cv

PhD in Data Sciences and Operations

• Advised by Advised by Yingying Fan and Paromita Dubey

M.A. and B.A. in Statistics

• Advised by Ilmun Kim

Artificial Intelligence Researcher

• Solved data science challenges for various departments within the Republic of Korea Army.
• My primary project focused on developing a predictive model for forest fires triggered by artillery training sessions, leveraging meteorological data.
• A key challenge was addressing the severe class imbalance in the dataset. To overcome this, I integrated generative model-based oversampling with a weighted support vector machine (SVM).
• This approach achieved a 99% improvement in prediction accuracy compared to previous models.
• Publications.
  • Prediction of forest fire risk for artillery military training using weighted support vector machine for imbalanced data
  • Weighted support vector machine for extremely imbalanced data

al-folio

• A beautiful, simple, clean, and responsive Jekyll theme for academics.

• Fully-funded machine learning theory summer school hosted by Princton University