Massimiliano Barolo

Professor

University of Padova

Italy

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About

Massimiliano Barolo is a Professor at the University of Padova in Italy. His research areas focus on process industries, pharmaceutical tablet development, and data-driven modeling techniques. His recent articles explore topics such as electrification in process industries, smart process analytics, and the application of machine learning in predicting drug solubility. He is dedicated to advancing knowledge in fault detection, biorefinery processes, and optimizing manufacturing systems.

Articles (19)

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2025

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2024

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2022

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2022

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2022

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2022

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2022

Collaborators (9)

Iiro Harjunkoski

Aalto University

FINLAND

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Mehmet Mercangöz

Imperial College London

UNITED KINGDOM

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Zoltan K. Nagy

Purdue University

UNITED STATES

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Catajina Harabajiu

GlaxoSmithKline

UNITED KINGDOM

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Fabrizio Bezzo

Full professor

University of Padova

ITALY

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Christos Maravelias

Professor

Princeton University

UNITED STATES

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Krist Gernaey

Professor

Technical University of Denmark

DENMARK

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CHARALAMPOS CHRISTODOULOU

GlaxoSmithKline Research and Development

UNITED KINGDOM

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Pierantonio FACCO

ITALY

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Massimiliano Barolo

Research Interests

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About

Articles (19)

Transforming the Process Industries through Electrification: Challenges and Opportunities

Smart Process Analytics for Process Monitoring

Predicting drug solubility in organic solvents mixtures: A machine-learning approach supported by high-throughput experimentation

Understanding Fouling in an Industrial Biorefinery Membrane Separation Process by Feature-Oriented Data-Driven Modeling

Hybrid modeling of a biorefinery separation process to monitor short-term and long-term membrane fouling

Capturing connectivity information from process flow diagrams by sequential-orthogonalized PLS to improve soft-sensor performance

Data fusion of Raman spectra in MSPC for fault detection and diagnosis in pharmaceutical manufacturing

Accelerating pharmaceutical tablet development by transfer of powder compaction equipment across types and scales

Data‐driven tools for the optimization of a pharmaceutical process through its knowledge‐driven model

A general procedure for the evaluation of the prediction fidelity of pharmaceutical systems models

Quality‐by‐control of intensified continuous filtration‐drying of active pharmaceutical ingredients

Optimal Indicator-Variable Approach for Trajectory Synchronization in Uneven-Length Multiphase Batch Processes

Streamlining tablet lubrication design via model-based design of experiments

Integrating metabolome dynamics and process data to guide cell line selection in biopharmaceutical process development

Digital design of new products: accounting for output correlation via a novel algebraic formulation of the latent-variable model inversion problem

A benchmark simulator for quality-by-design and quality-by-control studies in continuous pharmaceutical manufacturing ‒ Intensified filtration-drying of crystallization slurries

A review on the modernization of pharmaceutical development and manufacturing – Trends, perspectives, and the role of mathematical modeling

Data Analytics Can Help Reduce Energy Consumption in the Industrial Manufacturing of Specialty Chemicals

Practical use of primary drying models in an industrial environment with limited availability of equipment sensors

Collaborators (9)

Iiro Harjunkoski

Mehmet Mercangöz

Zoltan K. Nagy

Catajina Harabajiu

Fabrizio Bezzo

Christos Maravelias

Krist Gernaey

CHARALAMPOS CHRISTODOULOU

Pierantonio FACCO

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