Computer-Aided Classification

 

 

The power of the Locus standardized functional language is the ability to find, analyze, disambiguate and connect disparate parts of the global economic and business information. The CAC team is developing the technology underpinning the functional information-based applications.

A key responsibility of this group is building the machine learning methods to translate a variety of data about economic entities into our universal framework through the Locus Classification System. In doing so, they are building the tools to enable the rest of the team to process the vast world of economic data into an easily queryable and accessible form.

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+ STEFANIE BOURLAND

As a member of the Data team, Stefanie works on developing a machine-learning model to classify businesses. She received her Masters in Mathematics with a minor in Philosophy from Humboldt-Universität zu Berlin.

Before writing her thesis on the classification of symplectic and contact toric manifolds, she worked as a graduate analyst at a sustainability consulting firm. She is also an avid rail traveler, having taken the Trans-Siberian from Moscow to Beijing twice.

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+ GEORGE HYUN

George joined Locus in the summer of 2015, after interning the previous summer. As part of the Computer Aided Classification team, he spends his time thinking through ways to algorithmically assign functional attributes to various kinds of economic data.

Before joining Locus, George graduated from the University of Chicago with a BS in Mathematics. In his spare time, he hangs out on IRC and grows his hair.

 
  Owen Charles   Owen joined the data team full time after participating in the Summer 2016 internship. He works with various machine learning models as part of Locus's Computer Aided Classification project.   Owen graduated with honors from the University of Chicago with a BS in Mathematics and Computer Science. 

+ OWEN CHARLES

Owen joined the data team full time after participating in the Summer 2016 internship. He works with various machine learning models as part of Locus's Computer Aided Classification project.

Owen graduated with honors from the University of Chicago with a BS in Mathematics and Computer Science.

  Atul Prasad   Atul joined Locus to solve natural language processing problems using machine learning. He works on computer-aided classification, developing algorithms that use financial documents to automatically classify companies into the Locus system.  Atul graduated with honors from the University of Chicago in 2017, with a BS in Mathematics and Computer Science. He likes Impressionist art, analytic philosophy, and word games.

+ ATUL PRASAD

Atul joined Locus to solve natural language processing problems using machine learning. He works on computer-aided classification, developing algorithms that use financial documents to automatically classify companies into the Locus system.

Atul graduated with honors from the University of Chicago in 2017, with a BS in Mathematics and Computer Science. He likes Impressionist art, analytic philosophy, and word games.

  Leo Rayfiel   Leo is a member of the Data team, where he is a pioneer of computer-aided classification. He works on parsing financial documents and then training computers to read them. Leo graduated from Swarthmore College with a BA in History and Islamic Studies. His senior thesis was about urban planning in Amman, Jordan, where he spent his junior year.  Outside of Locus, you can find Leo playing experimental jazz with his band, Salt People.

+ LEO RAYFIEL

Leo is a member of the Data team, where he is a pioneer of computer-aided classification. He works on parsing financial documents and then training computers to read them. Leo graduated from Swarthmore College with a BA in History and Islamic Studies. His senior thesis was about urban planning in Amman, Jordan, where he spent his junior year.

Outside of Locus, you can find Leo playing experimental jazz with his band, Salt People.