Francisco Rau
Efficient MAC scheduling for ultra-dense wireless sensor networks based on 802.11 standard
Current work: Develop traffic modeling approaches aimed at effectively implementing artificial intelligence techniques, specifically for network traffic classification. Applying AI-driven embedded systems techniques, emphasizing real-time data processing and hardware acceleration strategies to achieve optimal performance. Additionally, I am actively exploring innovative incremental learning methods to dynamically adapt and enhance the capabilities of existing models. A key objective of my research is to seamlessly integrate these AI techniques into MAC scheduling frameworks, specifically tailored for ultra-dense network environments, with the goal of significantly improving WiFi network efficiency and performance.
List of Publications
2026
- L.M. Giraldo, J. Perez, R. Garcia, A. Pouralizadeh, V. Jungnickel, F. Rau and C. Herranz, “A SDN-Based Access Control Framework for Powerline Communications Networks”, In 2026, the IEEE 15th International Symposium on Communication Systems, Networks and Digital Signal Processing. DOI
- F. Rau, P. Georgieva, C. Herranz, I. Val and J. Perez, “Incremental Learning in Network Traffic Management: A Fixed-Representation Rehearsal Approach“, In 2026, the IEEE 15th International Symposium on Communication Systems, Networks and Digital Signal Processing. DOI
2025
- F. Rau, L. M. Giraldo, C. Herranz, J. Perez, I. Val and R. Garcia, “Implementing a Traffic Classifier on Embedded SoC Systems with Deep Learning Processor Unit,” 2025 International Conference on Software, Telecommunications and Computer Networks (SoftCOM), Split, Croatia, 2025. DOI
- F. Rau, C. Herranz, I. Val and J. Perez, “LSTM-Based Traffic Prediction for 5G Mobile Network Operator,” 2025 International Conference on Software, Telecommunications and Computer Networks (SoftCOM), Split, Croatia, 2025. DOI
Preprints
- F. Rau, C. Herranz, I. Val, P. Georgieva, J. Perez, “A Novel Flow-Based Online Network Traffic Classification Using Machine Learning,” TechRxiv, 2025. DOI
Datasets
Rau, F., Herranz, C., Val, I., & Perez, J. (2025). “VLC Data: A Multi-Class Network Traffic Dataset Covering Diverse Applications and Platforms“ [Dataset]. https://doi.org/10.5281/ZENODO.15121417Background
I hold a B.Eng. degree in Electrical and Electronics Engineering from Universidad de Santiago de Chile in 2009, a B.Sc. degree in Industrial Engineering from Universidad Tecnica Federico Santa Maria in 2017, and M.Sc. degree in Electrical Engineering from Universidad Santiago de Chile in 2023.
I have worked as Satellite Engineer and Project Engineer in Chile, FTTH Engineer in Ecuador. In my last job I worked as a Senior Project Manager, implementing projects such as 5G NSA, SDN Network, MPLS/IP Core Network Expansion at a Telecommunications Service Provider in Chile.