Bioprocess Digital Twin
Connecting process data and predictive models to understand cell-culture states and dynamics.
- Hybrid modeling and process simulation
- PAT-based monitoring and state estimation
- Fed-batch development and predictive control
Our research
Connecting biological understanding, process engineering and data-driven models.
Process Analytical Technology
Interpreting analytical signals to understand cells and the culture process.
- Biomass and culture-state analysis
- Spectroscopy, process sensors and soft sensors
- Data integration and state estimation
Self-Driving Laboratories
Investigating self-driving workflows that connect laboratory automation with active learning.
- Laboratory automation and analytical integration
- Active learning and Bayesian optimization
- Building and validating closed-loop experiments
CFD & Hydrodynamics
Analyzing mixing, shear and mass transfer to inform bioreactor design and process transfer.
- CFD analysis of flow, mixing and shear
- Shaking-flask and stirred-bioreactor characterization
- Bioreactor design, scale-up and process transfer
AI-Driven Optimization
Exploring media and process conditions through predictive models and experimental feedback.
- Cell-line-specific media formulation
- Bayesian optimization and sequential design
- Culture validation and experimental feedback
Systems Biotechnology
Connecting cellular metabolism and genome-scale models to understand culture performance.
- Genome-scale metabolic modeling
- Enzyme capacity and constraint-based analysis
- Cellular metabolism and media design
