Petr Polezhaev

1. Designed and implemented components for recommender system, including: API service to deliver recommended offers for mobile app users; data processing pipelines, models, monitoring, client API and models 2. Created a machine learning model for customer segmentation and an offer selection model for recommender system. The models increased our clients ARPU up to 23% 3. Conducted A/B-tests, which confirmed efficiency of the used approach for offer recommendations

1. Research: - Created regression models to estimate the difficulty of a specific curriculum item for students of an e-learning course - Created meta-heuristic algorithms for scheduling virtual machines and computational units - Developed an algorithm for efficient automatic creation of virtual machine disk images, created a design of the whole system and developed an integration layer with IaaS providers 2. Taught courses in machine learning, software development and computer security

Extended existing multi-platform CI/CD pipeline for code coverage analysis, detecting memory and threading problems, which reduced the number of bugs in the Intel software product.

Diploma of professional development in computer security.

A post-graduate course, PhD-student

Qualification: mathematician-programmer, GPA 5.00