Learning Systems and
The activities of the team of Learning Systems and Cybernetics Lab (LSCLab) are focused on the theoretical aspects of machine learning, data mining, big data analytics, and computational intelligence and their applications for cybernetics and security of cyber-physical systems. The principal research methodology of the lab is the development of novel techniques for learning from data streams under harsh conditions. The key framework of industrial activities of the laboratory is instead the application of learning and cybernetics techniques to guarantee the secure and safe operations of cyber-physical energy and power systems.
We are currently working on different projects related to learning systems and cybernetics. Dr. Roozbeh Razavi-Far is the director of LSCLab. Our group is committed to the principles of equity, diversity and inclusion (EDI) in all activities including the recruitment of students, training and retention. We aim to foster a diverse, equitable, and inclusive environment, assuring our graduates meet the requirements of the diverse communities, where all can work together.