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MASSIMILIANO BAROLO
Position
Professore Ordinario
Address
VIA F. MARZOLO, 9 - PADOVA
Telephone
0498275473
Dr. Massimiliano (Max) Barolo is a Professor of Chemical Engineering at the University of Padova.
After graduating with honors in Chemical Engineering, he worked as a process engineer in the largest petrochemical site in Italy. He earned the Ph.D. degree in Chemical Engineering in 1994.
He has been a visiting student (1993) and a visiting academic (1995) at the Centre for Process Systems Engineering of Imperial College (London, U.K.), and a visiting Professor (2005; 2009) at the Department of Chemical Engineering of the University of California (Santa Barbara, CA). He is the author or co-author of 150+ peer-reviewed papers and of some teaching monographs.
At University of Padova, he serves as a member of the of the “Presidium for Quality in Teaching” Committee. He served as the President of the School of Engineering, and as the Chair of the Master degree program in Chemical and process engineering.
He also serves as the National delegate in the Working Party on “Quality by design” of the European Federation of Chemical Engineering, and as a member of the Board of Directors of AIDIC (the Italian Association of Chemical Engineering).
RESEARCH
Max is the co-chair of the CAPE-Lab research group (https://research.dii.unipd.it/capelab/). His research activities are in the process systems engineering area, particularly in the following fields:
• process chemometrics; data analytics
• pharmaceutical engineering
• process monitoring; statistical process control
• process dynamics and control
• optimal model-based design of experiments
• dynamics and control of physiological systems
Past research activities have been in the fields of: distillation systems design and control; process simulation; process thermodynamics; development of anti-fraud and anti-adulteration systems for the food sector.
TEACHING
Max’s teaching experience includes the following courses:
• Process dynamics and control
• Unit operations
• Process design
• Design of chemical process equipment
• Basic chemical engineering calculations
AWARDS / HONORS
**Research**
• 2014: recipient of “The PSE Model-Based Innovation Prize 2014” from Process Systems Enterprise Ltd., London U.K. for a study on models of blood coagulation disorders (with F. Galvanin, F. Bezzo, R. Padrini and A. Casonato);
• 2013: recipient of the IFAC “Best Poster Award” for a paper presented at the DYCOPS 2013 Conference (Mumbai, India) for a study on quality control in the manufacturing of pharmaceutical products (with M. Ottavian and S. García-Muñoz)
• 2008: recipient of the IFAC/Elsevier prize for the best application paper published in the period 2005-2008 in the “Journal of Process Control” for a study on the optimal selection of measurement sensors in batch processes (with E. Zamprogna and D. E. Seborg)
**Teaching**
• Ranked no.1 in the students’ ranking of the Professors of the second-cycle (Master) degree program in Chemical and Process Engineering at Padova University in the following academic years: 2018/19, 2011/12, 2010/11, 2009/10, 2008/09
• Ranked no.1 in the students’ ranking of the Professors of the second-cycle (Master) degree program in Industrial Chemistry at Padova University in the following academic years: 2020/21, 2016/17, 2015/16, 2013/14, 2012/13
**As an undergraduate student**
• 1989: awarded as “Outstanding undergraduate chemical engineering student” (by FEDERCHIMICA)
• 1988: awarded as “Outstanding undergraduate chemical engineering student” (by MONTEDISON)
Notices
https://research.dii.unipd.it/capelab/
Office hours
Students may meet me in my office or remotely (via Zoom; webcam required). To arrange a meeting, please email me or contact me during a class.
