Group members

Former PhD students and post-docs

- Raihana Ferdous (post-doc, now a Senior Researcher with an academic appointment)

- Zeinab Khorshidpour (post-doc, now a Data Scientist with an industrial appointment)

- Mahshid Majd (post-doc, now a deep learning engineer with an industrial appointment)

Andrei Popleteev (PhD, now Research Fellow at University of Luxembourg)
- PhD thesis title: "Indoor positioning using FM radio signals"

Aleksandar Matic (PhD, now Head of Research at Telefonica Research and Development, Alpha)
- PhD thesis title: "Sensing Social Interactions Using Non-Visual and Non-Auditory Mobile Sources"

Alban Maxhuni (PhD, now post-doc at Technical University of Denmark)
- Managing the Scarcity of Monitoring Data through Machine Learning in Healthcare Domain

Seyedmostafa Sheikhalishahi (PhD, now post-doc at Ludwig Maximilian University of Munich)
- Machine learning in Intensive Care Units

Enrique Garcia Ceja (PhD visiting - now at University of Oslo)
- Detecting stress levels in working environments through analysis of smartphone data

Jose Carlos Carrasco Jimenez (PhD visiting - now at Barcelona Supercomputing Center)
- Predicting depressive and manic scores in patients with bipolar disorder through analysis of smartphone data

Elias Ruiz (PhD visiting - now at Instituto Nacional de Astrofísica, Óptica y Electrónica - INAOE)
- Detecting difficulties during dressing in patients with cognitive impairments, through image analysis

Pablo Hernandez-Leal (PhD visiting - now at CWI, Amsterdam)
- Stress modelling and prediction in presence of scarce data

Masters and undergraduate students at University of Trento

Behrooz Mamandipoor
Machine learning in healthcare researcher. Now a PhD student at University of California, San Diego - School of Medicine

Raffaele Marchesi
- Generative Adversarial Network approaches to mitigate health data poverty

Nicolo Micheletti
- Generative Adversarial Network approaches to mitigate health data poverty

Federica Forzanini
- Estimating risk of falls from routinely collected clinical data in patients diagnosed with Parkinson's disease

Walter Endrizzi
- Predicting progression of Multiple Sclerosis using routinely collected clinical data

Eros Zaupa
- Investigating explainable machine learning methods in predicting diabetes related complications

Eric Solinas
- Machine learning models to predict deterioration of critically ill patients

Giacomo Bornino
- Machine Learning prediction of diabetes comorbidities in a large Italian cohort

Nicolò Merzi
- Gender and Geographical Factors Impacting Stroke Admissions

Emiliano Versini
- m-health per la compatibilità tra i farmaci

Matthia Sabatelli
- Understanding mobility of bipolar patients through analysis of WiFi traces

Matteo Chini
- Monitoring sedentary behaviour of knowledge workers and development of a persuasive, mobile interface to encourage healthy, non-sedentary work-style.

Atena Bianchi
- Gathering user requirements to guide the development and evaluation of an adaptable interface for mobile and desktop devices.

Thiago Andrade Lima
- Data mining to analyse behaviour of traumatised/abused dogs and their response to the presence of humans within shelters.