Teaching

Teaching Philosophy

I believe that statistics and data science education should bridge the gap between theoretical foundations and real-world applications. My teaching philosophy centers on making complex statistical concepts accessible through hands-on learning, collaborative problem-solving, and the use of modern computational tools.

In my courses, I emphasize the importance of critical thinking about data, understanding the assumptions behind statistical methods, and developing the skills to communicate findings effectively to diverse audiences. I strive to create an inclusive learning environment where students feel comfortable asking questions and exploring statistical concepts through practical examples.

My background in graph-based machine learning and gen AI tools allows me to bring cutting-edge research into the classroom, helping students understand how statistics and data science are evolving in our interconnected world.