Teaching

I teach undergraduate and postgraduate courses in physical oceanography, climate science, environmental data science, statistics, and scientific computing. My courses emphasize quantitative reasoning, computational thinking, hands-on programming, and project-based learning to prepare students for interdisciplinary research in Earth and environmental sciences.

Current Courses

The World of Computing (FOU-117)

Semester: August–December 2026
Level: Undergraduate Foundation Course

An introductory course designed to develop computational thinking through hands-on exploration of computing devices, algorithms, digital systems, and embedded electronics. Students learn fundamental computing concepts through Arduino simulations, Tinkercad, and collaborative projects, while reflecting on the broader societal impacts of digital technology.

📄 Course page: The World of Computing

Quantitative Environmental Research Methods and Biostatistics (EVS-204)

Semester: August–December 2026
Level: Undergraduate

This course introduces quantitative research methods, environmental statistics, and biostatistics using R. Students learn data visualization, probability, statistical inference, regression, hypothesis testing, and reproducible scientific workflows through analysis of real environmental datasets and project-based learning.

📄 Course page: Quantitative Environmental Research Methods and Biostatistics

Student Research

I supervise undergraduate and postgraduate research projects in

• Physical Oceanography and Climate Dynamics
• Ocean Observations and Modeling
• Environmental Data Science Applications to Weather Derivatives

Interested students are encouraged to contact me with a brief statement of research project interests and an updated CV.

Teaching Philosophy

My teaching philosophy emphasizes curiosity, quantitative reasoning, and learning by doing. I believe students learn best when mathematical concepts are connected with observations, numerical experiments, and real-world environmental problems. My courses integrate lectures with hands-on programming, data analysis, simulations, and collaborative projects, enabling students to develop both conceptual understanding and practical research skills.