Leading advanced machine learning projects focused on generating novel recipes and optimizing process parameters to maximize the performance of paper machines.Establishing best practices for project management, incorporating Agile methodologies and integrating CI/CD pipelines to streamline development and deployment."

Implemented end-to-end machine learning pipelines using Azure along with cross-functional teams, reducing paper production defects and targeting €1M in annual savings.Leveraged data analytics to drive new cost-saving measures at two production sites, yielding €300k in annual savings.Engineered R&D dashboards for pulp morphology analysis leveraging SHAP and Power BI.

Based in Finland, with onsite assignments as a Data Scientist in Brazil (1 month) and India (1 year) during this period.Optimized heat transfer performance for recovery boiler superheaters by 5% using neural networks at a customer plant.Deployed machine learning models to forecast smelt flow rate, emissions, and ash content in flue gas on Andritz Cloud, ensuring smooth and prolonged boiler operations.Supported and enhanced AI and data analytics components in Andritz Cloud Digital Solutions studio.Collaborated with senior leadership, development teams, and external stakeholders to identify and develop AI strategies for multiple use cases.

Optimized the superheater region design in recovery boilers using CFD (Computational Fluid Dynamics), leading to €200-500k cost savings in manufacturing.Pioneered the integrated 3D-CFD and 1D process model for recovery boilers, enhancing thermal efficiency by analyzing simulation data, with findings published in Tappi journal

Contributed to nuclear fusion reactor project (ITER) and developed Python based algorithm and GUI using PyQt5 to develop data pipelines and perform numerical analysis related to material deposition and erosion rates.

Project management, training and placements; and recruiting