Aleksei Kuvshinov

• Working on multiple ML projects in collaboration with industry partners, colleagues, and students from conceptualization to implementation. • Driving innovation in robust and reliable machine learning. • Presenting cutting-edge research at international conferences. • Teaching the foundations and advanced topics of machine learning to the next generation of AI experts. • Administrative work: processing applications in the admission committee, coordinating examinations for the research unit’s lectures.

Topic: Transportation chains optimization in rail • Applying suitable solution approaches for the fixed charge multicommodity flow problem. • Programming in Python using an API for a commercial mathematical optimization solver (Gurobi). • Research-related work solving a network design and optimization problem for large real-world instances.

Topic: Operations Research • Mathematical modeling and forecasting of time series. • Data analysis and statistical computations in R. • Building web applications using the “shiny” package in R.

Final Grade: 1.2, passed with high distinction Thesis: “Convergence analysis and solution methods for distributionally robust optimization problems with moment constraints”

Final Grade: 1.2, passed with high distinction Thesis: “Convergence analysis and solution methods for distributionally robust optimization problems with moment constraints”

Final Grade: 1.2, passed with high distinction Thesis: “Convergence analysis and solution methods for distributionally robust optimization problems with moment constraints”