Machine Learning Research Assistant

Conducted classification robustness research under Professor Sanjoy Dasgupta, studying how Perceptron-based models behave when trained and evaluated on incomplete or noisy datasets. Built Python simulation scripts to introduce controlled missing data conditions at varying rates, then measured and reported the resulting impact on model accuracy and convergence — contributing to a broader research thread on the reliability of foundational ML classifiers.