2026 International Conference on Machine Learning and Unmanned Systems


The 2026 International Conference on Machine Learning and Unmanned Systems (MLUS 2026) will be held from May 29 to 31, 2026, in Nanjing, China. The conference is supported by Jiangsu Second Normal University.

With continuous breakthroughs in artificial intelligence and its deep integration into physical systems, interdisciplinary research in machine learning and unmanned systems has become a key driving force in the intelligent era, demonstrating immense potential in fields such as smart manufacturing, intelligent transportation, environmental exploration, and social services.

The MLUS 2026 Conference offers an opportunity to discuss new issues, tackle complex problems and find advanced solutions to enable shaping new trends in Machine Learning and Unmanned Systems. Submitted papers will be subject to stringent peer review by at least two experts and carefully evaluated based on originality, significance, technical soundness, and clarity of exposition.

Publication

After a careful reviewing process, all accepted papers will be published in the Conference Proceedings, and submitted to EI Compendex, Scopus for indexing. Note: All submitted articles should report original results, experimental or theoretical, not previously published or being 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 any academics. Hence, any act of plagiarism or other misconduct is totally unacceptable and cannot be tolerated.

Conference Tracks

Track 1: Machine Learning

  • • Deep Learning
  • • Reinforcement Learning
  • • Neural Networks
  • • Unsupervised Learning and Representation Learning
  • • Intelligent Decision-Making
  • • Feature Selection
  • • Data Mining and Knowledge Discovery
  • • Information Retrieval
  • • Generative Models and Simulation Environment Construction
  • • Embodied AI and World Models
  • • Multi-Agent Collaboration and Distributed Learning
  • • Edge Intelligence and Computing Power Coordination
  • • Large-Scale Simulation and Digital Twins
  • • Explainable AI and Machine Learning
    		•  Track 2: Unmanned Systems

  • • Unmanned Aerial Vehicles
  • • Unmanned Ground Vehicles/ Autonomous Vehicles
  • • Unmanned Underwater Vehicles and Systems
  • • Robotic Systems and Design
  • • UAS Communication and Networking Technologies
  • • Unmanned Systems Navigation and Positioning Technologies
  • • Intelligent Environmental Perception for Unmanned Systems
  • • Autonomous and Cooperative Control Technologies for Unmanned Systems
  • • Actuators and Actuation Technologies
  • • Unmanned Mission and Behavior Planning
  • • Multi-Agent and Cooperative Systems
  • • Single-Agent Learning and Decision-Making
  • • Swarm Intelligence and Cluster Robotics
  • • Autonomous Manipulation and Grasping
  • • Artificial Intelligence Algorithms
  • • Brain-Computer Integration and Hybrid Intelligence Technologies
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