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<B>Rohit Sharma</B>, MS QCF, Georgia Tech<BR>
 
<B>Rohit Sharma</B>, MS QCF, Georgia Tech<BR>
 
Morgan Stanley<BR>
 
Morgan Stanley<BR>
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<B>Vishal Shekhar</B>, MSCS, Georgia Tech<BR>
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Axioma<BR>
 
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Revision as of 13:41, 14 January 2016

Quantitative Software Research Group at Georgia Tech

The Quantitative Software Research Group investigates systematic algorithms for trading and investing. Our focus is on Machine Learning, but we are also interested in other types of algorithms that inform us about markets and trading.

Members of Our Group

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Tucker Balch, Ph.D., Director, Quant Software Research Group
Professor, Interactive Computing, Georgia Tech
Chief Scientist, Lucena Research, Inc.
website

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Maria Hybinette, Ph.D.
Associate Professor, Computer Science, University of Georgia

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C David Byrd, Graduate Student and Head TA
Title, IMTC

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Brian Hrolenok, Ph.D. Student and Head TA
Multiagent Robotics and Systems Lab

Alumni

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Sourabh Bajaj, MSCS, Georgia Tech
Coursera

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Devpriya Dave, MSCS Georgia Tech
Quant Developer, Morgan Stanley

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Jayita Bhattacharya, MSCS Georgia Tech
ML Specialist, Pandora

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Alexander Moreno
Ph.D. student, Georgia Tech

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Rohit Sharma, MS QCF, Georgia Tech
Morgan Stanley

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Vishal Shekhar, MSCS, Georgia Tech
Axioma

Publications

  • Moreno, Alexander, and Tucker Balch. "Speeding up large-scale financial recomputation with memoization." Proceedings of the 7th Workshop on High Performance Computational Finance. IEEE Press, 2014. (conference)
  • Moreno, Alexander, and Tucker Balch. "Improving financial computation speed with full and subproblem memoization." Concurrency and Computation: Practice and Experience (2015). (Journal) [1]