DataStart

The Southern StartUp Internship Program in Data Science (DataStart) provides graduate students in good standing at accredited universities from the South region the opportunity to work with host data-related startup companies on data-intensive business challenges important to the company.

Students are paid for their work through a grant to the startup company, and it is up to the students to identify their proposed company. The program is designed to stimulate lasting connections between graduate students in data science-related fields and entrprenuerial firms in the South. Students from all academic disciplines and domains are welcome to participate.

The 2016 DataStart Interns and their host companies are:

datastart_ansari

Student: Samia Ansari, University of Georgia
Host company: Sartography, Staunton, VA
Ansari, a student in the professional science master’s program in biomanufacturing and bioprocessing, will characterize the representation of women and racial minorities in cancer research conducted between 2002 and 2012. She will also characterize and spot trends about women and minorities’ participation in cancer trials during that time. The work complements efforts by many research agencies to ensure that clinical trials reflect the social, racial/ethnic, geographic, and economic diversity of the U.S. population.

 

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Student: Lucy D’Agostino McGowan, Vanderbilt University
Host company: Gun.io, Nashville, TN
D’Agostino McGowan, a PhD student in biostatistics, will incorporate raw data streams from Google Analytics, Slack and other sources to create a foundation for predictive modeling for Gun.io, a company that assembles remotely-managed freelance software development teams for companies worldwide. She will also examine financial data to better understand the relationship between the company’s pricing and client demand and the dynamics of different refund and return policies.

 

aziz_eramStudent: Aziz Eram, University of Arkansas at Little Rock
Host company: Black Oak Analytics, Little Rock, AR
Eram, a student in the master’s program in information quality, will develop and test a general approach to the problem of cleansing and standardizing information obtained from free text fields that reference the same product or service—for example, information about store inventory that is entered into a system manually by an employee. She will use a tool developed by Black Oak Analytics to design and test new comparators and rule configurations that address the free-text reference problem.

 

Zhengqian_Jiang.jpgStudent: Zhengqian Jiang, Florida State University
Host company: NPGroup Inc., Tallahassee, Florida
Jiang, a student in the department of industrial and manufacturing engineering, will assist Nanotechnology Patronas Group Inc. (NPGroup Inc.) in developing and commercializing a sensor system for wind turbines that can accurately detect loads that go undetected in the models typically used by inflow sensors to estimate load. The new sensor system seeks to increase wind power production and protect expensive wind turbine components.

 

jonathan_ortizStudent: Jonathan Ortiz, University of Texas at Austin
Host company: data.world, inc., Austin, TX
Ortiz, a student in the professional data analytics program, will work with data.world, a new Austin-based technology company headed by Brett Hurt, a serial entrepreneur who has led several successful big data startups, including Bazaarvoice and Coremetrics (now IBM Customer Analytics).

 

ashok_vardhanStudent: Ashok Vardhan, George Mason University
Host company: MetiStream, McLean, VA
Vardhan, who is pursuing a master’s in data analytics engineering, will help develop a healthcare data conversion solution called Ember, which bridges the gap between the existing Health Level Seven International (HL7) version 2.x (HL7 V2) healthcare standards and the emerging next generation international specification called Fast Healthcare Interoperability Resources (FHIR). The new standards are vital to using healthcare data to improve patient costs, but organizations have been slow to adopt them because of their complex existing technical environments or because of a reluctance to commit to change.

 

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