Curriculum Vitae

Anjana Yatawara is Assistant Professor of Statistics at California State University, Bakersfield. He completed his Ph.D. in mathematics, statistics emphasis, at Missouri University of Science and Technology in 2023, on time series with conditional heteroscedastic structure. His research spans time series and financial econometrics, statistics for artificial intelligence, AI in mathematics and statistics education, and environmental statistics. At CSUB he founded and leads the Hub for Statistics, Applied AI, and Data Science Innovation, coordinates the department’s introductory statistics courses, and mentors undergraduate researchers who have been first and co-first authors on peer-reviewed papers in environmental statistics and environmental health.

Research areas

• Time series, stochastic modeling and financial econometrics

  Statistical methodology for dependent and dynamic data: volatility modeling, count-valued time series, and high-frequency and multi-frequency processes, with applications in finance, economics, and the sciences.

• Statistics for artificial intelligence

  Methods for evaluating the reliability and uncertainty of AI systems, with emphasis on large language models, prediction, inference, and decision-making.

• Artificial intelligence in mathematics and statistics education

  Empirical and methodological research on the responsible integration of generative AI into education, with emphasis on mathematical and statistical reasoning, learning outcomes, assessment, and AI-supported tutoring.

• Environmental statistics and data science

  Statistical modeling of air quality, pollutant exposure, environmental inequality, spatiotemporal processes, sensor and monitoring networks, and heterogeneous environmental data.

Across these areas he works with students through the full research process, from data analysis and statistical computing to scientific writing and publication, and collaborates with researchers in other disciplines on methodological and applied problems. Full treatment of the research lives on the research page.

Program-building at CSUB: an interdisciplinary Hub and its colloquium series, coordination of the department’s introductory statistics courses, new and proposed curriculum in statistical data science, and the research computing behind them.

• 2025–present

  Founder & Faculty Lead, CSUB Hub for Statistics, Applied AI & Data Science Innovation

  • Founded and leads an interdisciplinary Hub supporting statistics, applied AI, data science, student research, research computing, and cross-disciplinary collaboration.
  • Established a physical home for the Hub and developed computing infrastructure supporting undergraduate and faculty research.

• 2025–present

  Founder & Organizer, Statistics, Applied AI & Data Science Colloquium Series

  • Founded and organizes an interdisciplinary colloquium series bringing external researchers and professionals to CSUB to engage students and faculty in statistics, data science, AI, scientific computing, and applied research.
  • Organized the colloquia held to date: Thomas A. DeFanti on CENIC AIR and the National Research Platform (November 2025); Bhash Abeysinghe of the American Institutes for Research on AI, NLP, and agentic systems (April 2026); and two NASA Ozone Where We Live research scientists on environmental data science (September 2026).

• 2026–present

  Statistics Coordinator, Department of Mathematics

  • Coordinates MATH 1209: Statistics in the Modern World and MATH 2200: Introduction to Statistical Concepts and Methods across multiple sections, including course expectations, content coverage, shared resources, instructor support, and communication.
  • Developed a shared instructional system for MATH 2200 and MATH 1209 with course materials, R resources, assignments, assessments, classroom activities, projects, and browser-based statistical computing through CSUB JupyterHub.

• 2025–2026

  Co-Developer & Instructor, MATH 4230: Applied Statistical Methods for Data Science

  • Co-developed MATH 4230 with Statistics faculty as an upper-division applied statistics and data science course and taught it in Spring 2026.
  • Developed the Spring 2026 implementation: syllabus, instructional materials, computational labs, assessments, and an open-ended capstone centered on real data, reproducible workflows, and statistical communication. Used R, Python, JupyterHub, and structured approaches to responsible AI use.
  • Participated in the 2026 National Workshop on Data Science Education at UC Berkeley to benchmark the course and the broader curriculum.

• 2025

  MATH 3218: The Science of Data, Statistics, and Artificial Intelligence

  Participated in faculty review and refinement of the new upper-division GE course led by Dr. Eduardo Montoya, and served as the named proposer responsible for entering and advancing the proposal through CourseLeaf.

