AI-Integrated Electrical Engineering

AI-Integrated Electrical Engineering: Empowering Electrical Engineers, Enabling Intelligent Systems

Not every electrical engineering student begins with a strong AI background — but every student can build it.

If you’re building systems — power grids, communication networks, electronic circuits, or controls — it’s time to equip yourself with the tools that will shape the next era.

This track is designed for students in Power Engineering, Communication Engineering, Electronics, and Control & Robotics who wish to enhance their skills with AI intelligence and prepare for the future.

You’ll learn how AI can optimize and extend what you already understand:

• Energy demand prediction and smart grid management
• System health monitoring and proactive maintenance planning to prevent failures
• Intelligent robots and automated control systems
• Enhancing communication efficiency using AI-based models

No need to be an AI expert from day one.
You bring the engineering mindset — and we’ll bring the AI tools to amplify your impact.

Graduates will be future-ready engineers who understand both the physics of real-world systems and how to use AI to make them more robust, efficient, and adaptive.

Key Focus Areas in AI x Electrical Engineering

• Smart Grid and Energy Systems
  • Forecasting electricity demand (hourly, daily, weekly)
  • Real-time control of renewable energy sources (solar, wind)
  • Detection of anomalies in power transmission and distribution systems
  • Predictive maintenance and fault forecasting
• AI in Control Systems & Robotics
  • AI-based intelligent control systems (Adaptive PID, Reinforcement Learning)
  • Intelligent robots and autonomous mobility systems
  • Autonomous vehicles, drones, and industrial automation systems
• AI in Communications
  • Channel and network resource management
  • Detection and prevention of anomalies in communication systems
  • Intelligent communication systems and automated networks
• AI for Signal and Image Processing
  • Signal classification, noise reduction, quality enhancement, and data compression
  • Biometric analysis and authentication
  • Analysis and prediction of medical signals (ECG, EEG), smart CCTV, and voice-controlled systems
• AI & Embedded / Edge AI
  • Artificial intelligence on microcontrollers and embedded systems
  • Intelligent sensors and smart detection systems
• Power Electronics & Electric Vehicles (EV)
  • AI-controlled inverters and converters
  • Battery life prediction, motor control, and fault detection in EVs

Program Overview

• Bachelor’s Program: Bachelor of Engineering in Electrical Engineering (International Program)
• Master’s Program: Master of Engineering in AI-Integrated Engineering (Regular Thai curriculum)
• First intake: Academic Year 2027
• Number of Students: 30
• Admission Channels: TCAS1-3 IUP only

What You’ll Learn

Students will learn the design and development of smart power grids with energy forecasting capabilities, integrating renewable energy sources and optimizing electricity distribution through intelligent demand prediction. The program covers AI applications in signal processing, medical systems, and multimedia applications, enabling students to develop sophisticated algorithms for various electrical engineering domains.

The curriculum includes embedded AI development for IoT and edge devices, teaching students to implement artificial intelligence on resource-constrained systems for real-time decision making. Students will master intelligent control systems for robotics and Industry 4.0, learning to create adaptive automation solutions that respond to dynamic industrial environments.

Throughout the program, students will cultivate essential skills in analysis, problem-solving, and teamwork, preparing them to tackle complex electrical engineering challenges collaboratively. This comprehensive approach ensures graduates can bridge traditional electrical engineering principles with cutting-edge AI technologies to create innovative solutions for modern technological challenges.

Sample Capstone and Research Topics

• AI-based smart grid management system
• Predictive maintenance for smart electrical devices using AI
• AI-driven anomaly detection in power networks
• Intelligent control systems for industrial robots
• AI-enabled resource allocation in communication networks
• AI-based channel estimation and equalization in communication systems
• AI-driven signal analysis for medical diagnosis

Industry & Research Partners

• EGAT, MEA, and PEA
• AIS, THAICOM, GISTDA
• PTT Group, GULF, B. Grimm, EGCO
• Schneider Electric, Siemens, Hitachi Energy
• Western Digital, Delta Electronics
• Biomedical Signal Processing Research Laboratories

4+1 Pathway

• Students must meet academic requirements by their 3rd year by taking AI foundational courses.
• Students start enrolling Master’s courses also in the 4th year. (See information for the M.Eng in AI-Integrated Engineering program.)
• 4th-year project linked to Master’s research in the 5th year.
• Two degrees (B.Eng. + M.Eng.) in 5 years for future professionals.

The detailed study plan will be available soon. Read more about the undergraduate AI core courses and the Master program.

Career Opportunities

• Smart Grid / Smart Energy Engineer: Plan and develop smart power grids using AI for efficient energy management, demand forecasting, and system stability enhancement.
• AI Robotics Engineer: Design and develop robots capable of perceiving, learning, and interacting with their environment, such as factory inspection robots, rescue robots, or service robots in industrial applications.
• Electrical Systems Data Analyst / AI Engineer: Analyze data from electrical systems, sensors, or IoT devices using Machine Learning and Deep Learning to predict issues, enable predictive maintenance, and optimize system performance.
• Embedded AI System Developer: Develop AI-enabled microcontrollers and embedded systems, such as anomaly detection in electrical equipment or smart wearable devices.

Graduate Profile

AI-Integrated Electrical Engineering graduates will be able to:

• Design intelligent, energy-efficient devices and renewable energy systems
• Create ML applications for embedded systems and signal analysis
• Integrate AI into communication systems and power electronics
• Lead innovation in robotics, IoT, and renewable energy technologies
• Possess strong potential for career development in future-oriented fields

Enrichment Activities

• Internships with leading companies specializing in electrical technology, robotics, or AI
• Capstone Projects in collaboration with top-tier industries
• Student exchange programs or joint research projects with partner universities
• Interdisciplinary projects across AI x Engineering tracks

AI Foundation Courses (Undergraduate Level)

Students will take the following courses during their first 3 years as undergradute students.

• Applied AI for Engineering (01204162)
• Mathematical Foundations for AI Engineers (course under development)
• Programming Concepts for Data Processing and Analysis (course under development)

See course descriptions.

Equivalent internal courses from Electrical Engineering may be submitted for equivalency review.