial intelligence and machine learning of interest from around the world. Prospective authors are invited to contribute high-quality original research papers to MMAL 2027. All the accepted papers will be included in the conference proceedings, and will be submitted to EI Compendex, Scopus for indexing.
Potential topics include, but are not limited to:
Foundations and Theories of Multimodal AI
Multimodal representation learning and cross-modal alignment
Unified multimodal modeling theories and architectures
Pretraining and post-training methods for multimodal large models
World models and physical law learning
Self-supervised, semi-supervised, and few-shot multimodal learning
Explainable and trustworthy multimodal learning
Robust learning and uncertainty modeling
Cross-modal generation and reasoning
Autonomous Agents, Multi-Agent Collaboration, and Human-AI Hybrid Decision-Making
Autonomous agent theory and self-evolution mechanisms
Multi-agent collaboration and swarm intelligence
Autonomous planning and scheduling in complex dynamic environments
Reinforcement learning and autonomous decision-making
Multimodal intention understanding and human-robot interaction
Human-AI hybrid augmented intelligence and human-in-the-loop mechanisms
Embodied AI and physical interaction
Safety, ethics, and alignment in human-AI collaboration
Multimodal AI System and Implementation Technologies
Architectural design and optimization of multimodal intelligent systems
Edge-cloud collaboration and engineering deployment
Model lightweighting, compression, and embedded optimization
Multimodal data governance, evaluation, and synthetic data
Digital twin and simulation verification technologies
Large-scale data processing and distributed learning
System reliability, robustness, and fault diagnosis
Privacy preservation and security protection technologies
Cutting-Edge Applications and Interdisciplinary Intersections of Multimodal AI
Multimodal AI for scientific discovery (AI4Science)
Multimodal learning in healthcare and bioinformatics
Cross-disciplinary multimodal data analysis
Industrial manufacturing and digital twin applications
Multimodal AI in low-resource and real-world scenarios
Cross-scenario transfer learning and domain adaptation
Societal impacts and responsible AI in multimodal systems
Intelligent decision support and industry applications
Important Dates
Submission Deadline: September 30, 2026
Acceptance Deadline: October 31, 2026
Registration Deadline: November 31, 2026
Submission Guidelines
-Authors must make sure that their submissions do not substantially overlap work which has been published elsewhere or simultaneously submitted to a journal or another conference with proceedings.
-All submitted papers should be within FOI of the conference.
-The submission file is in Microsoft Word, PDF, or WordPerfect document file format.
-All URL addresses in the text (e.g., http://pkk.suu.ca) are activated and ready to click.
-All submissions should be written in English with a varying length from 4 to 8 pages.
-All submissions should strictly follow the format of the Paper Template.
-All submissions should be submitted directly to the conference e-mail address: mmal@acamail.org.