Main Research Areas
The WISENET Centre covers both Fundamental Research (theoretical foundations and algorithm design), as well as Applied Research (testbed design and implementation) in different application scenarios.
- Data science
- Automated online machine learning
- Robust statistical inference and learning
- Graph signal processing for multi-variate data-driven systems
- Sparse signal representations and dimensionality reduction
- Inference-aware data compression
- Efficient and Explainable Deep learning
- Safe Deep Reinforcement Learning for data-driven control
- Computer Vision, Image Processing
- Design and implementation of machine learning methods for embedded systems
- Distributed computation and inference over wireless networks
- Decentralized processing for graph signal processing
- Autonomous Wireless Embedded Systems & IoT Devices
- Distributed control for sensor and actuator networks
- Parallel optimization and deep learning methods
- Distributed Data Ledger systems
- Cooperative algorithms for Collaborative Robots
- mmWave Sensing
- FPGA-based and GPU-based cyber-physical systems
- Local processing and distributed inference for UAVs
- Statistical learning for spectrum cartography
- Advanced Optimization and Deep Learning for resource allocation.
- Data-driven generative models for networks
- Dynamic Optimization for networks based on reinforcement learning
- Testbed design for smart Software-Defined Radios
- Protocol Implementation for Wireless Communication & Sensor Networks
- Energy Harvesting for Wireless Embedded Systems & IoT Devices
- Data mining for prediction and reasoning in wireless communications
- Complexity analysis and algorithms for NP-Hard network problems