Emerging career researcher in asset pricing and machine learning at Bond University (PhD in Computational Finance). My research integrates financial theory, econometrics, and deep learning to examine the persistence of value and momentum effects across global markets and in emerging contexts such as cryptocurrencies, using large-scale market data and advanced programming in R and Python. I am broadly interested in capital market phenomena from both behavioural and theoretical perspectives, applying flexible, assumption-light modelling approaches to re-examine widely accepted paradigms in finance. I also teach and design industry-engaged subjects in financial trading systems, deep learning, and data analytics, incorporating industry platforms to connect quantitative finance theory with applied practice.