Sid Arora

Sid Arora has a background in machine learning and software development, with notable internships at companies such as Amazon and Bizmetric. At Bizmetric, Sid designed a decision tree model to predict patient mortality rates using ICU data. As a Scientific Researcher at the University of California, Santa Barbara, collaborative work focused on predicting New York Times Best Sellers, while another research role at Rice University explored the effects of min-wise hashing on neural network training. Additional experience includes software engineering internships where Sid developed tools for sales tracking at PetroEd and contributed to projects related to Amazon's RDS PostgreSQL and DynamoDB. Currently pursuing a Bachelor of Science in Mathematics and Computer Science at The University of Texas at Austin, Sid has also engaged in research aimed at using reinforcement learning to alleviate traffic congestion.