Paal Engelstad

Paal Engelstad is a Professor at the University of Oslo, affiliated with the Section for Autonomous Systems and Sensor Technologies at the Institute of Transport Economics (ITS). He holds a full-time academic position. His research focuses on machine learning, wireless communications, renewable energy systems, and network security, with applications in IoT, reinforcement learning, and graph neural networks. His work addresses challenges in energy forecasting, autonomous systems, and secure information exchange.

Key research interests include:

• Deep learning for solar and wind energy forecasting
• Graph neural networks and their applications in recommendation systems and network analysis
• Non-orthogonal multiple access (NOMA) in IoT and wireless networks
• Reinforcement learning for autonomous systems and control
• Security classification and anomaly detection in networks

His recent publications highlight contributions to probabilistic solar irradiance forecasting, graph-based wind prediction models, and reinforcement learning algorithms for autonomous vehicles. He collaborates extensively with international researchers and has led projects like DESSI (Distributed Energy System and Security Infrastructure).

Engelstad is involved in the following initiatives:

• Development of secure cross-domain information exchange frameworks
• Advances in energy-efficient IoT and sensor networks
• Applications of machine learning in cybersecurity and network optimization

His research lab focuses on interdisciplinary solutions bridging transport economics, energy systems, and intelligent sensor technologies.