Fei is a Senior Lecturer in the School of Risk and Actuaries Studies and Lead - Data and AI Tech at UNSW Business AI Lab. She received her BSc. in Mathematics from Xiamen University, MPhil in Actuarial Science from the University of Hong Kong, and PhD in Actuarial Studies from the Australian National University. Before joining UNSW in 2020, she was a faculty member at the Australian National University.

In her research, Fei focuses on responsible AI and data-driven decision-making, especially for the insurance industry, utilizing tools from statistics, machine learning, economics, and marketing. Her research interests include fair and non-discriminatory insurance pricing, algorithmic bias, interpretable machine learning, mortality modelling, and customer relationship management. She particularly explores ways to make insurance equitable, affordable, and sustainable in the contexts of AI and climate change. Her work has been published in leading actuarial journals. Fei has received the Carol Dolan Actuaries Summit Prize and the ASTIN Colloquium Best Paper Award for her research on anti-discrimination in insurance pricing. In 2023, she was honoured with the Actuaries Institute's Volunteer of the Year Award in the Spirit of Volunteering category and the UNSW Business School SDG Research Impact Award.

Fei teaches actuarial data science and statistical machine learning at UNSW.  By collaborating with industry partners, she incorporates contemporary industry challenges into the course syllabus to offer a unique industry-engaging experience for students via Sandbox Projects. Her educational excellence has been recognized by winning the UNSW John Prescott Award for Outstanding Teaching Innovation (2022), the ANU Vice Chancellor’s Award for Teaching Excellence in the Early Career Category (2018) and the ANU College of Business and Economics Award for Teaching Excellence in the Early Career Category (2017).  Fei is a Senior Fellow of Advance HE (SFHEA).

Fei works with insurers, consulting firms, and government agencies for transformative research and education projects, covering a wide range of topics. Examples of such collaborations include mortality modelling, fairness metrics for life insurance, Interpretable and fair insurance pricing using causal models, personalised customer management, bushfire risk modelling, multi-coverage bundled insurance pricing, claims inflation forecasting, and property insurance pricing with high-cardinality features.