I am a student at the
University of Texas at Austin
studying Computer Science and Philosophy.
Currently, I am building a startup that uses Nobel Prize winning algorithms to optimally match undergraduate researchers to labs at their universities.
Uses a K-Nearest Neighbors classification model to predict heart disease given different health information. Trained on UCI's heart disease dataset (91.4% accuracy). All data was standardized before a hypertuned model was applied.
Uses TensorFlow, MobileNet V2, and Adam optimization to predict dog breeds from images. Trained on Stanford's Dog Breed dataset. 81.12% accuracy on validation dataset. Users upload a photo of a dog to the website and it will output its 10 most confident predictions.
Researched racial bias in machine learning under Professor Saied Tizpaz-Niari. Demonstrated how COMPAS, an algorithm to predict inmates' chances of reoffending, was biased against minorities. Contributed to Partfait-ML, a Python library that minimizes bias.