Andrew's Water Quality Monitoring System Wins at Princeton!

Leveraging machine learning techniques, Andrew developed a low-cost water quality monitoring system that not only enhances efficiency but also addresses the cost issues associated with traditional methods, ultimately earning me admission to Princeton University, the top-ranked institution in the United States!

Student Testimonial

During the development process, Andrew utilized advanced algorithms such as Random Forest and Gradient Boosting, along with innovative analysis methods for water quality testing data. By employing Bayesian Optimization to fine-tune my model, he gradually increased the accuracy of the predictions.

More About This Project + Accolades

Admitted to Princeton University