Robert Hannah

Quantitative Researcher at Citadel Securities

Robert Hannah began their work experience in 2009 as a Heart Foundation Scholarship Research Intern at the Victor Chang Cardiac Research Institute. Here they focused on investigating the effects of various substances on the hERG potassium ion channels in the heart.

In 2017, Robert joined Microsoft as a Software Engineering Intern (Core AI), where they developed and trained machine learning models to improve customer campaign performance. Robert utilized ad-market domain knowledge and statistical analysis to enhance results.

The following year, Robert continued their work at Microsoft as a Research Intern, specializing in randomized algorithms for large-scaling machine learning models. Robert'sresearch led to the discovery that certain methods cannot achieve a parallel speedup under standard assumptions.

In 2019, Robert joined Citadel Securities as a Quantitative Researcher. Robert utilized their expertise in optimization, stochastic processes, and algorithms to work on portfolio optimization for the Central Risk Book. Robert'sprimary focus was to maximize returns while minimizing risk.

Robert Hannah completed their education at UCLA from 2013 to 2019, earning a Doctor of Philosophy (PhD) in Applied Mathematics. Prior to that, they studied at the University of Sydney from 2008 to 2012, obtaining a Bachelor of Science (BSc) in Mathematics and Physics. Robert's educational history also includes attending Sydney Grammar School, although specific details such as the dates and qualifications obtained are not provided.

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Miami, United States

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Citadel Securities

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Citadel Securities is a leading quantitative trading firm and market maker. Our teams develop and deploy best-in-class research and technology, solving problems that others consider impossible. By utilizing advanced analytics, technology and trading expertise, we provide critical liquidity to central banks, financial institutions, government agencies, corporations, insurers and sovereign wealth funds.


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