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 published by ACM, which will be sent 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: November 15, 2026

Acceptance Deadline: December 15, 2026

Registration Deadline: December 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.