I'm a PhD researcher in an industrial collaboration working at the interface of bioprocess engineering, scientific machine learning, and experimental optimization.
My work focuses on building data-driven and hybrid modeling workflows for biological processes, including protein refolding, fermentation, and downstream processing. I am especially interested in how Bayesian optimization, mechanistic models, and uncertainty-aware machine learning can work together and support better experimental decision-making.
- Hybrid mechanistic / machine learning models for bioprocesses
- Bayesian optimization for experimental design
- Scientific machine learning and AI for engineering
- Protein refolding, inclusion bodies, and downstream process development
- Uncertainty quantification for model-based decisions
- AI Agents and agentic workflows
- Hybrid ODE/ML models
- (Physics-informed) Bayesian optimization workflows for process optimization
- Soft-sensors for monitoring of protein refolding
- AI Agents for smart tech transfer in biopharmaceutical industry
Python · JAX · Equinox · Diffrax · PyTorch · BoTorch · GPyTorch · NumPy · pandas · matplotlib
- Google Scholar
- Email: florian[at]gisperg.com