I'm a University of British Columbia graduate with a Combined Major in Computer Science and Statistics. I am a data-driven and analytical thinker, passionate about applying statistical learning and programming expertise to real-world problems in data science and AI.My focus is on data analysis, machine learning, and predictive modeling.

My work centers on developing robust models and generating clear insights from complex datasets.

• Developed regression models using R to predict real estate prices from 414 property sales from Taipei & New Taipei City.
• Achieved an adjusted R² of 0.737, explaining 74% of the variance, by performing feature engineering with transformations (log price, quadratic age, $\sqrt{\text{MRT distance}}$).
• Key Insight: Identified MRT proximity and convenience store access as key price drivers.

• Processed the HTRU2 dataset ($\sim 17\text{k}$ observations) to classify pulsar stars using Random Forest and SVM models in Python.
• Optimized performance through cross-validation, hyperparameter tuning, and feature engineering.
• Result: Achieved ROC-AUC > 0.95, with kurtosis and skewness identified as key discriminative features.

• Analyzed theft crime trends before and after COVID-19 using R[cite: 15, 16].
• Conducted hypothesis testing and constructed confidence intervals to assess changes in crime proportions.
• Built clear and impactful data visualizations to communicate temporal trends and policy implications.

• University of British Columbia (UBC)
  • Bachelor of Science: Combined Major in Computer Science and Statistics (Expected May 2025)
  • Award: Outstanding International Student Award (OIS)