Karthikeyan K

• Optimized deep learning models for faster performance in real-time applications.
• Streamlined image annotation processes by devising automated tools, increasing team efficiency and reducing manual errors.
• Developed robust computer vision systems for enhanced image processing and analysis.
• Enhanced video analytics capabilities by incorporating advanced tracking algorithms for improved motion detection and event recognition.
• Devised efficient pipeline architectures for seamless integration of various components within complex computer vision systems.
• Conducted extensive research on the latest computer vision techniques, contributing to cutting-edge advancements in the field.
• Applied data augmentation techniques to increase dataset diversity, improving model generalization across various scenarios.
• Evaluated various deep learning frameworks and libraries for optimal implementation in computer vision projects, ensuring maximum compatibility and performance.
• Conduct feasibility studies through initial client calls to evaluate and understand project requirements
• Provide expert recommendations on camera and lighting configurations to optimize image capturing for computer vision tasks.
• Oversee the collection of data necessary for model training, ensuring it meets quality standards and project needs.
• Develop, train, and optimize deep learning models and computer vision algorithms tailored to client specifications.
• Suggest and implement improvements to workflows in collaboration with both backend and frontend teams to enhance project efficiency.
• Manage the deployment of computer vision solutions in both local and server environments, ensuring smooth integration and functionality.
• Facilitate and perform User Acceptance Testing on the client side to ensure that solutions meet their expectations and requirements.
• Act as the Single Point of Contact (SPOC) for clients, managing communication and addressing any project-related issues or concerns.

Category: Forecasting Spare parts inventory

The case business case is on inventory management. Keeping Inventory of spare in various service centre to market demand is always challenge as most service

centres spends significant amount in spare parts inventory costs. In spite of this,

availability of spare parts is been one of problem areas.

Client: No-Churn Telecom | Category: Telecom – Churn Rate ML

No-Churn Telecom is an established Telecom operator in Europe with more than decade in Business. Due to new players in market, telecom industry has become very competitive and retaining customers becoming challenge.

In spite of No-Churn initiatives of reducing tariffs and promoting more offers,

churn rate (percentage of customers migrating to competitors) is well above

10%.

No-Churn wants to explore possibility of Machine Learning to help with following use cases to retain competitive edge in industry.

• Provided detailed documentation on audit findings, facilitating swift corrective action when necessary.
• Maintained confidentiality, handling sensitive information discreetly throughout all stages of the audit process.
• Ensured compliance with regulatory requirements by performing regular audits and staying up-to-date on industry standards.
• Streamlined audit processes, improving efficiency and reducing time spent on each audit engagement.
• Planned and executed follow-up audits at appropriate intervals.