Mashrin Srivastava, a master's student in the Machine Learning Department, recently won top awards at two hackathons.

He earned a finalist prize in the Wells Fargo Analytics Challenge, which asked students to use machine learning and natural language processing to predict and categorize transactions to build better customer engagement tools. For his project, Srivastava completed detailed data analysis and built about 100 models with different settings. The best performing model categorized the transactions with 93-94% accuracy on the provided data. Srivastava was one of five to win a finalist prize.

Srivastava also received the Subsocial Award at the Polkadot Hackathon for work creating a Twitter clone from scratch on blockchain and building an app on top of it to help find essential resources during a disaster using social media posts. The project also was the most liked project at the hackathon.