I am passionate about alternative data and machine learning technology to drive the complex future of quantitative finance. With unique blend of academic training and pragmatic set of experiences, I've had the opportunity to use this blend to formulate and implement systematic trading strategies ...
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I am passionate about alternative data and machine learning technology to drive the complex future of quantitative finance. With unique blend of academic training and pragmatic set of experiences, I've had the opportunity to use this blend to formulate and implement systematic trading strategies with consistent success from diverse innovative datasets that create revenue and simultaneously improve market efficiency.
Throughout my 13 years experience in quantitative finance, I created systematic trading strategies in global equities, FX, commodity derivatives on various holding horizons for our customers. As a leader in quantitative research, I led a small team conducting empirical research and delivering active and passive investment strategies from innovative data using R, Matlab, Python, C++ and SQL.
Prior to joining hedge fund industry, I was a machine learning expert in Philips Research USA where I researched and created an online facial recognition model based on Probabilistic Neural Networks that is able to recognize the known faces, identify new faces and train new faces automatically. Prior to Philips, I studied in Computer Engineering at Columbia University and Computer Science at Shenzhen University.
I enjoy playing guitar, competition badminton (won several semi-pro tournaments), and the Boston Celtics.I
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