Statistics taught as work students do.

Undergraduates have worked with me in sustained individual research supervision since 2024, and several are authors on peer-reviewed journal articles, some as first or co-first author. The work runs from environmental statistics and exposure inequality to machine learning, forecasting, local language models, and cryptography — and it comes with the rest of it: research writing, poster and talk preparation, doctoral applications, and the long conversations about what comes next.

Research scholar programs

• 2024, 2025

  CV Pathway — Summer Research Apprenticeship for Doctoral Programs

  Faculty research mentor. Mentored Tom Regpala in 2024 and Emily DeJesus and Noah Gallego in 2025 through intensive summer research and doctoral-preparation experiences, supervising research design, literature review, data acquisition, statistical and computational analysis, research writing, and poster and presentation development. Several of these collaborations continued past the summer into sustained undergraduate research and publication.

• Summer 2025

  Chevron Summer Undergraduate Research Experience (SURE)

  Faculty research mentor. A Customizable AI Pipeline for Academic Excellence: Locally Hosted Language Models in Higher Education. Mentored undergraduate researchers in developing and evaluating locally hosted large language models for higher education, covering retrieval-augmented generation, model fine-tuning, quantization, GPU-based deployment, and comparison with commercial cloud-based AI systems.

• 2025 – 2026

  CES Mini-Grant

  Principal investigator and undergraduate research mentor. Air Pollution Disparities in California, 2000–2025: Examining Environmental Inequities Across Income, Poverty, and Minority Populations. Supervised undergraduate research in environmental statistics, air-pollution exposure inequality, statistical computing, and large-scale demographic and environmental data integration. Student research from this project contributed to multiple peer-reviewed publications in environmental statistics and environmental health.

Undergraduate researchers

• 2024 – 2026

  Tom Regpala

  Environmental statistics, air-pollution exposure inequality, statistical computing, and environmental data integration. Began through CV Pathway in 2024 and continued as a sustained research collaboration. Student co-first author on peer-reviewed work published in Atmospheric Environment: X. Continued mentoring covered research writing and doctoral-study preparation, including his 2026–27 CSU Chancellor’s Doctoral Incentive Program application.

• 2025 – 2026

  Eric Palafox

  Environmental statistics and computational data analysis. Supervised large-scale monitor–satellite air-quality analysis, R programming, statistical methodology, and reproducible workflows. Student co-first author on peer-reviewed work published in Atmospheric Environment: X.

• 2025 – 2026

  Kayla Ko

  Environmental inequality and statistical data science. Supervised research on income-based pollution-exposure disparities across California counties. Student first author on peer-reviewed work published in Environmental Research: Health.

• 2025 – 2026

  Christian Rodriguez

  Environmental data science and applied AI, supported through Chevron SURE and ELEVATE. Student coauthor on peer-reviewed work published in Environmental Research: Health, and co-presenter of undergraduate research on open-source and local large language models.

• 2025 – 2026

  Noah Gallego

  Machine learning, time-series forecasting, and computational data science; CV Pathway 2025 Research Scholar. Supervised hybrid GRU-CNN influenza forecasting, computational implementation, statistical evaluation, and manuscript development. His work contributed to research presented at the 2025 Joint Statistical Meetings and to a manuscript in progress.

• 2025 – 2026

  Emily DeJesus

  Environmental data science; CV Pathway 2025 Research Scholar. Supervised literature review, environmental and demographic data analysis, interpretation, research writing, and poster preparation, with continued graduate-school and research-pathway mentoring, including support for her Cal-Bridge application.

• 2024 – 2026

  Juan Rodriguez Aguilar

  Applied AI, forecasting, and open-source and local large language models. Supervised research development, computational experimentation, poster preparation, and communication of findings. Co-presented CSUB-GPT: Open-Source Local LLMs for Campus Use at the CSUB Mathematics Seminar.

• Fall 2026 – present

  Chase Davis and Brian Martinez

  Undergraduate mathematics research in cryptography and LLM text watermarking; the project is in its initial research-development stage.