6th CONFSEML

Trustworthy AI Systems: Software Engineering, Machine Learning and Applications

Organizer Submission Deadline Notification of Acceptance Submission Email Download
University of Portsmouth May 27, 2027 7-20 workdays sympo_portsmouth@confseml.org Manuscript Template

Scope

We invite original research, systematic and scoping reviews, methodological papers and evaluated case studies from academia, industry and the public sector. Contributions are welcome from software engineering, machine learning, informatics and human factors. We particularly encourage multidisciplinary teams. The following themes are of particular interest:

  • Software architecture, testing and maintenance for machine-learning-enabled systems, including those in safety-critical domains
  • Verification, validation, benchmarking and assurance methods for trustworthy AI
  • Explainable and human-centred AI, including how domain experts interpret and act on model output
  • Federated and privacy-preserving learning architectures for distributed and multi-site data
  • Large language models in documentation, decision support and user-facing communication
  • Detection of and resilience to AI-generated misinformation
  • Decision support design, human-computer interaction and workflow integration

Topics

This symposium welcomes submissions with the following topics

Software Engineering

  • Advanced Topics in Software Engineering
  • Computer-Supported Collaborative Work
  • Computer Graphics and Human-Computer Interaction
  • Decision Support
  • Distributed Computing
  • Knowledge-Based Systems and Formal Methods
  • Languages and Formal Methods
  • Managing Software Projects
  • Modeling Software Architecture
  • Multimedia and Visual Software Engineering
  • Quality Management
  • Search Engines and Information Retrieval
  • Software Engineering Decision Making
  • Software Engineering Practice
  • Software Maintenance and Testing
  • Web Engineering

Meanwhile, submissions aligned with the overall conference scope are also welcomed.

Computer Applications

  • AI Architecture and Practice
  • AI Model and Algorithms
  • Artificial Intelligence in Modeling and Simulation
  • Artificial Intelligence in Scheduling and Optimization
  • Cloud Computing Architecture
  • Computer Vision and Object Recognition
  • Concurrent and Parallel Processing
  • Coordination in Robotics
  • Data Visualization and Modern Technologies
  • Distributed Intelligent Processing
  • Intelligence and Language
  • Intelligent Wireless Communications
  • Intelligent Wireless Sensor Networks
  • Internet of Things
  • Software Frameworks and Simulations

Machine Learning

  • Data Mining in Heterogeneous Networks
  • Deep and Reinforcement Learning
  • Distributed and Decentralized Machine Learning Algorithms
  • Human-robot Interface and Interaction
  • Network Slicing Optimization
  • User Behavior Prediction
  • Machine Learning in Knowledge-Intensive Systems
  • Machine Learning Methods and Analysis
  • Mechanism Design and Applications
  • Mobile Sensor Networks
  • Modeling and Identification
  • Multi-agent Systems
  • Natural Language Processing
  • Pattern Recognition and Classification for Networks
  • Robotic Automation and Control