LinkedIn Profile “All models are wrong, but some are useful.” George Box’s observation captures what draws me to quantitative research. Markets are too complex to be modeled perfectly, but through careful feature engineering, rigorous empirical testing, and continuous refinement, we can uncover signals that are both statistically meaningful and practically useful. After earning a degree in Mathematics with Statistics from King’s College London, I had the opportunity to apply these ideas in live markets. At Timeline Capital, I researched auction trading strategies across Taiwanese equities, engineering alpha features and evaluating machine learning models. Several of the strategies I worked on were deployed in live trading, giving me firsthand experience with the complete research lifecycle from hypothesis generation to production. Prior to this, I conducted high-frequency signal research at VICI Holdings, using order book data to deepen my understanding of market microstructure and short-horizon Prediction. I am seeking opportunities in quantitative research and trading, where I can combine mathematical rigor, practical research experience, and a systematic approach to developing quantitative trading strategies. I welcome the opportunity to connect and discuss how I can contribute to your team’s success.
