Author: Erica Tavazzi

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Hosting and Contributing to Mt Hood Challenge Conference 2026

Recently, our group contributed to the local organisation and hosting of the Mt Hood Challenge Conference 2026, held in Padova from 2 to 4 October and co-organised in collaboration with the REDDIE – Real-World Evidence for Decisions in Diabetes project. The meeting brought together an international community working on health economics and simulation modelling in diabetes, with a strong focus on transparency, comparability and methodological innovation. This year’s programme included challenges on reference simulation, comorbidity and dementia, synthetic data, and presymptomatic screening in type 1 diabetes, alongside discussions on emerging applications of AI in health economic modelling.

Our group took on several roles throughout the scientific programme. Erica Tavazzi chaired the session Diabetes & Its Complications, Sara Poletto chaired Applied Health Economics and contributed to the REDDIE session on Synthetic Data for Diabetes Simulation, Sergio Gaiotti chaired Diabetes & Its Complications II, and Enrico Longato contributed a talk to the invited session Health Economic Modelling in the Age of AI.

The conference was also a valuable opportunity to reconnect with many REDDIE partners, strengthening ongoing collaborations and creating space for new ideas and joint methodological work.

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Advancing ALS Research: Talk on Progression Prediction at “Skeletal Muscle in ALS”

On September 25–26, our group is taking part in the international conference “Skeletal Muscle in ALS – Mechanisms, Biomarkers, and Therapeutic Perspectives”, held in Padova and organised by ASLA APS, with Gianni Sorarù, Maria Pennuto, Manuela Basso and Matteo Zanovello as members of the organising committee. The conference brings together researchers and clinicians to discuss the role of skeletal muscle in ALS, from disease mechanisms and biomarkers to emerging therapeutic strategies.

As part of the session “Muscle Biomarkers in ALS”, our group leader Barbara Di Camillo will present the talk “Toward reliable and responsible ALS progression prediction: development and external validation of clinical models”, focusing on the development of computational approaches for reliable prediction of ALS progression.

The conference highlights the increasingly interdisciplinary nature of ALS research, connecting neurology, molecular biology, biomarker research and data-driven approaches to better understand disease progression and support more personalised strategies. 

We warmly thank the organisers for the invitation and for creating this opportunity for exchange across different areas of ALS research.

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SysBioBiG at the XLV GNB Annual School on Generative Artificial Intelligence

Last week, Barbara Di Camillo, Davide Dei Cas, and Sergio Gaiotti from our research group attended the XLV GNB Annual School – “Generative Artificial Intelligence for Bioengineering” in Brixen.

The school explored the methodological and practical applications of Generative AI in bioengineering, including data analysis, biological modelling, experimental design, and scientific communication.

🎤During the school, Barbara delivered a lecture on Responsible AI, focusing on data quality, model validation and generalisation, interpretability, and human oversight.

💻🏆Davide and Sergio participated in the school and in the hands-on challenge. The week ended with a great result: Davide’s team won the challenge with a project on generating dermatoscopic images from conventional clinical images of skin lesions.

The school was a valuable opportunity to deepen our knowledge of Generative AI, reflect on its responsible use, and exchange ideas with researchers from different areas of bioengineering.

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SysBioBiG at CIBB 2026 in Rome

Our research group participated in the 21st Conference on Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB 2026), held in Rome from September 2 to 4, 2026.

During the conference, our PhD student Sergio Gaiotti presented the contribution “Treatment persistence drives estimator performance in longitudinal causal inference based on observational data: A simulation study”, authored by Sergio Gaiotti, Sara Poletto, Enrico Longato, Erica Tavazzi, and Martina Vettoretti.

The work, developed within the European REDDIE – Real-World Evidence for Decisions in Diabetes project, investigates how treatment dynamics influence the performance of causal inference methods for longitudinal observational data. In particular, the study highlights the role of treatment persistence in determining the behaviour of baseline and longitudinal estimators, showing that treatment dynamics can have a greater impact than functional complexity on estimator performance.

We thank the session chairs and the CIBB 2026 organisers for the stimulating discussion and for another great edition of a conference that has long been a regular appointment for our group.

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Two Research Contributions from Our Group Presented at ATTD 2026

Last week, our research group had the opportunity to take part in the 19th International Conference on Advanced Technologies and Treatments for Diabetes (ATTD 2026), held in the fascinating city of Barcelona, Spain.

During the conference, our PhD student Sara Poletto presented two research contributions developed within the framework of the European project REDDIE, which we are proud to be part of.

Advancing research in diabetes is essential to improve prevention, management, and quality of life for millions of people worldwide, and we are excited to contribute to this collective effort.

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Our Research Group at AI@DEI 2025 – From Research to Industry

Last week our research group took part in AI@DEI 2025 – From Research to Industry, the annual event organised by the Department of Information Engineering (DEI) of the University of Padova and the Regional Innovation Network IMPROVENET, with the support of UniSMART.
The initiative aims to strengthen the dialogue between academia and industry, showcasing concrete applications of Artificial Intelligence across a wide range of sectors, from computer vision to predictive maintenance, industrial decision-making, robotics, automation, and conversational technologies.

As part of the programme, our researcher Erica Tavazzi delivered the presentation: “Fondo Italiano per le Scienze Applicate: AI e diagnostica avanzata nella partnership DEI–AB Analitica contro l’antibiotico resistenza”.

The talk, prepared together with Dino Paladin (AB Analitica), introduced READY – Responsive Early Antibiotic resistance Detection and therapY, the project funded by the Italian Applied Sciences Fund (FISA) and launched this year. READY focuses on integrating AI, automation, and advanced diagnostics to support the early detection of antimicrobial resistance.

We warmly thank DEI, IMPROVENET, and UniSMART for organising the event, as well as all participating companies and colleagues for the productive exchange of perspectives.
A special acknowledgement goes to Sara Brugnerotto, whose photos beautifully captured the atmosphere of the day.

Systems Biology and Bioinformatics Group
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