Antonio Aguirre Data Modelling·Bayesian Statistics·Machine Learning

Antonio Aguirre

Welcome

Hello! I’m Antonio Aguirre, a dedicated Ph.D. candidate at the University of California, Santa Cruz. Under the mentorship of Dr. Bruno Sansó and Dr. Raquel Prado, I specialize in Bayesian Statistics, Machine Learning, and Spatio-Temporal Modeling. My research focuses on developing scalable methods for inference and forecasting, emphasizing interpretable and operational models for real-world applications.

I completed my Bachelor’s and Master’s degrees at Instituto Tecnológico Autónomo de México (ITAM). My undergraduate in Applied Mathematics had an emphasis on Numerical Analysis, while my graduate studies in Economics focused on Econometrics.

I'm always actively looking for new interdisciplinary projects and collaborations. Feel free to reach out to me!

Research Interests

  • Spatio-Temporal Modeling: Developing interpretable models for high-dimensional spatio-temporal data with applications in climate and environmental science.
  • Dynamic Quantile Regression: Innovating scalable, fast quantile-based inference and forecasting.
  • Continual Learning: Exploring Sequential Monte Carlo (SMC) methods and variational approaches for real-time model updating.
  • Operational Methodologies: Building efficient, scalable workflows for forecast correction, synthesis, and real-time decision-making.

Real-Time Monitoring: San Lorenzo River Discharge Flow

Note: This plot provides real-time monitoring of the San Lorenzo River's discharge flow at Big Trees. The data updates automatically every ten minutes. Stay tuned as I plan to add more features and insights to this visualization, reflecting my ongoing research.
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