Research
Bayesian statistics, Network science, Quantitative finance, Empirical market microstructure, Online learning, High dimensional time series
Interests
My interests span the following areas. First, Bayesian statistics. I am interested in both the development of novel computational methods for Bayesian inference, including Bayesian online learning, and Bayesian modeling. Second, I am interested in the intersection of network science and statistics, in particular, designing statistical procedures to detect the presence of structures in networks. Third, I work on problems in quantitative finance, with a focus on empirical market microstructure. This involves using high-frequency, market by order, data to understand the dynamics of price formation on exchanges. Of particular interest to me here are live experiments conducted on accessible crypto exchanges such as Binance and Bybit.
Publications
Publications of specific relevance to the Centre for Probability, Statistics and Data Science
2025
A unifying framework for generalised Bayesian online learning in non-stationary environmentsDuran-Martin G, Sanchez-Betancourt L,
Shestopaloff A and Murphy K
Transactions on Machine Learning Research 13-03-2025 Bayesian Partial Reduced-Rank RegressionPintado MF, Iacopini M, Rossini L and
Shestopaloff A Journal of Computational and Graphical Statistics 03-01-2025 2024
Empirical study of graph spectra and their
limitationsMiasnikof P,
Shestopaloff A, Bravo C and Lawryshyn Y
Thirteenth International Conference on Complex Networks and their Applications.
20-02-2024The Good, the Bad, and Latency: Exploratory Trading on Bybit and BinanceAlbers J, Cucuringu M, Howison S and
Shestopaloff AY ,
Elsevier 01-01-2024 Outlier-robust Kalman Filtering through Generalised BayesDuran-Martin G, Altamirano M,
Shestopaloff AY, Sánchez-Betancourt L, Knoblauch J, Jones M, Briol FX and Murphy K
Proceedings of Machine Learning Research. vol. 235, 12138-12171.
01-01-2024 2023
Dynamic Time Warping for Lead-Lag Relationship Detection in Lagged Multi-Factor ModelsZhang Y, Cucuringu M,
Shestopaloff A and Zohren S
4th ACM International Conference on AI in Finance., 454-462.
25-11-2023 Uncertainty Quantification in Bayesian Reduced-Rank Sparse RegressionsPintado MF, Iacopini M, Rossini L and
Shestopaloff AY 02-06-2023 Statistical power, accuracy, reproducibility and robustness of a graph clusterability testShestopaloff A, Miasnikof P and Raigorodskii A
International Journal of Data Science and Analytics,
Springer 16-04-2023 Statistical Network SimilarityMiasnikof P,
Shestopaloff AY, Bravo C and Lawryshyn Y
Eleventh International Conference on Complex Networks and their Applications. vol. 1078, 325-336.
01-01-2023 LOW-RANK EXTENDED KALMAN FILTERING FOR ONLINE LEARNING OF NEURAL NETWORKS FROM STREAMING DATAChang PG, Durán-Martín G,
Shestopaloff A, Jones M and Murphy K
Proceedings of Machine Learning Research. vol. 232, 1025-1071.
01-01-2023 2022
An empirical comparison of connectivity-based distances on a graph and their computational scalabilityMiasnikof P,
Shestopaloff AY, Pitsoulis L and Ponomarenko A
Journal of Complex Networks vol. 10 (1)
16-02-2022 2021
Fragmentation, Price Formation and Cross-Impact in Bitcoin MarketsAlbers J, Cucuringu M, Howison S and
Shestopaloff AY Applied Mathematical Finance,
Taylor & Francis vol. 28 (5), 395-448.
03-09-2021 2020
Distances on a GraphMiasnikof P,
Shestopaloff A, Pitsoulis L, Ponomarenko A and Lawryshyn Y
Ninth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2020.
20-12-2020 A density-based statistical analysis of graph clustering algorithm performanceMiasnikof P,
Shestopaloff AY, Bonner AJ, Lawryshyn Y and Pardalos PM
Journal of Complex Networks,
Oxford University Press (OUP) vol. 8 (3)
01-06-2020 A Statistical Test of Heterogeneous Subgraph Densities to Assess ClusterabilityMiasnikof P, Prokhorenkova L,
Shestopaloff AY and Raigorodskii A
International Conference on Learning and Intelligent Optimization. vol. 11968 LNCS, 17-29.
22-01-2020 2019
Replica conditional sequential monte carloShestopaloff AY and Doucet A
Proceedings of the 36th International Conference on Machine Learning. vol. 2019-June, 10098-10107.
13-05-2019 2018
Sampling latent states for high-dimensional non-linear state space models with the embedded HMM methodShestopaloff AY and Neal RM
Bayesian Analysis vol. 13 (3), 797-822.
01-09-2018 A statistical performance analysis of graph clustering algorithmsMiasnikof P,
Shestopaloff AY, Bonner AJ and Lawryshyn Y
International Workshop on Algorithms and Models for the Web-Graph. vol. 10836 LNCS, 170-184.
30-05-2018 2015
Naive Bayes classifiers for verbal autopsies: Comparison to physician-based classification for 21,000 child and adult deathsMiasnikof P, Giannakeas V, Gomes M, Aleksandrowicz L,
Shestopaloff AY, Alam D, Tollman S, Samarikhalaj A and Jha P
Bmc Medicine vol. 13 (1)
25-11-2015