• 2025–present

  Statistical Data Science concentration and proposed B.S. in Statistical Data Science

  • Works with Statistics and Mathematics faculty on CSUB’s Statistical Data Science curriculum, including the existing concentration and the current effort to develop a standalone B.S.
  • Contributed degree requirements, prerequisite structure, elective pathways, comparisons with programs at other universities, student-demand survey analysis, and proposal development.

• Initial proposal

  Proposed general education course — Inside AI: The Mathematics of Large Language Models

  • Developed an initial proposal and course material for a lower-division Area 2: Mathematical Concepts & Quantitative Reasoning course that teaches mathematics and statistics through the inner workings of modern language models.
  • Covers tokens, embeddings, vectors and matrices, attention, probability, sampling, uncertainty, numerical precision, quantization, model size, and statistical evaluation. The concept adapts hands-on small-model teaching ideas encountered through Eric Van Dusen’s UC Berkeley / NWDSE materials to a mathematics-and-statistics GE setting.

• 2026–present

  Founder & Organizer, CSUB AI & Data Science Research Group

  Established a cross-departmental faculty research group connecting statistics, computer science, artificial intelligence, institutional research, and related areas; organizes research meetings and supports collaborative projects, student involvement, and grant opportunities.

• 2025–present

  Research computing and AI infrastructure development

  • Contributed to research-computing infrastructure supporting statistics, data science, and AI research at CSUB, including connection to the National Research Platform / Nautilus ecosystem for GPU and high-performance computing.
  • Participated in CSUB’s AWS Cloud & AI initiative, contributing statistical evaluation and benchmarking, curriculum-integration ideas, and student-training plans to a project supported by substantial AWS cloud-computing credits.

• 2025–present

  AI and data science workshops and training

  • Developed and delivered a sustained program of workshops, seminars, and training activities on responsible and useful applications of generative AI in teaching and research.
  • Selected activities: Teaching With AI: Helping Students Learn Statistics With Custom GPTs and Prompts; AI as a Thinking Partner in Statistics; Effective Ways to Introduce AI in Your Classroom at CSUB.
  • Developed course-specific AI tutoring approaches to support mathematical and statistical reasoning, and contributed to broader campus AI activities including OpenAI University Day at CSUB.

Undergraduate research at CSUB runs through scholar programs, sustained individual supervision, and the graduate-pathway work that follows it. Several of these students are first, co-first, or contributing authors on peer-reviewed papers in environmental statistics and environmental health.

Undergraduate research scholar programs

• 2024, 2025

  Faculty Research Mentor, CV Pathway — Summer Research Apprenticeship for Doctoral Programs

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

• Summer 2025

  Faculty Research Mentor, Chevron Summer Undergraduate Research Experience (SURE)

  A Customizable AI Pipeline for Academic Excellence: Locally Hosted Language Models in Higher Education.

  Mentored undergraduate researchers in the development and evaluation of locally hosted large language models for higher education, including retrieval-augmented generation (RAG), model fine-tuning, quantization, GPU-based deployment, and comparison with commercial cloud-based AI systems.

• 2025–2026

  Principal Investigator & Undergraduate Research Mentor, CES Mini-Grant

  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 contributed to multiple peer-reviewed publications in environmental statistics and environmental health.

Individual undergraduate research supervision

• 2024–2026

  Tom Regpala

  Environmental statistics, air-pollution exposure inequality, statistical computing, and environmental data integration. Began through CV Path 2024 and continued as a sustained research collaboration. Student co-first author on peer-reviewed work published in Atmospheric Environment: X; continued mentoring included research writing and doctoral-study preparation.

• 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 Path 2025 Research Scholar. Supervised hybrid GRU-CNN influenza forecasting, computational implementation, statistical evaluation, and manuscript development.

• 2025–2026

  Emily DeJesus

  Environmental data science; CV Path 2025 Research Scholar. Supervised literature review, environmental and demographic data analysis, interpretation, research writing, and poster preparation; continued graduate-school and research-pathway mentoring.

• 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 undergraduate research through the CSUB Mathematics Seminar.

