MrDaniele Pessina

I am a final year PhD student at the Sargent Centre for Process Systems Engineering in the Department of Chemical Engineering at Imperial. I am supervised by Dr. Maria Papathanasiou and Prof Jerry Heng, and my PhD is funded through a CASE studentship with AstraZeneca.

My research is focused on template-induced biomolecule crystallisation modelling and process design. I work at the interface of process systems engineering, machine learning, and computational modelling — developing tools to quantify uncertainty, guide experimental design, and accelerate crystallisation process development.

I also work on integrating smart machine learning methods for efficient pharmacokinetic modelling, and have explored data-driven high-dimensional time-series monitoring methods for real-time quality assurance in manufacturing.

I am interested in:

• Time-series modelling in data-scarce regimes with advanced ML architectures like neural ODEs, transformers, autoencoders with transfer learning and reinforcement learning methods
• Probabilistic programming and uncertainty quantification of mechanistic, hybrid and black-box models, enabling robust parameter estimation and decision-making under uncertainty
• Differentiable programming for process modelling and simulation, delivering GPU-accelerated, autodiff-compatible frameworks in Julia and JAX
• Hybrid modelling and ML-assisted sensitivity analysis of large, non-linear pharmacokinetic models, improving interpretability and identifiability
• ML-based soft sensors for real-time product quality monitoring in manufacturing, reducing reliance on offline batch testing
• Experimental validation of modelling hypotheses through medium-scale protein crystallisation studies using MT EasyMax and PAT tools (FTIR, UV-Vis, image analysis)
• Agentic AI for process development