Laura Azzimonti

About

Laura Azzimonti leads the Knowledge-Informed AI group and the IDSIA research area AI in Health and Life Sciences. She is also Group Leader at the SIB Swiss Institute of Bioinformatics, where the group is registered as Machine Learning for Bioinformatics and Personalised Medicine.

Her research develops machine learning methods that integrate data with prior knowledge: physics-informed machine learning, causal AI and probabilistic graphical models, and federated learning. She is principal investigator, or SUPSI principal investigator, of projects funded by Horizon Europe and Innosuisse and of direct research mandates with hospitals and companies.

This work builds on more than fifteen years at the interface of statistics, scientific computing and machine learning. It started with spatial regression with partial differential equation penalisation, which uses physical knowledge to estimate blood flow fields from sparse measurements and was developed during her doctoral work at Politecnico di Milano, including a research stay at EPFL. It continued at IDSIA with hierarchical Bayesian models and probabilistic graphical models, within a project funded by the Swiss National Science Foundation, and with machine learning for personalised medicine in collaboration with hospitals in Switzerland and Italy.

Positions

Since 2024: Group Leader, Machine Learning for Bioinformatics and Personalised Medicine, SIB Swiss Institute of Bioinformatics
Since 2023: Responsible for the research area AI in Health and Life Sciences, IDSIA USI-SUPSI
Since 2020: Senior Researcher and Lecturer, IDSIA USI-SUPSI, Lugano
2017–2019: Researcher and Lecturer, IDSIA USI-SUPSI
2015–2017: Researcher, IDSIA USI-SUPSI
2014–2015: Research Specialist Engineer, MOXOFF, Milan. Mathematical and computational methods for clients in electronics, biomedicine, automotive, transport and ecology
2013–2014: Postdoctoral Researcher, MOX, Department of Mathematics, Politecnico di Milano
2012–2013: Four-month research stay, Scientific Computing and Uncertainty Quantification group (Prof. F. Nobile), EPFL

Education

2019: Certificate of Advanced Studies in Teaching, SUPSI
2012: PhD in Mathematical Models and Methods in Engineering, Politecnico di Milano, with Doctor Europaeus certification. Thesis: Blood flow velocity field estimation via spatial regression with PDE penalization
2009: MSc in Mathematical Engineering, Politecnico di Milano, 110/110 cum laude
2007: BSc in Mathematical Engineering, Politecnico di Milano, 110/110 cum laude

Projects and funding

Role as principal investigator (PI) or co-investigator. Project pages are linked where available.

2025–2027: AI for materials characterisation, direct mandate with an international manufacturing company. PI
2024–2025: GUIDE, Innosuisse Innovation Cheque with Enhance-d. Co-applicant and PI
2023–2025: PRAESIIDIUM, Horizon Europe (101095672). Co-applicant and SUPSI PI
2023–2025: Early identification of ventilator-associated pneumonia, Innosuisse (102.522.1 IP-ICT) with EOC. Co-applicant and SUPSI PI
2023: HEAVEN, direct mandate with Inselspital, Bern University Hospital. PI
2022–2025: SPEARHEAD, Innosuisse Flagship (PFFS-21-15). Co-applicant and SUPSI PI
2021–2022: CLIER and K-CLIER, with EOC (2022 follow-up as direct mandate). PI
2018–2022: Direct mandates with a major Swiss bank on client analytics and natural language processing (2018–2021). PI. Organisational manager of the collaboration in 2019–2020, coordinating twenty SUPSI researchers in six sub-projects, and responsible for the collaboration in 2020–2022
2018: ALBIS, risk-based surveillance of invasive mosquitoes, SUPSI. Applicant and co-investigator
2015–2022: Further mandates and consultancy projects with EOC (personalised medicine, vital signs, perinatal depression, resource planning). PI
2011–2013: FIRB Futuro in Ricerca and PRIN projects, Italian Ministry of Education, University and Research. Co-investigator

