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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


Tucker Balch, Ph.D., Director, Quant Software Research Group
Professor, Interactive Computing, Georgia Tech
Instructor for CS 7646
Chief Scientist, Lucena Research, Inc.


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

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Jianling Wang, TA for CS 7646
Graduate Student, College of Computing, Ga Tech

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Vivek George, TA for CS 7646
Graduate Student, College of Computing (CSE), Ga Tech
2016 Summer Intern, Electronic Arts


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David Byrd, Ph.D., Georgia Tech
Asst Professor, Bowdoin College
Instructor for CS 7646, Summer 2016, Summer 2017, Fall 2019
Instructor for CS 4646, Spring 2018

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Brian Hrolenok, Ph.D., Georgia Tech
Postdoctoral Fellow, Georgia Tech

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Sourabh Bajaj, MSCS, Georgia Tech
Software Engineer, Coursera Inc

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Devpriya Dave, MSCS, Georgia Tech
Analyst, Data Division, Morgan Stanley

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Jayita Bhattacharya, MSCS, Georgia Tech
Software Engineer (Playlist), Pandora Media

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Alexander Moreno, MSCS, Georgia Tech
Ph.D. student, Georgia Tech


Rohit Sharma, MS QCF, Georgia Tech
Blackrock Capital

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Vishal Shekhar, MS QCF, Georgia Tech
Software Engineer, Axioma Inc.


  • 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]