Welcome!
I am the Director of the Dataism Laboratory for Quantitative Finance (DLQF) and an Assistant Professor in the Department of Economics and the Computational Modeling and Data Analytics program at the College of Science, Virginia Tech.
My research lies at the intersection of statistical machine learning and big data econometrics, with a particular focus on high-dimensional nonlinear time-series analysis and its applications in macroeconomic and financial forecasting, quantitative finance, and the analysis of large financial networks. I earned my Ph.D. in Statistics in 2017 from the London School of Economics and Political Science.
In addition to my academic work, I occasionally consult for financial firms and governmental organizations on quantitative modeling, forecasting, and machine-learning applications. I have also worked in industry for several years as a trader and portfolio strategist, where I developed algorithmic trading strategies and financial analytics.
Research Interests:
Selected Research
How do modeling choices affect estimates of the effects of U.S. bank deregulation? Read paper
Can we recover latent factors when observations are missing or noisy and the link function is unknown? Read paper
Can language models track changing financial conditions and use their calculations to make sound risk decisions? Read paper
How does quantum reservoir computing compare with econometric and machine learning models for forecasting realized volatility? Physical Review Research. Read article
How do anxiety, joy, and trading experience relate to retail traders’ willingness to use algorithmic trading bots? Journal of Behavioral Finance. Read article
Academic Positions
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2024 - present Director
Dataism Laboratory for Quantitative Finance (DLQF)
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2018 - present Assistant Professor
Department of Economics &
Computational Modeling and Data Analytics
Virginia Tech -
2012-2017 Instructor
Department of Statistics
London School of Economics
