Multi-Objective Evolutionary Design of Composite Data-Driven Models. - Iana S. Polonskaia; Nikolay O. Nikitin; Ilia Revin; Pavel Vychuzhanin; Anna V. Kalyuzhnaya (CEC, 2021)

Automated evolutionary approach for the design of composite machine learning pipelines. - Nikolay O. Nikitin; Pavel Vychuzhanin; Mikhail Sarafanov; Iana S. Polonskaia; Ilia Revin; Irina V. Barabanova; Gleb Maximov; Anna V. Kalyuzhnaya; Alexander Boukhanovsky (Future Gener. Comput. Syst., 2022)

Hybrid and automated machine learning approaches for oil fields development: The case study of Volve field, North Sea. - Nikolay O. Nikitin; Ilia Revin; Alexander Hvatov; Pavel Vychuzhanin; Anna V. Kalyuzhnaya (Comput. Geosci., 2022)

Composite model of seismic monitoring data analysis during mining operations on the example of the Kukisvumchorrskoye deposit of JSC Apatit. - Ilia Revin (CoRR, 2023)

Integration Of Evolutionary Automated Machine Learning With Structural Sensitivity Analysis For Composite Pipelines. - Nikolay O. Nikitin; Maiia Pinchuk; Valerii Pokrovskii; Peter Shevchenko; Andrey Getmanov; Yaroslav Aksenkin; Ilia Revin; Andrey Stebenkov; Ekaterina Poslavskaya; Anna V. Kalyuzhnaya (CoRR, 2023)

Automated machine learning approach for time series classification pipelines using evolutionary optimization. - Ilia Revin; Vadim A. Potemkin; Nikita R. Balabanov; Nikolay O. Nikitin (Knowl. Based Syst., 2023)

Integration of evolutionary automated machine learning with structural sensitivity analysis for composite pipelines. - Nikolay O. Nikitin; Maiia Pinchuk; Valerii Pokrovskii; Peter Shevchenko; Andrey Getmanov; Yaroslav Aksenkin; Ilia Revin; Andrey Stebenkov; Vladimir Latypov; Ekaterina Poslavskaya; Anna V. Kalyuzhnaya (Knowl. Based Syst., 2024)

Rockburst Forecasting Using Composite Modelling for Seismic Sensors Data. - Ilia Revin; Vadim A. Potemkin; Nikolay O. Nikitin (ICCS (4), 2025)