Fernando Rodriguez Sanchez
I am currently a Senior AI Engineer at Aliy Labs, where I focus on Natural Language Processing and Agentic Reasoning. My work primarily involves integrating Large Language Models with Probabilistic Graphical Models. Before joining Aliy Labs, I worked as a Senior Research Scientist at Nielsen IQ.
I hold a PhD in Artificial Intelligence from the Polytechnic University of Madrid. My PhD focused on on learning Bayesian networks with multiple latent variables for clustering and density estimation of continuous, categorical, and mixed data. My advisors were Pedro Larrañaga and Concha Bielza.
I enjoy 3D printing and painting miniatures, mostly from the Warhammer universe.
Teaching
45+ lecture hours in Machine Learning, Deep Learning and Generative AI, including:
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LangChain for Python Development (OpenWebinars, 2024)
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Deep Learning with TensorFlow (Tokio School, 2023)
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Machine Learning with Python (Telefónica Talentum, 2020)
Publications
Journal Papers
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Rodríguez-Sánchez, F., Bielza, C., & Larrañaga, P. (2022). Multi-partition clustering of mixed data with Bayesian networks. International Journal of Intelligent Systems, 37, 2188–2218.
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Rodríguez-Sánchez, F., et al. (2021). Identifying Parkinson’s disease subtypes with motor and non-motor symptoms via model-based clustering. Scientific Reports, 11, 1–10.
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Rodríguez-Sánchez, F., Larrañaga, P., & Bielza, C. (2020). Incremental learning of latent forests. IEEE Access, 8, 224420–224432.
Conference Papers
- Rodríguez-Sánchez, F., Larrañaga, P., & Bielza, C. (2018). Discrete model-based clustering with overlapping subsets of attributes. Proceedings of the 9th International Conference on Probabilistic Graphical Models, 72, 392–403.
Technical Reports
- Rodríguez-Sánchez, F., Larrañaga, P., & Bielza, C. (2017). Multi-facet determination for clustering with Bayesian networks. Technical Report, Universidad Politécnica de Madrid.