Conducting lectures on neural networks and their application in scientific research for MSU graduate students, preparation of lecture materials and practical assignments of the course, supervision of scientific work of the course students.

Researcher in predictive maintenance project for complex technical product: co-developer of math modeling and machine learning (mostly using Python with TensorFlow) approaches to analyse and predict specific time-series data.Main goals: Designed LSTM-based prediction module for inhomogeneous multivariate time series data. Implemented project on multivariate time series clusterization using topological data analysis approach.

Development of segmentation algorithms for histological MxIF and IHC images (PyTorch, OpenCV). Research work on cell typing automation for MxIF data.Main goals: Participated in development of Mask R-CNN-based solution for cell instance segmentation and classification on IHC images. Contributed to the LDT validation as a data analyst.

Lattice study of quantum chromodynamics (QCD): research work, co-development of C++ MPI/CUDA sources, maintainment of HPC calculations on "Lomonosov-2" supercomputer and ITEP cluster, postprocessing and visualization of the obtained numerical results using Python.Main goals: Carried out several research projects on numerical study of quantum chromodynamics properties and presented results on thematic conferences.