Susan Wei

Susan Wei is an Associate Professor in the Department of Econometrics & Business Statistics at Monash University. Her research focuses on machine learning theory, fairness in AI, causal inference, and Bayesian methods. She leads two active research projects: 'Deep Learning Theory' funded by Google (Singapore) and 'Making Machine Learning Fair(er)' supported by the Australian Research Council (ARC). Her work contributes to UN Sustainable Development Goals through ethical AI applications. Key collaborations include international institutions like the ARC and top universities globally.

Wei's research explores the mathematical foundations of deep learning, addressing challenges in optimization, fairness, and interpretability. Notable contributions include developing variance reduction techniques in variational inference and advancing interventional fairness frameworks using causal graphs. Her projects aim to improve algorithmic transparency and ethical AI deployment across industries.

Her grants include a 2020-2025 ARC grant (Making Machine Learning Fair(er)) and a Google-funded initiative starting in 2024. Though no formal advisees are listed, she collaborates with researchers like Zuo, Gong, and Lau on high-impact papers. Her work is published in top venues like IEEE Transactions and the International Conference on Learning Representations (ICLR).