35th ROME Global Conference on Advanced Computing, Engineering & Cybersecurity (ACEC-25) Oct. 1-3, 2025 Rome (Italy)

Call for papers

Topics of interest for submission include any topics on:

I. Advanced Computing:

• High-Performance Computing (HPC):
  • Exascale and post-exascale computing architectures.
  • Heterogeneous computing (CPU-GPU, FPGA).
  • Energy-efficient HPC and green computing.
  • Applications of HPC in various engineering disciplines (e.g., computational fluid dynamics, structural analysis, materials science).
  • Advanced numerical algorithms and simulations.
  • Data management and visualization for large-scale simulations.
• Quantum Computing:
  • Quantum algorithms and their potential applications in engineering and cybersecurity (e.g., optimization, materials design, cryptography).
  • Quantum hardware development (superconducting qubits, trapped ions, photonic qubits, etc.).
  • Quantum error correction and fault-tolerant quantum computing.
  • Quantum simulation of physical and chemical systems.
  • Hybrid quantum-classical computing approaches.
• Neuromorphic Computing:
  • Brain-inspired computing architectures and their applications.
  • Spiking neural networks and event-based processing.
  • Hardware implementations of neural networks.
  • Energy efficiency in neuromorphic systems.
  • Applications in AI, robotics, and sensor processing.
• Edge Computing and IoT:
  • Architectures and platforms for edge intelligence.
  • Federated learning on edge devices.
  • Real-time data processing and analytics at the edge.
  • Security and privacy challenges in edge and IoT environments.
  • Applications in smart cities, industrial IoT, and autonomous systems.
• Cloud Computing:
  • Serverless computing and function-as-a-service (FaaS).
  • Containerization and orchestration (Docker, Kubernetes).
  • Hybrid and multi-cloud strategies.
  • Cloud-native application development.
  • Security and compliance in cloud environments.
  • AI and machine learning services in the cloud.
• Advanced Architectures and Algorithms:
  • Reconfigurable computing.
  • In-memory computing.
  • Approximate computing.
  • Bio-inspired computing.
  • Novel data structures and algorithms for large-scale data processing.

II. Engineering:

• AI and Machine Learning in Engineering:
  • AI for design and optimization.
  • Predictive maintenance using machine learning.
  • AI in robotics and automation.
  • Computer vision for inspection and quality control.
  • Natural language processing for engineering documentation and collaboration.
  • Digital twins for simulation and monitoring.
• Robotics and Automation:
  • Human-robot interaction and collaboration (cobots).
  • Autonomous mobile robots (AMRs) and their applications.
  • Soft robotics and bio-inspired robotics.
  • Advanced control systems for robots.
  • Robotics in manufacturing, healthcare, agriculture, and logistics.
• Advanced Materials and Manufacturing:
  • Smart materials and metamaterials.
  • Additive manufacturing (3D printing) for advanced applications.
  • Nanomaterials and nanotechnology in engineering.
  • Sustainable materials and green manufacturing.
  • Advanced composites.
• Cyber-Physical Systems (CPS):
  • Design and analysis of integrated computational and physical systems.
  • Real-time control and embedded systems.
  • Sensor networks and data acquisition.
  • Applications in smart infrastructure, transportation, and energy systems.
  • Security considerations for CPS.
• Sustainable Engineering:
  • Renewable energy systems and integration.
  • Energy efficiency and conservation.
  • Waste management and circular economy principles.
  • Environmental monitoring and remediation.
  • Sustainable infrastructure development.
• Biomedical Engineering:
  • Bioinformatics and computational biology.
  • Medical imaging and analysis.
  • Bioprinting and tissue engineering.
  • Wearable sensors and health monitoring devices.
  • Neural engineering and neuroprosthetics.

III. Cybersecurity:

• Artificial Intelligence in Cybersecurity:
  • AI-powered threat detection and analysis.
  • Machine learning for anomaly detection and intrusion prevention.
  • AI for security automation and orchestration (SOAR).
  • Adversarial AI and defense against AI-powered attacks.
• Network Security:
  • Next-generation firewalls and intrusion detection/prevention systems.
  • Software-defined networking (SDN) security.
  • Wireless network security (5G and beyond).
  • Network forensics and incident response.
  • Zero-trust architectures and micro-segmentation.
• Data Security and Privacy:
  • Advanced encryption techniques (including post-quantum cryptography).
  • Data loss prevention (DLP) and data governance.
  • Privacy-enhancing technologies (PETs).
  • Compliance with data privacy regulations (e.g., GDPR).
  • Secure data storage and management in the cloud.
• Identity and Access Management (IAM):
  • Multi-factor authentication (MFA) and biometrics.
  • Role-based access control (RBAC) and attribute-based access control (ABAC).
  • Identity federation and single sign-on (SSO).
  • Decentralized identity solutions.
• Cybersecurity for Critical Infrastructure:
  • Industrial control systems (ICS) and operational technology (OT) security.
  • Security of smart grids and energy systems.
  • Transportation cybersecurity.
  • Water and wastewater infrastructure security.
• Emerging Threats and Attack Vectors:
  • Ransomware and extortion attacks.
  • Supply chain security.
  • Social engineering and phishing attacks.
  • Insider threats.
  • Deepfakes and disinformation.
  • Quantum computing threats to cryptography.
• Cybersecurity Governance, Risk, and Compliance (GRC):
  • Cybersecurity frameworks and standards (e.g., NIST, ISO 27001).
  • Risk assessment and management.
  • Cybersecurity audit and compliance.
  • Legal and ethical aspects of cybersecurity.

Overlapping and Interdisciplinary Topics:

• Security of AI/ML systems.
• Secure edge computing and IoT deployments.
• Privacy-preserving machine learning.
• Hardware security and trusted execution environments.
• Formal verification for security.
• Explainable AI for security analysis.
• Cybersecurity in autonomous systems and robotics.