Seyedalborz Manavi

• Developed and standardized financial service data models (FSDM) to enhance data management and operational efficiency using SQL
• Collaborated in digital business automation projects, significantly improving process consistency across the company
• Contributed to Agile project teams, employing Scrum & Kanban methodologies to facilitate project delivery and improve stakeholder satisfaction.

• Conducted advanced research on Physics-Informed Neural Networks (PINNs), focusing on their application to computational problems to optimize design processes
• Engaged in sensitivity analysis and process optimization projects, contributing to enhancements in design methodologies.

Developed data modeling and machine learning solutions to monitor and control bioprocesses, improving process reliability and product quality

• Implemented and validated predictive models using denoising autoencoder neural networks (DAE-NN) and variational-autoencoder neural networks (VAENN) to enhance anomaly detection and data integrity
• Initiated adoption of novel machine learning techniques, including integration of physics-informed neural networks in multiscale and multiphysics problem simulations.