Sep 9–12, 2019

TJ Torres
Data Scientist, Intuit

TJ Torres is a data scientist at Intuit, where he works on the ML futures team tackling research problems in the areas of computer vision (CV) and natural language processing (NLP) in order to better customer experience within Intuit’s core products. Previously, he worked as an applied ML researcher, including building fashion recommendation models using computer vision to help understand visual style at Stitch Fix and building models to help automatically analyze issues with sign-up conversion at Netflix. He holds a PhD in physics.

Sessions

11:55am–12:35pm Wednesday, September 11, 2019

Location: LL21 C/D

Document understanding: Extracting structured information from financial images and forms

Models and Methods

Secondary topics: Computer Vision, Data, Data Networks, Data Quality, Machine Learning, Text, Language, and Speech

Joy Rimchala (Intuit), TJ Torres (Intuit), Xiao Xiao (Intuit), Hui Wang (Intuit)

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Document understanding is a company-wide initiative at Intuit that aims to make data preparation and entry obsolete through the application of computer vision and machine learning. A team of data scientists, Joy Rimchala, TJ Torres, Xiao Xiao, and Hui Wang, detail the design and modeling methodologies used to build this platform as a service. Read more.