Antonio De Leon
I am a Ph.D. candidate in Statistics at the University of California, Santa Cruz, advised by Bruno Sansó and Raquel Prado. I work on Bayesian forecasting, quantile methods, and statistical software, with emphasis on uncertainty quantification, approximate and simulation-based inference, and reproducible R/Python workflows. Current projects include forecast correction for environmental products used in risk assessment, dynamic quantile state-space models, Bayesian Quantile Deep Echo State Networks, and mean-tilted interval methods.
Applied and Professional Experience
- Computer Systems Coordinator, UCSC Statistics: Administer Linux research servers and build automation for research workflows (2024–present).
- Quantitative Researcher, Delos Financial Technologies: Built evaluation workflows, automated backtests on AWS, and standardized model diagnostics (2025).
- Data Analyst, NeatLeaf Inc.: Developed data pipelines and spatiotemporal models for greenhouse telemetry and anomaly detection (2021–2022).
- Data Analyst, Banco de México: Built pipelines for image datasets, anomaly classification models, and forecasting prototypes (2018–2019).
Current Work
-
exdqlm: CRAN v1.1.0 R package for Bayesian quantile modeling, with a companion arXiv:2607.22760 and a manuscript submitted to Journal of Statistical Software. - Forecast correction preprint: Bayesian quantile-based correction and synthesis of environmental forecast products for risk assessment; manuscript submitted to Environmetrics.
- Q-DESN forecasting: Working paper on Bayesian quantile forecasting with fixed nonlinear recurrent features.
- MTI tolerance-interval preprint: Mean-Tilted Intervals: A Generalized-Bayes Approach to Fixed-Content and Tolerance Intervals.
- MTI regression manuscript: Mean-Tilted Intervals: Regression and Dynamic Models; submitted to arXiv; public identifier pending.
Teaching and Mentoring
- Graduate Student Instructor: Data Visualization (STAT 80B), Spring 2025.
- Teaching Assistant: Supported Probability Theory, Classical and Bayesian Inference, Statistics, and related courses (2021–present).
- UCSC Statistics TA Resources: Co-maintain the department TA wiki, a public guide for TA responsibilities, teaching practices, and course support.
- ASA DataFest Mentor: Guided student teams on modeling and communication (2023).
Education
- Ph.D. in Statistics: University of California, Santa Cruz (2021–present, expected 2026)
- M.Sc. in Economic Theory: Instituto Tecnológico Autónomo de México (ITAM) (2018–2020)
- B.Sc. in Applied Mathematics: Instituto Tecnológico Autónomo de México (ITAM) (2014–2018)
Beyond Research
Outside work, I enjoy baking bread, cooking Mexican food, reading history and philosophy of science, and studying German.
For collaboration, questions, or related work, the Contact page lists the best ways to reach me.