20th MILAN World Conference on Electrical, Electronics and Intelligent Systems: WCEEIS-26

Call for papers/Topics

The field of Electrical, Electronics, and Intelligent Systems is currently undergoing a massive convergence driven by Artificial Intelligence (AI), Renewable Energy Transition, and Edge Computing.

Below is a comprehensive hierarchy of topics and subtopics designed for researchers, conference organizers, or students looking to specialize in the 2025–2026 technological landscape.

Topics of Interest for Submission include, but are Not Limited to:


1. Electrical & Power Systems

The focus has shifted from traditional generation to decentralized, "smart" grids and the massive electrification of transport.

  • Smart Grids & Microgrids:

    • Integration of Distributed Energy Resources (DERs).

    • Low-inertia power systems and Grid-forming inverters.

    • Blockchain for peer-to-peer (P2P) energy trading.

  • Renewable Energy Systems:

    • Floating solar and offshore wind farm optimization.

    • Advanced Maximum Power Point Tracking (MPPT) algorithms.

    • Hybrid energy storage systems (Lithium-ion + Supercapacitors).

  • Electric Machines & Drives:

    • Axial flux motors for high-performance EVs.

    • Sensorless control of Permanent Magnet Synchronous Motors (PMSM).

    • Condition monitoring using AI-based vibration analysis.


2. Electronics & VLSI Design

Innovation here is defined by Wide Bandgap (WBG) materials and the push toward "More than Moore" (packaging multiple chips together).

  • Power Electronics:

    • Applications of Silicon Carbide (SiC) and Gallium Nitride (GaN) FETs.

    • High-efficiency Wireless Power Transfer (WPT) for room-scale charging.

    • Solid-state transformers for medium-voltage grids.

  • VLSI & Embedded Systems:

    • System-on-Chip (SoC) design for Edge AI.

    • 3D Integrated Circuits (3D IC) and Advanced Packaging.

    • Low-power hardware design for wearable medical devices.

  • Flexible & Organic Electronics:

    • Printable conductive inks for smart textiles.

    • Biodegradable sensors for environmental monitoring.

    • Foldable and stretchable display technologies.


3. Intelligent Systems & Robotics

This is the "brain" of modern engineering, where traditional control theory meets modern machine learning.

  • Autonomous Systems:

    • Agentic AI: Autonomous agents that can perform end-to-end workflows.

    • Path planning and obstacle avoidance for Swarm Robotics.

    • Unmanned Aerial Vehicles (UAVs) for precision agriculture.

  • Human-Machine Collaboration:

    • Cobots (Collaborative Robots) in smart factories (Industry 5.0).

    • Brain-Computer Interfaces (BCI) for prosthetic control.

    • Augmented Reality (AR) overlays for remote industrial maintenance.

  • Intelligent Control Theory:

    • Model Predictive Control (MPC) for complex thermal systems.

    • Reinforcement Learning (RL) for adaptive traffic signal control.

    • Explainable AI (XAI) in high-stakes autonomous decision-making.


4. Signal Processing & Communication

As we look beyond 5G, the focus is on lower latency and higher frequency bands like Terahertz (THz).

  • Future Communication (6G & Beyond):

    • Reconfigurable Intelligent Surfaces (RIS) for signal boosting.

    • Visible Light Communication (VLC) and Li-Fi.

    • Quantum communication and post-quantum cryptography.

  • Advanced Signal Processing:

    • Real-time biomedical signal processing (EEG/ECG) for point-of-care.

    • Computer Vision for defect detection in semiconductor manufacturing.

    • Deep Learning for audio source separation and noise cancellation.


5. Emerging Interdisciplinary Frontiers

These topics represent the most recent "cross-pollination" between fields.

  • Digital Twins:

    • Creating real-time virtual replicas of cities or power plants for predictive maintenance.

  • Cyber-Physical Security:

    • Protecting critical infrastructure (grids, water plants) from state-sponsored hacks.

    • Hardware-based security (Physical Unclonable Functions - PUF).

  • Green Computing:

    • Developing AI models that require significantly less electrical power.

    • Energy-harvesting sensors that run on ambient light or thermal gradients.