Fabrizio Bezzo's research interests comprise:

Design and analysis of energy systems:
- optimal design of supply chains for carbon capture, transport and sequestration (CCS)
- design and optimization of processes for biofuels production
- environmental and economic analysis and optimization of energy supply chains
- modelling and optimization of microalgae production systems

Experiment design for model identification:
- development of advanced model-based experiment design techniques
- design of clinical tests for identification of physiological models
- development and identification of biosystems models

Statistical process control:
- data-driven modelling for process and product quality control in the fine chemicals industry
- design space characterization and process scale-up in the pharmaceutical industry

Fabrizio Bezzo co-leads the CAPE-Lab research group.

The titles of some recent Master's theses are listed in the following:

- Recycling of critical materials for the renewable energy sectors: technology analysis and supply chain modelling
- From conventional to surrogate-based flexibility assessment: application to a bio-methanol process under uncertainty
- Bioprocessing of genetically engineered microalga Nannochloropsis gaditana for lipid production: upstream and downstream operations
- Conceptual design of a green-ammonia production process: cost and safety assessment
- Optimization of the design and operation of outdoor microalgae production in industrial-scale tubular photobioreactors
- CFD-based design and optimization of a mixing impeller for enhanced viscosity and pH measurements in hand dish-washing liquid products
- Development of a test method to study grease-on-plastic cleaning through hand wash
- Experimental investigation of the combined effect of light and temperature on microalgae growth in milli-photobioreactors
- Experimental and model-based analysis for optimizing Chromochloris zofingiensis growth from laboratory to plant scale
- An optimisation framework to define maximum parametric uncertainty guaranteeing acceptable model fidelity
- Development of a model for temperature control in an industrial batch reactor
- Study of the main parameters affecting the rinsing speed of hand dish washing products
- Environmental optimization of the Northern Italy supply chain for the treatment of residual plastic packaging waste considering waste-to-energy and chemical recycling technologies
- Alternative sustainable routes to methanol production: Techno-economic and environmental assessment
- Fluid dynamics modelling and process optimization of a flashing light photobioreactor for enhancing microalgae cultivation
- Design and optimization of membrane processes for carbon capture purposes
- Optimal design of experiments for kinetic model structure identification using reinforcement learning methodologies
- Economic optimization of the Northern Italian supply chain for the treatment of residual plastic packaging waste considering waste-to-energy and chemical recycling technologies
- Experimental analysis of the effect of different light conditions on microalgal growth in small-scale continuous photobioreactors
- Advanced process control with surrogate models based on finite impulse response neural networks
- Identification of a multi-vial primary drying model for process optimization in the presence of limited industrial data
- Assessing mass transfer in a polymer dissolution process via test method development and CFD simulations
- Economic optimisation of carbon capture and sequestration from Italian industrial sources under seismic risk constraints
- Design of a chemical looping reactor for the production of syngas from CO2
- Process design and optimization of protein extraction from sunflower meal
- Identification of lyophilization models via sensitivity analysis and optimal design of experiments
- State estimation monitoring of loss-in-weight feeders in the continuous manufacturing of powder-based pharmaceutical products
- Optimization of the carbon capture and sequestration supply chain for the Italian cement industry
- Coupling artificial neural networks and optimal design of experiments for fast recognition of kinetic models from experimental data
- Hybrid modelling of batch bioreactors for mammalian cell cultures