LIU Peng
Education
2021 Ph.D. in Statistics and Data Science (Part-time)
National University of Singapore
2015 M.S. in Business Analytics (Full-time)
National University of Singapore
2012 B. Eng. in Electronic Science and Technology (Full-time)
Beijing Technology and Business University
Current Position (s) Held
2022 - Now Assistant Professor of Quantitative Finance (Practice)
Lee Kong Chian School of Business, Singapore Management University
Apr 2019 - Jun 2022 Manager, Advanced Analytics
Standard Chartered Bank, Singapore
Aug 2015 - Apr 2019 Analytics Manager
Marina Bay Sands, Singapore
Jan 2013 - Jul 2014 Technical Support
IBM, China
Research Interests
Generalization in deep learning, sparse estimation, portfolio optimization using reinforcement learning, financial text mining, risk management, Bayesian optimization
Awards and Certificates
Best Ph.D. Graduate Research Award, Department of Statistics and Data Science, NUS, 2020
National Scholarship of China, School of Computer and Information Engineering, BTBU, 2009
Google TensorFlow Developer Certificate, 2020 - 2023
Project Management Professional, 2013 - 2017
Publications
- Peng Liu. Seeking Better Sharpe Ratio via Bayesian Optimization. Journal of Portfolio Management (JPM), 2023
- Peng Liu, Haowei Wang, Qiyu Wei. Bayesian Optimization with Switching Cost: Regret Analysis and Lookahead Variants. International Joint Conference on Artificial Intelligence (IJCAI), 2023
- Peng Liu. An Integrated Framework on Human-in-the-Loop Risk Analytics. The Journal of Financial Data Science (JFDS) 5 (1): 58-64, 2023
- Peng Liu. A Review on Derivative Hedging using Reinforcement Learning, The Journal of Financial Data Science (JFDS) 5 (2): 136-145, 2023
- Chen Zichuan,Peng Liu. Towards Better Data Augmentation using Wasserstein Distance in Variational Auto-encoder, IEEE International Conference in Image Processing (ICIP), pp. 81-85, 2022
- Peng Liu, Ying Chen, Chung-Piaw Teo. Limousine Service Management: Capacity Planning with Predictive Analytics and Optimization, INFORMS Journal on Applied Analytics (IJAA), Vol. 51. No. 4, 2021
Books
- Peng Liu, Practical Bayesian Optimization: Theory and Practice Using Python, Apress, 2023
- Peng Liu, Regularization in Deep Learning, Manning Publications (to appear in 2023)
- Peng Liu, The Statistics and Machine Learning with R Workshop, Packt, (to appear in 2023)
- Peng Liu, Quantitative Trading Strategies with Python, Apress (to appear in 2023)
- Peng Liu, Deep Reinforcement Learning in Portfolio Management (work in progress)
- Peng Liu, Bayesian Complementarity in Deep Learning (work in progress)
