Alexander Shestopaloff

Dr. Alexander Shestopaloff is a Senior Lecturer in Statistics at the School of Mathematical Sciences, Queen Mary University of London, and a Fellow of the Alan Turing Institute. He holds a PhD in Statistics from the University of Toronto (2016). His research focuses on Bayesian statistics, network science, quantitative finance, and empirical market microstructure, with a particular emphasis on cryptocurrency exchanges like Binance and Bybit. He develops computational methods for Bayesian inference, including online learning algorithms, and explores statistical procedures to detect network structures.

Education:

• PhD in Statistics, University of Toronto (2016)

Research Interests:

• Bayesian computational methods and modeling
• Network science and statistical graph analysis
• Quantitative finance, market microstructure, and high-frequency trading
• Online learning and high-dimensional time series analysis

Grants and Funding:

• Research Fellowship: Cross-sectional forecasting of high-dimensional time series (£112,358), Delphia Technologies Inc (2023–2026)
• Innovate UK KTP: Wise (£219,928), Innovate UK (2022–2025)

Key Contributions:

• Advances in robust Kalman filtering and Bayesian online learning
• Statistical analysis of network structures and graph algorithms
• Analysis of cryptocurrency market dynamics using high-frequency data

Affiliations: Centre for Probability, Statistics and Data Science at Queen Mary University of London.