Visual Damage Detection System for Smart Parking

• Trained a computer vision model to detect vehicle scratches and damage from images.

• Built a containerised service using Docker for model deployment.

• Enhanced image preprocessing pipeline to boost model accuracy and generalisation.

• Collected and preprocessed data to build a time prediction model that improved the accuracy of rendering job estimates.

• Designed and implemented a visual predictive model using synthetic data for internal research.

• Built a sentiment analysis tool to assess user feedback and created a recommendation system based on user behaviour patterns.

• Integrated a payment API client with a Telegram chat-bot, enabling 500 users to initiate over 300 payments daily.
• Developed backend Django ORM logic to automatically generate and persist more than 10,000 payment records annually.
• Implemented a cron-based scheduler for payment status updates, achieving synchronization latency under 2 seconds.
• Ensured 99.9% accuracy in payment status tracking, reducing payment dispute cases by 40%.

Over a three-year period, we worked closely with one of Russia's largest banks to successfully establish a robust AI monitoring system. This system operates with precision to swiftly address system failures by pinpointing their root causes and making well-informed decisions. The model expanded the scope of forecasted indicators to a total of 50,000, achieving an 85% reduction in false positive alerts. It also delivered a 20% improvement in precision compared to previous methodologies.

Led a team to develop an AI monitoring system that was capable of detecting anomalies in various business indicators. By closely working with one of Russia's largest banks over a span of 3 years, we designed and implemented an advanced backend system dedicated to the detection of anomalies across a wide spectrum of critical business metrics. This system significantly decreased the time and effort previously invested in manual incident detection and enhanced operational efficiency.