Teaching

2025, 2026: Federated Learning in Bioinformatics, SIB Swiss Institute of Bioinformatics. Course coordinator
2020–2024: Bayesian Data Analysis and Probabilistic Programming, BSc in Data Science and Artificial Intelligence, SUPSI. Module leader
2017–2023: Calculus, BSc in Data Science and Artificial Intelligence (in English) and BSc in Engineering, SUPSI. Lecturer
2015–2017: Pre-calculus and Calculus, BSc in Engineering, SUPSI. Lecturer
2015–2016: Data Mining for Business Intelligence, Management Engineering, SUPSI. Lecturer
2011, 2013: Statistics for Mechanical and Energy Engineering, Politecnico di Milano. Teaching assistant

Supervision

Current group

Researchers: Daniele Malpetti, Lea Multerer, Clara Galimberti
PhD student: Giovanni Angelotti
Master's students: Manuel Acquistapace, Christian Berchtold

Theses

2026: MSc in Artificial Intelligence, University of Bologna (in progress)
2026: BSc in Data Science and AI, SUPSI. Predicting major adverse arrhythmic cardiac events in ischaemic and non-ischaemic cardiomyopathy: an explainable ML study on the DERIVATE registry
2026: BSc in Data Science and AI, SUPSI. CATE estimation and use in the MASTER DAPT study (co-supervisor)
2025: BSc in Data Science and AI, SUPSI. Bayesian hierarchical estimation of ordinary differential equation parameters with application to glucose-insulin dynamics. Best thesis award
2024: MSc in Artificial Intelligence, USI. Leveraging artificial intelligence for enhanced medical diagnosis in dermatology, with focus on skin cancer detection
2020: BSc in Computer Science Engineering, SUPSI. Software development for hierarchical Bayesian networks learning
2019: BSc in Computer Science Engineering, SUPSI. Bayesian neural networks

Visiting students and internships

2026: Visiting MSc student in Artificial Intelligence, University of Bologna
2024: Visiting PhD student, Università Campus Bio-Medico di Roma. Causal inference for diabetes
2021: Two internships in Mathematical Engineering, EPFL. Relaxing hierarchical Bayesian networks; Mixed effects Bayesian networks
2018–2020: Three MSE projects in Intelligent Systems, SUPSI

Editorial work and service

2026–2027: Associate Editor, Statistical Methods & Applications (Applications section)
2026: Guest Editor, npj Digital Medicine collection "Physics-Informed Machine Learning for Personalized Disease Prediction, Prevention, and Management"
2025: Guest Editor, International Journal of Approximate Reasoning special issue "Causal Inference in Healthcare"
2025, 2026: Organising committee, Precision Health Day, SUPSI
2025: Session chair, "Clinical Data Science", BC2 Basel Computational Biology Conference, SIB
2024: PhD evaluation committee, Information Technology, Politecnico di Milano
Since 2021: Board member, BSc in Data Science and Artificial Intelligence, SUPSI
2021: Programme committee, PharML workshop, ECML PKDD
2019–2020: Working groups for the creation of the BSc in Data Science and Artificial Intelligence and for the 2021–2024 strategy of the SUPSI Department of Innovative Technologies

Talks

2026: Online lecture, Physics-Informed Machine Learning and Causal Artificial Intelligence for Personalized Diabetes Prevention, Causal Analysis of Biomedical Data Lecture Series, Luxembourg Centre for Systems Biomedicine, University of Luxembourg
2025: Keynote on artificial intelligence and predictive medicine for diagnosis, treatment and monitoring, symposium "Decostruire per preparare il futuro di una nuova Nefrologia", Lugano
2024: Keynote, Leveraging AI and Causality to Enhance Personalised Treatments for Type 2 Diabetes, International Annual Conference on Artificial Intelligence in Health, Basel
2023: Keynote, Challenges and Opportunities for Artificial Intelligence in Biomedicine, Giornata della Ricerca e dell'Innovazione in Medicina Umana della Svizzera italiana, Lugano
2010–2020: More than twenty contributed and invited presentations at international conferences, including PGM, IEEE ICDM, ERCIM CMStatistics and ENUMATH

Awards

2025: Second place, 7th Digital Critical Care Datathon, ESICM (team lead)
2011: Best Graduate Student Prize, MSc in Mathematical Engineering, Politecnico di Milano (academic year 2008–2009)
2009: Best Graduate Student Prize, BSc in Mathematical Engineering, Politecnico di Milano (academic year 2006–2007)