Tag: news

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.

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.

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.

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.

Last week, Giacomo attended HPCSIM25 – Frontiers of High-Performance & Cloud Computing in Modeling and Simulation, held in Padova, Italy, on September 11–12, 2025.

The event focused on the latest methodologies and technologies in the field of High-Performance Computing (HPC), offering researchers and practitioners an overview of the current landscape and future directions of HPC in both real-world applications and scientific research.

Giacomo delivered an oral presentation titled “High-Performance Scientific Computing in Veneto: The CONVECS Initiative”, introducing the CONVECS project (COmuNità VEneta per il Calcolo Scientifico) where he is responsible for leading multiple core tasks. This initiative, recognized as an Operation of Strategic Importance by the Veneto Regional Government, aims to enhance, consolidate, and interconnect the HPC infrastructures currently available across universities and research laboratories in the Veneto region. Its goal is to create a unified, scalable computing environment accessible to both academic researchers and technology-driven enterprises, driving measurable impact in science, industry, and society.

Last week we attended the 20th Conference on Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB2025) in Milano from September 10th to 12th, 2025.

We’re proud to share that our group contributed to the scientific program with three oral presentations showcasing our recent research efforts:

🧠 Piero Mariotto, Ilaria Patuzzi, Giada Innocente, Barbara Simionati, Barbara Di Camillo, Giacomo Baruzzo “A network science-based approach to unveil the effects of faecal microbiota transplantation in enteropathic dogs” (great collaboration with EuBiome srl)

📊 Federico De Mori Bajolin, Anna Maria Bianchi, Erica Tavazzi “A multivariate deep-learning approach for stratifying Amyotrophic Lateral Sclerosis patients based on temporal dynamics“

💉 Davide Dei Cas, Barbara Di Camillo, Gian Paolo Fadini, Giovanni Sparacino, Enrico Longato “The impact of clinical history on the predictive performance of machine learning and deep learning models for renal complications of diabetes“