• Fall 2026–present

  Chase Davis & Brian Martinez

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

Student research presentations and competitive achievements

• February 2026

  CSU Channel Islands Plot-A-Thon

  • Mentored and helped organize CSUB student participation, including recruitment, team formation, funding, travel, and lodging coordination.
  • CSUB Team 1 — Juancarlos Sandoval, Krrithik Ezhilarasan, Christine Leanna Bonoan, and Sean Toledo — won Best Overall, Best in Data Analysis, and Best in Data Communication.

• November 2025

  CSUB Mathematics Seminar — Undergraduate AI Research

  Mentored Tom Regpala, Juan Rodriguez Aguilar, and Christian Rodriguez in presenting undergraduate AI and data-science research; Aguilar and Rodriguez presented CSUB-GPT: Open-Source Local LLMs for Campus Use (November 19, 2025).

• 2025

  Joint Statistical Meetings

  Undergraduate research with Noah Gallego contributed to presented work on hybrid deep-learning methods for forecasting influenza-like illnesses.

• 2024–2025

  CV Path Research Symposia

  Supervised preparation of undergraduate research reports, posters, and presentations associated with the CV Path research program.

Graduate and professional pathway mentoring

• 2025–2026

  CSU Chancellor’s Doctoral Incentive Program (CDIP)

  Faculty mentor and recommender for Tom Regpala’s 2026–27 CDIP doctoral-pathway application.

• 2025

  Cal-Bridge graduate pathway mentoring

  Supported Emily DeJesus in pursuing Cal-Bridge and communicated with program faculty regarding her research preparation and graduate-school pathway.

• Ongoing

  Graduate school and career mentoring

  Mentors undergraduate researchers in graduate and Ph.D. applications, research CVs, statements of purpose, fellowships, internships, employment applications, and letters of recommendation.

Regional research collaboration

• 2026–present

  Local, Task-Specific Language Model for Automated Essay Grading

  Collaboration with Dr. Jonathan P. Brown, Professor of Mathematics, Bakersfield College · Bakersfield, CA.

  • Developing a resource-efficient local language model for an existing automated essay-grading application, with shared computing resources and participation of Bakersfield College student researchers.
  • Investigating neural-network, small language model, and model-distillation approaches for task-specific essay grading and evaluation.

The same record is on the publications page.

Professional

• 2026–present

  Member, ADSA AI Tutoring Study Working Group, Alliance for Data Science and AI

  Multi-institution working group examining AI tutoring and AI-supported learning in statistics and data science education.

• 2026–2027

  Mentor, ASA Section on Statistics and Data Science Education (SSDSE) Mentoring Program

  American Statistical Association.

• 2026

  Program Committee Member and Reviewer, AIxHEART 2026

  Artificial Intelligence × Humanities, Education, and Art.

• 2026

  Reviewer, IEEE International Conference on Tools with Artificial Intelligence (ICTAI)

University

• 2026–2027

  Academic Affairs Committee (AAC), Academic Senate

  Appointed member of the university standing committee concerned with academic policy, programs, curricula, and related academic matters.

• 2026–2027

  General Education Curriculum Committee (GECCo)

  Elected by acclamation as a Mathematics/NSME representative to complete an existing term, May 2026–May 2027.

Department

• 2026–present

  Founding Faculty Advisor, CSUB Data Science & Applied AI Society

  Recruited founding student officers and guided development and registration of the new student organization.

• 2024–2025

  Mathematics Department Website Subcommittee

  Member; coordinated collection of faculty and staff information and distributed the departmental faculty and staff webpage survey.

Outreach and community engagement

• March 2026

  Co-Organizer, Data Science Exploration Challenge, Lee Webb Math Field Day

  Developed a new high-school data science competition, including the dataset, data dictionary, participant materials, judging framework, school communication, and event implementation.

• 2025, 2026

  Volunteer, Kern County Chapter MATHCOUNTS Competition

  Supported competition operations and student activities, including scoring support.

• March 2026

  Volunteer, Future ’Runner Day / Meet Your Major

  Represented Mathematics in prospective-student and family outreach.

• October 2025

  Volunteer, NSME Open House

  Represented the Mathematics Department to prospective students and families.

• March 2025

  Faculty Volunteer, Math Club Runner Night

More detail on leadership and service is on the leadership & service page.