Sergio Rozada

Assistant Professor at ECE, URJC. Interested in dynamical systems, reinforcement learning, and optimization.

Conference Publications

  • Uslu Y. B., Hadou S., Rozada S., Saeedi Bidokhti S., and Ribeiro A., Graph Signal Generative Diffusion Models, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2026.
  • Rozada S., Kumarasamy V., Cavallo A., Marques A. G., Jamali-Rad H., and Isufi E., Graph-Aware Diffusion for Signal Generation, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2026.
  • Rozada S., Ding D., Marques A. G., and Ribeiro A., Deterministic Policy Gradient Primal-Dual Methods for Continuous-Space Constrained MDPs, AAAI Conference on Artificial Intelligence, 2025.
  • Navarro M., Rozada S., Marques A. G., and Segarra S., Low-Rank Tensors for Multi-Dimensional Markov Models, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025.
  • Rozada S., Rey S., Mateos G., and Marques A. G., Unrolling Dynamic Programming via Graph Filters, IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2025.
  • Rozada S., and Marques A. G., Tensor Low-Rank Approximation of Finite-Horizon Value Functions, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024.
  • Rozada S., Paternain S., Bazerque J. A., and Marques A. G., A Tensor Low-Rank Approximation for Value Functions in Multi-Task Reinforcement Learning, Asilomar Conference on Signals, Systems, and Computers, 2024.
  • Rozada S., and Marques A. G., Matrix Low-Rank Approximation for Policy Gradient Methods, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023.
  • Rozada S., and Marques A. G., Matrix Low-Rank Trust Region Policy Optimization, IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2023.
  • Rozada S., and Marques A. G., A Multi-Resolution Low-Rank Tensor Decomposition, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022.
  • Rozada S., Tenorio V., and Marques A. G., Low-rank State-action Value-function Approximation, European Signal Processing Conference (EUSIPCO), 2021.
  • Rozada S., Apostolopoulou D., and Alonso E., Load Frequency Control: A Deep Multi-Agent Reinforcement Learning Approach, IEEE Power & Energy Society General Meeting, 2020.
  • Rey S., Tenorio V., Rozada S., Martino L., and Marques A. G., Overparametrized Deep Encoder-Decoder Schemes for Inputs and Outputs Defined over Graphs, European Signal Processing Conference (EUSIPCO), 2020.
  • Rey S., Tenorio V., Rozada S., Martino L., and Marques A. G., Deep Encoder-Decoder Neural Network Architectures for Graph Output Signals, Asilomar Conference on Signals, Systems, and Computers, 2019.

Journal Publications

  • Rozada S., Orejuela J. L., and Marques A. G., Solving Finite-Horizon MDPs via Low-Rank Tensors, IEEE Transactions on Signal Processing (under review), 2026.
  • Rozada S., Wai H. T., and Marques A. G., Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning, IEEE Transactions on Signal Processing, 2025.
  • Rozada S., Paternain S., and Marques A. G., Tensor and Matrix Low-Rank Value-Function Approximation in Reinforcement Learning, IEEE Transactions on Signal Processing, 2024.
  • Rozada S., Apostolopoulou D., and Alonso E., Deep Multi-Agent Reinforcement Learning for Cost-Efficient Distributed Load Frequency Control, IET Energy Systems Integration, 2021.