Medicine, Life Sciences, and Environment



Life Sciences, broadly including Medicine, Healthcare and Public Health Sciences, drive conception and development of technologies that in the last decades have been impacting our society the most. The general context is to understand complex biological phenomena, measure the effect of therapeutical interventions on single patients and across the population and enhance our ability to predict disease trajectories in single individuals, as well as in the broader society. Parallel to this human-centred perspective, environmental challenges especially related to the global change are also calling for data-driven solutions. Environmental sciences fall in the big-data paradigm and require innovative and challenging approaches for producing novel and reliable findings.

Research Topics

In this curriculum we apply machine learning and artificial intelligence to heterogenous data sources in genomics, medical images, electronic health records and human patterns data, within the broad context of oncology, neurological disorders, cardiac diseases and infectious diseases epidemiology. We also work on biodiversity informatics to improve our knowledge of the environment, with the aim to provide us baseline for adapting to and mitigating the effects of global changes in the coming years.

Expected Outcome

Profiles developed in this curriculum will be able to contribute on the applications of machine learning and artificial intelligence to the fields of bioinformatics, biostatistics, biodiversity informatics, computational epidemiology and systems biology. Graduates in this track will be ready to apply successfully for lead data science positions in companies and Public Health agencies, as well as to pursue research careers in both the public and private sectors.

ADSAI people

Curriculum Coordinator: Prof. Giulia Barbati

Faculty Members

Adjoint Faculty Members