Welcome to
MLCS 2027
2027 International Conference on Machine Learning and Complex Systems
Venue
Guangzhou, China
Conference Dates
February 26-28, 2027
Final Paper Submission Date
December 6, 2026
Notification Deadline
January 11, 2027
Final Paper Submission Date
February 6, 2027
About MLCS 2027
In an era of rapid advances in intelligent science,machine learning and complex systems have become core pillars for understanding high‑dimensional dynamic structures and driving intelligent decision‑making. Their convergence is giving rise to new computational paradigms and cognitive frameworks, offering novel pathways to address the complexity and uncertainty inherent in social, economic, and engineering systems.
To delve into the frontiers and future trends in machine learning and complex systems, the2027 International Academic Conference on Machine Learning and Complex Systems (MLCS 2027) will be held in Guangzhou, China, from February 26 to 28, 2027.The conference aims to provide a refined and efficient academic exchange platform for scholars, engineers, and researchers worldwide in related fields, focusing on frontier topics including complex network analysis, deep learning theory and applications, nonlinear dynamical systems, data‑driven modeling, and intelligent optimization algorithms. Through keynote speeches, oral presentations, and poster sessions, the conference will foster in‑depth discussions and the exchange of ideas. We sincerely invite experts and scholars from around the globe to gather in Guangzhou, share their research achievements, and jointly promote interdisciplinary innovation and development.
Submission & Publication
All accepted full papers will be published in the conference proceedings and will be submitted to EI Compendex / Scopus for indexing.
Please send the full paper (Word+PDF) to the Submission System.
📤︎Submission System (CN)📤︎Submission System (EN)
Note: All submitted articles should report original research results, experimental or theoretical, not previously published or under consideration for publication elsewhere. Articles submitted to the conference should meet these criteria. We firmly believe that ethical conduct is the most essential virtue of academics. Hence, any act of plagiarism or other misconduct is totally unacceptable and cannot be tolerated.
The topics of interest for submission include,
but are not limited to:
📚︎Machine Learning Theory & Methods
Supervised learning,Unsupervised learning,Reinforcement learning,Deep learning,Representation learning,Transfer learning,Generative models,Optimization methods,Model evaluation,Learning theory,Ensemble learning,Feature selection,Online learning,Semi-supervised learning,Bayesian methods
📚︎Complex Systems & Modeling
Nonlinear dynamics, Network science, Multi-agent systems, Emergent behaviors, Complex adaptive systems, System simulation, Complex System Stability Analysis, Computational modeling, Large-scale systems, Hybrid modeling approaches, Self-organizing systems, Dynamic networks, Spatiotemporal complexity, Complex system optimization, Interdisciplinary modeling
📚︎Intelligent Information Processing
Big data processing,Data mining,Statistical learning,Pattern recognition,Feature engineering,Intelligent data fusion,Predictive analytics,Knowledge discovery,Data visualization,Scalable algorithms,Natural language processing,Computer vision,Speech and audio processing,Smart healthcare,Smart cities
📚︎Intelligent Systems
Distributed learning systems, Cloud-based AI platforms, Edge computing and AI, High-performance computing, Software frameworks, AI development tools, Real-time processing, Embedded intelligence, System integration, Explainable AI, Human–AI collaboration, Trustworthy systems, Responsible AI, Industrial AI, AI for science and engineering
Support
🎓️️
Ms He (Hanna)
Conference Secretary
☎️ +86-16782275466
📱 WhatsApp: +86-13794043062
💬 QQ: 2454789319
The Secretary's office of MLCS 2027 will collect contributions and handle daily organizational tasks.
All paper reviews will be completed by Program Committee Members and invited experts.
* If you have any questions or inquiries, please feel free to contact us.