Main Research Areas

The WISENET Centre covers both Fundamental Research (theoretical foundations and algorithm design), as well as Applied Research (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
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  • Distributed computation and inference over networks
  • Decentralized processing for graph signal processing
  • Distributed control for sensor and actuator networks
  • Parallel optimization and deep learning methods
  • Distributed Data Ledger systems
  • Cooperative algorithms for Collaborative Robots
  • Autonomous IoT Devices and Cyber-physical systems
  • Local processing and distributed inference for UAVs
  • FPGA-based and GPU-based cyber-physical systems
  • 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
  • Protocol Design for Wireless Communication & Sensor Networks
  • Energy Harvesting for Wireless Embedded Systems & IoT Devices
  • Data mining for prediction and reasoning in wireless networks
  • Complexity analysis and algorithms for NP-Hard network problems
  • Implementation in Software-Defined Radios