As a Computer Vision Engineer, I develop and implement machine learning models aimed at enhancing the user experience in virtual try-on environments. My focus is on improving accuracy, performance, and realism to deliver seamless and immersive experiences. I successfully enhanced the realism of the earring try-on module by accounting for occlusions and head-turn effects, improving precision and visual fidelity. Additionally, I optimized the ring try-on module, doubling the FPS by balancing GPU and CPU computations in TypeScript.

Teach data analysis using Python, covering visualization techniques with matplotlib, seaborn, and plotly.js from beginner level to job readiness. All sessions are conducted interactively via Zoom, ensuring full engagement. Act as a mentor for data analyst internship programs at Technische Universität München, guiding students from learning to professional employment.

Developed and implemented educational products focused on machine learning and data analysis, including courses on Python programming and digital image processing. Created the 'Mastering Prompt Engineering' course and organized ITMO hackathon tasks in areas like autonomous navigation and image segmentation. Actively participated in 'Digital Breakthrough' hackathons as a technical expert, improving machine learning models. Competed in Kaggle challenges in image processing and bioinformatics. Supervised student projects involving architectures like Unet and ResNet. Developed Q&A chatbots integrated with various databases, and applied machine learning to solve business tasks like feedback monitoring and NLP analysis.

Coordinated large system projects involving 5 teams and 80 participants across 3 cities. Developed dashboards and automated reports for leadership, optimized ETL processes, and synchronized project activities using Jira, Confluence, and Redmine. Created a local AI assistant for processing project data and automating documentation. Managed the project knowledge base and human resources, including meetings, task coordination, and schedule monitoring. All project stages were completed on time with no customer complaints.

As a Lead Researcher, I designed and implemented proprietary algorithms for deep analysis and identification of technical systems using Python (NumPy/SciPy), MATLAB, and Simulink. My work included validating mathematical models against collected real-world data and optimizing them to align with the operating conditions of simulated physical objects. I successfully refined and adapted computer vision and image analysis algorithms based on cutting-edge research, contributing to innovative solutions in the field. My intellectual contributions were published in international research databases such as Scopus and Web of Science, showcasing impactful advancements. My scientific publications can be explored on https://www.researchgate.net/profile/Alexander-Gusev-6/research

Automated statistical analysis of longitudinal psychological surveys of students of schools of the Russian Federation and analysis of the quality of functioning of the software platform of longitudinal psychological surveys (up to 40 thousand participants at a time).

Teaching disciplines:- Algorithmization and Programming (C/C++/Python/ASM)- Database Management Systems (PostgreSQL)Student Research management

Building C++ / Qt front-end