Teaching & Mentoring

My teaching philosophy focuses on combining theoretical machine learning foundations with hands-on, research-driven projects. I am passionate about training the next generation of engineers and researchers in Trustworthy AI.

💻 Courses Taught

Below are the courses I currently teach or have recently taught at Jilin University, categorized by level.

Undergraduate Level (Core & Electives)

• ae22212403: Machine Learning
  Focus: Linear Regression, Log-logistc Regression, Neural Networks, Clustering.
• ae22551007: Machine Learning B
  Focus: Linear Regression, Log-logistc Regression, Neural Networks, Clustering.

📖 Mentoring & Advising

I actively mentor students at all levels. Mentoring is deeply integrated with our lab's research projects, giving students exposure to real-world academic research pipelines.

• Graduate Students: Current PhD and Master's students are listed on the Group Page.
• Undergraduate Research: I usually supervise 8-10 undergraduate theses or capstone projects each year. Topics are often tied to fairness-aware algorhitms, graph anomaly detection or small GNN application prototypes.