Luis E. Ascencio Gorozpe

CIMAT. Centro de Investigación en Matemáticas, A.C., Jalisco S/N, Col. Valenciana CP 36023 Guanajuato, Gto, México, Apartado Postal 402, CP 36000

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Venustiano Carranza, 15900 Ciudad de México, CDMX.

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México City

I am a highly analytical Ph.D. candidate in Mathematics at CIMAT, leveraging 7+ years of rigorous training in Probability, Statistics, and Mathematical Modeling to solve complex, high-dimensional data problems. I am dedicated to bridging advanced theoretical knowledge with robust industrial applications in Data Science, Machine Learning, and Data Engineering.

I am actively pursuing professional certifications to align my academic expertise with industry best practices. My current focus includes obtaining Data Analyst certifications in cloud environments (GCP and AWS), and completing specialized courses to acquire Databricks certifications for massive and distributed computing using Spark and PySpark. This ensures proficiency in scalable data architecture and deployment technologies.

My doctoral research at CIMAT is centered on advanced Probability and Statistics, with a practical emphasis on Machine Learning (ML) techniques, high-dimensional statistics, and dimensionality reduction. I specialize in developing and applying cutting-edge methodologies for time series analysis and the statistical modeling of complex, non-Euclidean data structures. I have also gained pedagogical experience as a Teaching Assistant for graduate courses, including Statistical Models, Programming (Python/R), Time Series, Statistical Inference, and Statistical Computing.

My academic journey provides a strong foundation in core analytical disciplines:

  • Master of Science (Pure Mathematics, UAM): Deepened expertise in Measure Theory (essential for rigorous Probability), Linear Algebra, and Numerical Methods.
  • Bachelor of Science (Mathematics, UAM): Coursework included Probability & Statistics, Mathematical Analysis, Linear Algebra, and Numerical Analysis. Crucially, during this period, I collaborated with the UAM Visualization and Parallel Computing Laboratory, gaining early exposure and hands-on knowledge in supercomputing and cloud computing environments.

My goal is to transition my expertise in statistical rigor and computational efficiency into a high-impact role as a Data Scientist, Data Engineer, or Senior Data Analyst.