Teaching Philosophy

I view teaching as an opportunity to equip students with the conceptual foundations, technical skills, and critical thinking abilities needed to address complex environmental challenges. My approach emphasizes student motivation, hands-on learning, and ethical use of artificial intelligence as a learning tool rather than a substitute for reasoning.

I connect course content to real-world applications, incorporate active learning strategies such as project-based labs and group discussions, and provide visual and interactive materials to support students from diverse backgrounds.

Teaching Experience

Teaching Assistant / Lab Instructor

Remote Sensing of Environment (NRE 3535)
University of Connecticut | Fall 2023

• Led weekly laboratory sessions on satellite data acquisition, visualization, and analysis using ENVI.
• Delivered guest lectures on multispectral remote sensing and satellite geometry.
• Organized group discussions and student presentations.
• Graded assignments and provided constructive feedback to support student learning.

Research Mentorship

• Mentored undergraduate and graduate students on projects involving satellite time-series analysis, machine learning, and forest disturbance monitoring.

Future Teaching Interests

I am interested in teaching courses in:

• Remote Sensing of the Environment
• Geographic Information Systems (GIS)
• Environmental Data Science and Geospatial AI

I am also enthusiastic about developing new courses that integrate satellite remote sensing, machine learning, and reproducible research workflows using Python, GIS, and cloud-based platforms.