Intern on Data Team.

Project with Data Team

Similar to ‘Service’ in Google Maps, will use prompted questions to ask users about their experience and improve the data quality and obtain exact transactions to conduct fraud detection on the Financial Intelligence team

Conducted tactical & strategic analysis on 130 Columbia research inventions, including matching to potential industry partners in Life Sciences, Clean Energy, Media & Tech, Blockchain, and Cybersecurity, leading to 25 license deals & IP-backed startups

Engineered a backend simulator that mimics the tokenization process of a credit card in GPay’s infrastructure, using principles like Async programming (Promises), Remote Procedure Calls, & Lambda Func. in Java to accelerate the verification of 5+ vendors APIs. The simulator, used for end-to-end testing, improves quality assurance and developer velocity for future GPay releases.

- Devised a workflow to review standardized processes and process documents using P​ython’s​ pandas packages and improved efficiency by 40% by automating the initial review process of scanning 5000+ document pages to find Reference numbers- Implemented a Machine Learning​ model against overhead footage of turtles by labelling and testing 1000 frames of high-definition video with labelImg, and developing prediction models for future videos using Tensorflow, Keras, and pandas.

- Presented a final project about a J​avascript​ maze-generation algorithm and machine learning movement tracker to create a two-player maze game, run by keyboard presses and hand gestures

- Created a P​ython​ script to analyze anomalies in results from a citizen scientist crowdsourcing websites and developed ground truth for deepROOT, a machine learning system developed by engineers at the Biophotonics Core