Main Research Areas
- Data science
- Robust statistical inference and learning
- Graph signal processing for data-driven systems
- Sparse signal representations and dimensionality reduction
- Inference-aware data compression
- Geometric deep learning
- Design and implementation of machine learning methods for embedded systems
- Distributed computation and inference over wireless networks
- Decentralized processing for graph signal processing
- Cross-layer network algorithms for collective intelligence
- Parallel optimization methods
- Distributed control for sensor and actuator networks
- FPGA-based cyber-physical systems and sensor networks
- Statistical learning for power spectrum and channel gain cartography
- Advanced convex and non-convex optimization for multi-objective resource allocation in wireless networks
- Adaptive algorithms for networks based on reinforcement learning
- Data mining for prediction and reasoning in wireless communications
- Information Science of complex networks
- Complexity analysis and approximation algorithms for NP-Hard network problems