Rainne Busque

Using statistical learning to rediscover classical mathematical formulas from raw numerical data — can an algorithm look at data and recover the equation that generated it?

• Implemented and analyzed SINDy (Sparse Identification of Nonlinear Dynamics) and sparse regression pipelines in Python and MATLAB.
• Applied symbolic regression and numerical methods (including Euler’s method) to recover differential-equation structure from data.
• Built up the linear-algebra foundations that these ML methods actually run on.

Built a Decision Tree regression model to predict residential housing prices in the Philippines using 1,500 real estate listings. Applied log transformation to address price skewness, evaluated using Mean Absolute Error, and shared findings publicly on Reddit.

Built an object detection pipeline using YOLOv8 for real-time inference with custom OpenCV preprocessing.

• Dean’s Scholarship recipient
• Coursework: Linear Algebra, Calculus II, Data Structures, Intro to Machine Learning
• Clubs: Devil Data Club · Google Developer Club · Philippine American Student Association (Culture Chair, 2026–2027)