IUMRS-ICEM 2026

Chair:
Prof. Dr. Tanaka Hirofumi, Kyushu Institute of Technology, Japan

Co-chairs:
Asst. Prof. Dr. Ittipon Fongkaew, Suranaree University of Technology, Thailand
Dr. Wiwat nuansing, Suranaree University of Technology, Thailand

Session Description
The rapid convergence of artificial intelligence, Internet of Things (IoT), and advanced digital technologies is fundamentally transforming the landscape of electronic materials and smart device engineering. This symposium provides an interdisciplinary platform for researchers, engineers, and innovators to explore how AI-driven methodologies are reshaping the design, fabrication, characterization, and application of next-generation electronic systems. From machine learning-accelerated materials discovery to edge-AI-enabled smart sensors and intelligent IoT ecosystems, this session addresses the critical interplay between advanced materials science and digital intelligence. Participants will engage with cutting-edge research on AI-integrated hardware architectures, neuromorphic computing materials, data-driven device optimization, and intelligent sensing platforms that bridge the physical and digital worlds. This symposium welcomes contributions that demonstrate how the fusion of AI, IoT connectivity, and novel electronic materials can unlock transformative innovations in healthcare, environmental monitoring, smart manufacturing, agriculture, and sustainable technology — with a particular focus on practical implementation, scalability, and real-world impact.

Key Topics

1. AI-Accelerated Materials Discovery and Design

Machine learning and deep learning for electronic materials property prediction

High-throughput computational screening of novel semiconductors and functional materials

AI-driven inverse design and materials optimization

2. Smart Sensors and Intelligent Sensing Systems

AI-enabled biosensors, chemical sensors, and gas sensors

Machine learning integration for signal processing and anomaly detection

Self-calibrating and adaptive sensing platforms

3. Neuromorphic Computing and AI Hardware

Memristive devices and resistive switching materials for neuromorphic architectures

In-memory computing and analog AI hardware

Low-power AI chips and edge AI processing units

4. IoT-Integrated Electronic Devices and Systems

Materials and devices for wireless communication and connectivity (5G/6G, RFID, NFC)

Energy-autonomous IoT nodes: energy harvesting and storage integration

Flexible and wearable electronics for IoT applications

5. Data-Driven Device Fabrication and Process Optimization

AI-assisted semiconductor manufacturing and process control

Digital twin technologies for materials and device modeling

Real-time monitoring and quality control using machine learning

6. Intelligent Electronic Systems for Sustainable Applications

AI-driven electronic systems for precision agriculture and environmental monitoring

Smart healthcare electronics: AI-assisted diagnostics and wearable medical devices

AI-optimized energy management in smart grid and green electronics

7. Digital Technologies for Next-generation Electronic Platforms

Quantum-classical hybrid computing interfaces

AI at the edge: microcontrollers, FPGAs, and embedded intelligence

Cyber-physical systems and human-machine interaction