LIU Peng

LIU Peng is an Assistant Professor of Quantitative Finance (Practice) at the Lee Kong Chian School of Business, Singapore Management University. He holds a Ph.D. in Statistics and Data Science (Part-time) from the National University of Singapore (2021), an M.S. in Business Analytics (2015), and a B.Eng. in Electronic Science and Technology (2012). Prior to his academic role, he worked as a Manager at Standard Chartered Bank (2019–2022) and in analytics roles at Marina Bay Sands and IBM.

• Education: Ph.D. (NUS), M.S. (NUS), B.Eng. (Beijing Technology and Business University)

His research focuses on generalization in deep learning, sparse estimation, portfolio optimization via reinforcement learning, financial text mining, risk management, and Bayesian optimization. His work bridges theoretical advancements with practical applications in quantitative finance and data science.

Notable contributions include studies on explainable neural networks, Bayesian optimization frameworks for portfolio management, and risk analytics integrating human decision-making. His recent articles emphasize model risk assessment, cost-aware optimization, and financial data analysis.

• Awards: Best Ph.D. Graduate Research Award (NUS, 2020), Google TensorFlow Developer Certificate (2020–2023)

He teaches courses in quantitative finance, machine learning, and risk management, and has secured grants including the Research Capability Building Fund (2023–2025). His research aligns with strategic priorities in digital transformation and financial innovation.