SPiNCOM

Signal Processing in Networking and Communications

Research

Current Research Thrusts

  • Data Science and Big Data Analytics

    • Estimation, tracking, and feature extraction on a budget

    • Randomized and data-driven algorithms for classification and clustering

  • Learning and Inference over Features and Graphs

            • Crowdsourcing and ensemble Gaussian processes with scalability and robustness

            • Bayesian optimization, online, active, reinforcement, deep and meta-learning

  • AI-aided Wireless Communications

    • Spatio-temporal cartography for spectrum sensing

    • Meta-learning aided scheduling and resource allocation

  • Data-driven Power Networks

    • Machine learning for grid analytics and power management

    • Dynamic state estimation and power flow using deep neural networks