Teaching & Mentoring

I view mathematics as a tool for understanding biological systems and solving real-world problems. In teaching mathematical epidemiology and applied mathematics, I emphasize connections among mathematical structure, biological interpretation, computation, and public-health questions. I aim to create an inclusive learning environment in which students from different disciplinary backgrounds can engage with mathematical ideas and develop confidence in applying them.

Teaching Experience

  • Guest Lecturer, MIC 433/533: Medical and Molecular Virology, The University of Arizona, Tucson, AZ, USA, Spring 2026.
  • Guest Lecturer, MATH 586: Case Studies in Applied Mathematics, The University of Arizona, Tucson, AZ, USA, Spring 2026.
  • Co-Instructor, MIC 433/533: Medical and Molecular Virology, The University of Arizona, Tucson, AZ, USA, Spring 2025.
  • Teaching Assistant, MAT 401: Linear Algebra, Central University of Rajasthan, Ajmer, Rajasthan, India, Spring 2023.
  • Teaching Assistant, MAT 407: Qualitative Theory of Ordinary Differential Equations, Central University of Rajasthan, Ajmer, Rajasthan, India, Fall 2022.

Teaching Approach

At the University of Arizona, I have taught mathematical epidemiology to upper-level undergraduate and graduate students from biology, public health, veterinary science, medicine, and related disciplines. I introduce mathematical models through biological questions and connect model equations and parameters to their epidemiological interpretation.

My teaching has included SIR/SIRS and related compartmental models, reproduction numbers, transmission dynamics, immunity, and intervention modeling. I have designed interactive classroom activities and guided R programming exercises in which students simulate outbreaks, vary epidemiological parameters, compare model structures, and interpret resulting disease dynamics.

I use group discussions, problem-solving activities, quizzes, coding exercises, and formative and summative assessments to identify challenging concepts, provide feedback, and adjust instruction when needed.

Research Mentoring

Ash Ellen Maxwell

Undergraduate Researcher, Fall 2025 – Spring 2026

I mentored an undergraduate research project developing a mechanistic age- and sex-structured model of bovine tuberculosis in Michigan deer. My mentoring included guidance on mathematical model formulation, epidemiological interpretation, simulation of disease dynamics in R, research communication, and presentation of results.

The project was disseminated through five poster presentations, including the Conference of Research Workers in Animal Diseases (CRWAD) and University of Arizona events such as the Undergraduate Research Opportunities Consortium (UROC) Colloquium, GIDP/AWARDSS Research Showcase, School of Animal & Comparative Biomedical Sciences (ACBS) Poster Session, and Ecology and Evolutionary Biology (EEB) 50th Anniversary Poster Session.

Undergraduate Biology Research Program

Small Group Co-Leader, Spring 2026

Through the Undergraduate Biology Research Program (UBRP) at the University of Arizona, I co-mentored undergraduate researchers through small-group discussions on research progress, challenges, professional development, and preparation for graduate study.

I also led workshops on research-topic pitches, scientific abstracts, conference selection, poster preparation and presentation, statements of purpose, CVs and resumes, recommendation-letter requests, and graduate-school applications.

Mentoring Philosophy

My mentoring approach emphasizes clear communication, mutual respect, realistic expectations, and increasing research independence. I aim to help students understand not only how to complete a particular analysis or model, but also how to formulate scientific questions, evaluate assumptions, communicate results, and develop confidence as independent researchers.

Teaching Interests

I am interested in teaching courses in:

  • Mathematical Epidemiology
  • Dynamical Systems
  • Ordinary and Delay Differential Equations
  • Linear Algebra
  • Data-Informed Modeling in Biology and Public Health