Position: QA Manager, Team lead, Quality Researcher
Category: Lead
English level: intermediate
Years of experience: 11

- Developed an approach of position tracking testing for VR and AR domains. This approach was presented at the international workshop and used for more than 7 years to control project quality in this domain.
- Designed heuristics for machine learning projects that helped to increase the model accuracy. As a result, successful completion of the project
- Applied the Adaptive Random Testing approach for the verification process in machine learning projects. As a result full regression automation process that covers the almost infinite number of user scenarios
- Many successful data processing (web crawling, augmentation, generation, data creation) tasks help to collect training and validation datasets for ML projects and save the project resources.
- about 50+ successful delivered projects within the last 10 years
12 years of QA/QC process experience. (10 years in a leadership position as QA Manager and Project Leader)

Full sack management of up to 30 QA members in 20 projects. 
- Project requirement analysis, risk management, process improvement, audit, KPI
- Test process, strategy, documentation, development of new test approach
- People management, interview, 1 to 1, performance review, problem-solving, education
- Leading Automation and Manual activities
- Open-source verification, code quality review 

Participated in domains:
- ML (visual processing/recognition/tracking, Automotive AI, heuristic search, evaluation)
- AR/VR (Position tracking, object detection and tracking) 
- Android development (UI/UX testing, performance) 
- Healthcare (sensors data recognition)
- Data processing (Data sets analysis, gathering, creation, labeling, data augmentation)
- Camera calibration
- Robots

Experience with PoC projects, from research to commercialization.
Priority for me is the machine learning projects domain (image processing, visual recognition, Automotive AI, and other similar areas).