Relevant areas include robotics, machine learning, AI, optimization, etc., with applications connected to electrical engineering, such as:
- Cyberphysical systems, e.g., machine based perception in robotics and autonomous systems; analysis of massive sensor data for anomaly detection, system vulnerability and failure characterization; data-driven learning of high performance control schemes;
- Electrical networks, e.g., data-based learning of the aggregate behavior of renewable energy sources; anticipation of vulnerable system states and data based learning and identification of corrective actions; disaggregation of loads based on smart meter and substation provided data.
- Communications systems, e.g., machine learning for optimal usage of the frequency spectrum in cognitive radio; learning of Internet traffic to improve network structure and routing algorithms, to increase communication speed and to decrease energy usage (Green Internet); data based speech and signal processing.
- Medical image analysis using artificial intelligence and machine learning algorithms, integration of genomic, proteomic, metabolomic data with clinical image analysis, big data science applied to medical imaging, etc.