Johnson & Johnson
Process Science Modeling and Data Co-Op
Sped up app development in my team by creating a new Python application framework and UI component library using Jinja and Flask.
Centralized all site-to-site tech transfer data within J&J into a single application, allowing users to view technologies used and connect with relevant in-house experts.
Developed a cell growth model using filterpy unscented Kalman filters that outperformed traditional machine learning models for prediction accuracy and interpretability.
Led the 28-person intern community within my group; organized guest speakers to share career insights.