Teachings
- PROCESS PLANT ENGINEERING, AA 2024 (INL1001984)
- PROCESS DYNAMICS AND CONTROL, AA 2024 (INQ2100479)
- PROCESS PLANT ENGINEERING, AA 2023 (INL1001984)
- PROCESS DYNAMICS AND CONTROL, AA 2023 (INQ2100479)
- PROCESS PLANT ENGINEERING, AA 2022 (INL1001984)
- PROCESS DYNAMICS AND CONTROL, AA 2022 (INQ2100479)
- PROCESS DYNAMICS AND CONTROL, AA 2022 (INP5071883)
- PROCESS DYNAMICS AND CONTROL, AA 2021 (INP5071883)
- FUNDAMENTALS OF UNIT OPERATIONS 2, AA 2021 (SC02106761)
- PROCESS DYNAMICS AND CONTROL, AA 2020 (INP5071883)
- FUNDAMENTALS OF UNIT OPERATIONS 2, AA 2020 (SC02106761)
- PROCESS DYNAMICS AND CONTROL, AA 2019 (INP5071883)
- FUNDAMENTALS OF UNIT OPERATIONS 2, AA 2019 (SC02106761)
- PROCESS DYNAMICS AND CONTROL, AA 2018 (INP5071883)
- FUNDAMENTALS OF UNIT OPERATIONS 2, AA 2018 (SC02106761)
- PROCESS DYNAMICS AND CONTROL, AA 2017 (INP5071883)
- FUNDAMENTALS OF UNIT OPERATIONS 2, AA 2017 (SC02106761)
- PROCESS DYNAMICS AND CONTROL, AA 2016 (INP5071883)
- FUNDAMENTALS OF UNIT OPERATIONS 2, AA 2016 (SC02106761)
- PROCESS DYNAMICS AND CONTROL, AA 2015 (IN01122499)
- FUNDAMENTALS OF UNIT OPERATIONS 2, AA 2015 (SC02106761)
- PROCESS DYNAMICS AND CONTROL, AA 2014 (IN01122499)
- FUNDAMENTALS OF UNIT OPERATIONS 2, AA 2014 (SC02106761)
- PROCESS DYNAMICS AND CONTROL, AA 2013 (IN01122499)
- FUNDAMENTALS OF UNIT OPERATIONS 2, AA 2013 (SC02106761)
- FUNDAMENTALS OF UNIT OPERATIONS 2, AA 2012 (SC02106761)
- PROCESS DESIGN, AA 2012 (INL1000417)
- PROCESS DYNAMICS AND CONTROL, AA 2011 (IN01122499)
Publications
To download a list of Prof. Barolo's publications, please follow the link.
Research Area
My current research areas are the following:
• process chemometrics; data analytics
• pharmaceutical engineering
• statistical process control
• process dynamics and control
• dynamics and control of physiological systems
• optimal model-based design of experiments
Thesis proposals
If you are interested to know some possibile topics for your Master thesis project, please meet me and I will be pleased to discuss my on-going research activities.
You may also visit the following web site to get an idea of the general research areas my research group (CAPE-Lab) is involved in:
https://research.dii.unipd.it/capelab
Some thesis projects that have been assigned recently are listed below.
- Control of a feed-effluent heat exchanger/reactor system: assessment by dynamic simulation
- Data-driven modeling approach to investigate the tableting properties of three powder blends for pharmaceutical product development
- On the implementation and performance assessment of an assumption-free methodology for batch process monitoring
- Design of an advanced control system and a dual-horizon optimizer for a refinery thermal cracking furnace through predictive fouling monitoring
- Accelerating pharmaceutical tablet development by transfer of compaction equipment across types and scales
- Batch process monitoring using an assumption-free modeling methodology
- Machine learning approaches to enhance biopharmaceutical process monitoring under small-data scenarios
- Powder feeding monitoring in continuous pharmaceutical solid-dosage manufacturing through state estimation
- Study and automation of the visual inspection process for syringe products
- Improving the reliability of an industrial process for the manufacturing of a polymer stabilizer by data analytics
- Interaction between design and control of heat transfer operations
- An integrated modelling framework for quality risk assessment in secondary pharmaceutical manufacturing
- Data analysis through multivariate statistical techniques: an industrial application
- Experimental protocols for the identification of freeze-drying models: a comparative study
- A Laplace domain approach to the modeling of von Willebrand disease
- Data analytics to improve process reliability in the manufacturing of specialty chemicals according to an Industry 4.0 approach
- Modeling of the primary phase of freeze-drying processes: a pharmaceutical industry application
- Multivariate monitoring of a semi-continuous pharmaceutical blending process
- Impact of measurement error in Bayesian design space determination for pharmaceutical processes
- Data analytics for powder feeding modelling on continuous secondary pharmaceutical manufacturing processes
- Design of dynamic experiments for the identification of data-driven dynamic models
- Online characterization of particle size distribution of mixtures using multivariate image analysis
- Diagnosis of first-principles mathematical models using data analytics