Teaching
Teaching Philosophy
My teaching aims to equip students with the computational, analytical, and systems-thinking skills needed to thrive in a rapidly evolving world. Through data, modeling, and hands-on projects, I hope students develop the adaptability to learn new technologies and tackle emerging real-world challenges.
Courses
Students learn how to analyze and model complex systems using network science, data-driven methods, and computational tools. The course combines methodological foundations with applications across social, biological, technological, and population systems. The main topics include:
- Network Structures and Properties
- Centrality Measures
- Network Optimization
- Network Flow
- Graph Partitioning
- Community Detection
- Dynamic Networks