Dr. Bilal Aslam
The Business School

Dr. Bilal Aslam

Dr. Bilal Aslam

Bilal Aslam is an accomplished academic with a PhD in Finance from Curtin University. His doctoral research, titled “Machine Learning for Capital Market Research and Portfolio Optimization,” delved into the application of advanced computational techniques to equity portfolio construction and decision-making. Prior to his PhD, Bilal completed an MPhil in Economics and Finance at Curtin University, focusing on “Weak Euler Scheme for Stochastic Differential Equations with Applications in Finance.” His academic journey began with an MSc in Financial Mathematics (with distinction) from the University of Sussex, providing a strong foundation in mathematical finance.

Bilal has a strong multidisciplinary background in finance, mathematics and computing, and he teaches courses in quantitative and computational finance. His research interests encompass derivatives, portfolio management, and applications of machine learning in finance.

ACADEMIC QUALIFICATIONS  

  • Doctor of Philosophy (2020 – 2024), Curtin University, Malaysia. Thesis: Machine learning for capital market research and portfolio optimization
  • Master of Philosophy (2017 – 2019), Curtin University, Malaysia. Thesis: Weak Euler scheme for stochastic differential equations with applications in finance
  • Master of Science (2014 – 2015), University of Sussex, England (UK). Degree Title: MSc in Financial Mathematics

PROFESSIONAL APPOINTMENTS    

  • British University Vietnam (BUV) 
    Lecturer in Finance (2024 – Current)
  • Curtin University (Malaysia) 
    Research Assistant (2017 – 2024)
    Research area: Machine learning in equity portfolio management

RESEARCH AREAS / FIELDS 

  • Derivatives
  • Portfolio Management
  • Machine Learning in Finance

RESEARCH PUBLICATIONS 

  • Aslam, B., & Zhang, C. (2022) – A strengthened solution to option manipulation. INFOR: Information Systems and Operational Research, 60(3), 407-427.
  • Aslam, B., Bhuiyan, R. A., & Zhang, C. (2023) – Portfolio construction with k-means clustering algorithm based on three factors. In MATEC Web of Conferences.
  • Aslam, B. (2025). Identifying optimistic stocks with K-means clustering algorithm. International Review of Economics & Finance, 104579.

RESEARCH GRANTS

  • Aslam, B., & Zhang, C. (2022) – Sarawak Digital Economy Corporation (SDEC). A deep learning-based application for asset pricing and portfolio optimization incorporating option valuation. ($20,500)
  • Aslam, B. & Bhuiyan, R.A. (2023)  – Curtin University Research Grant. Long-short term memory (LSTM) based decision support system for financial portfolio construction. ($2,500)
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