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)
PhD students
Raffaele Marchesi
- Generative AI for clinical data (2023-2026)
Nazia Nafis
- Generative AI and bias in clinical data (2023-2027)
Bojana Velickovska
- Algorithmic bias and health inequalities (2021-2024)
Walter Endrizzi
- Predictive models for neurodegenerative diseases (2023-2026)
Mahta Darvish
- Postoperative predictive models for obese children (2024-2027)
Former PhD students
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 students
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.
