Stefan Zohren

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Deep Learning Models for High-Frequency Market Microstructure Data

Stefan is a permanent faculty member at the Machine Learning Group and the Oxford-Man Institute for Quantitative Finance (OMI). His research interests include machine learning applied to market microstructure and high-frequency trading (HFT), statistical physics approaches to machine learning and optimisation as well as quantum computing. Before joining the OMI, Stefan worked on equities market making as a quant researcher/trader at two leading HFT firms in London. Prior to that, he coordinated the Quantum Optimisation and Machine Learning project, a joined research project of Oxford University, Nokia Technologies and Lockheed Martin. Stefan’s background is in theoretical physics, probability theory and statistics.

Stefan Zohren is an Associate Professor (Research) at the Machine Learning Research Group and the Oxford-Man Institute for Quantitative Finance (OMI). Before joining the OMI, Stefan worked on equities market making as a quant researcher/trader at two leading HFT firms in London. Prior to that, he coordinated the Quantum Optimisation and Machine Learning project, a joined research project of Oxford University, Nokia Technologies and Lockheed Martin. His background is in theoretical physics, probability theory and statistics. Stefan's research interests include statistical physics approaches to machine learning, information theory and optimisation, quantum computing as well as machine learning applied to finance, particularly market microstructure and high-frequency data.

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