4th CONFMLA

Explainable Computing, Modeling & Data Science in Complex Systems

Organizer Submission Deadline Notification of Acceptance Submission Email Download
University of Surrey September 11, 2026 7-20 workdays [email protected] Manuscript Template

Scope

This symposium welcomes contributions from researchers, practitioners, and postgraduate students working on computational, modelling, and data-driven approaches to complex systems. We particularly encourage submissions that address explainability, interpretability, and mechanistic understanding in computational and AI-assisted research workflows. Topics of interest include, but are not limited to:

  • Explainable artificial intelligence and interpretable machine learning
  • Computational modelling and simulation of complex systems
  • Hybrid mechanistic and data-driven modelling approaches
  • Multi-scale and network-based modelling frameworks
  • Data science methods for biological, ecological, social, and technological systems
  • Model validation, uncertainty quantification, and reproducibility
  • Open-source platforms, collaborative computational infrastructures, and scientific software tools
  • AI-assisted scientific discovery and decision-support systems
  • Ethical, transparent, and trustworthy computational methods

The symposium aims to foster interdisciplinary exchange, methodological discussion, and future collaboration across the broad field of explainable computational complex systems research.

Topics

This symposium welcomes submissions with the following topics

Machine Learning

  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement Learning
  • Deep Learning
  • Convolutional Neural Networks
  • Recurrent Neural Networks
  • Generative Adversarial Networks
  • Transfer Learning
  • Ensemble Learning
  • Explainable AI
  • Natural Language Processing
  • Speech Recognition
  • Image Recognition
  • Recommendation Systems
  • Anomaly Detection
  • Cluster Analysis
  • Dimensionality Reduction
  • Feature Engineering
  • Model Evaluation

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

Automation

  • AI-Assisted Design
  • Automated Machine Learning
  • Clustering and Classification
  • Collaborative Filtering and Recommendation Systems
  • Computer Vision
  • Cyber-Physical Systems
  • Data Preprocessing Methods
  • Feature Selection Approaches
  • Graph and Network Data
  • Home Automation
  • Regression with Machine Learning
  • Robotic Process Automation
  • Sensor Technology
  • Warehouse Automation
  • Hyperparameter Optimization
  • Industrial Automation
  • IoT (Internet of Things)
  • Machine-to-Machine Communication
  • Meta-learning
  • Model Interpretability Techniques
  • Model Selection Strategies
  • Neural Architecture Search
  • Pipeline Generation Methods
  • Predictive Maintenance
  • Process Automation
  • Supply Chain Automation
  • Time Series Analysis

Robotics and Intelligent Systems

  • Aerial and Underwater Robotics
  • Assistive Devices and Exoskeletons
  • Autonomous Vehicles
  • Deep Learning for Robotic Vision
  • Drones
  • Human-Robot Collaboration and Learning
  • Human-Robot Interaction
  • Imitation Learning and Learning from Demonstration
  • Intelligent Transportation Systems
  • Learning-Based Control and Planning Algorithms
  • Multi-Robot Systems and Learning
  • Reinforcement Learning for Robotics
  • Robotic Manipulation and Grasping
  • Robot Navigation and Path Planning
  • Robot Perception
  • Transfer Learning and Domain Adaptation