My teaching philosophy: Caring -- caring about students as individuals, caring students’ learning experience, and caring about the materials that I teach, to empower students for impactful careers in an increasingly AI-driven world.
I teach actuarial data science and responsible AI for business decision-making via real-world project-based learning. By collaborating with industry partners, I incorporate contemporary industry challenges into the course syllabus to offer a unique industry-engaging experience for students.
Presenting the Datathon Industry Challenge, bringing together industry partners, students, and academics to tackle real-world problems.
Open Learning Resource, [datascience.feihuang.org]
This Open Learning Resource for Actuarial Data Science presents an end-to-end problem-solving framework that applies data science techniques to real-world business challenges.
The course features industry-based Datathon case challenges, designed around a single, coherent business problem explored throughout the term. Multiple industry partners contribute diverse perspectives, including data and domain expertise, consulting practice, and entrepreneurship, providing students with a holistic and practical learning experience.
An open-course organised by the Guanghua School of Management, Peking University
Focusing on AI fairness, explainability and privacy preservation, this fully online workshop combines theoretical frameworks with hands-on practice using R and Python.
📆 Aug 10 – Sep 4, 2026 | Mon & Thu, 18:00 (GMT+8)
🗣 Taught in Chinese | Free admission
Read more information about the program here.
Course videos can be accessed here.
This program brought together 288 students from 152 academic majors and 124 universities across China and abroad.
Teaching in Tune is an AI-assisted playlist that turns quantitative ideas from machine learning into songs that are memorable, human, and fun to learn from. Tracks tie to ACTL4305/5305 (Actuarial Data Science Applications).
Pet Insurance Pricing Factors: Gaining a Competitive Market Share