Luca.
I design data-driven approaches for Real-World Evidence
Driven by an unwavering enthusiasm, I am committed to making a significant impact in healthcare, society and inspiring others with my determination.
Hi, my name is
About Me
I am a PhD candidate at KTH Royal Institute of Technology, enrolled in the medicine and technology program. My research project focuses on developing data-driven approaches to achieve real-world evidence in various healthcare fields, including oncology, clinical trials design, emergency medicine, psychiatry care for children and adolescents, and health complex adaptive systems.
With a background in applied physics, I have previously worked on successfully developing deep learning and complex graph theory applications in neuroimaging.
In my spare time, I love exploring everything from tech and innovation to culture and history. It’s important for me to keep a balanced lifestyle, which comes naturally thanks to my background as a high competitive sprint kayaker. My time on the water taught me discipline and helped me to win both national and international competitions.
I speak English (C1), Italian (Native Speaker), French (B1), and Swedish (B1).
Experience
Research consultant and teaching assistant (PhD duties)
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KTH Royal Institute of Technology
Jun 2020 - present
As a PhD student, I undertook departmental duties that included assistant teaching, supervising student projects, and providing consultancy to healthcare institutions involved in my research projects.
I worked on two consultancies. One regarding emergency department and hospital overcrowding for the Akademiska sjukhuset hospital (Uppsala, Sweden), and the other regarding coordination of paediatric and adolescents psychiatric care units for the Stockholm region Barn och UngdomsPsykiatri, BUP (Stockholm, Sweden).
I have been part of the core team for the Centre of Data-Driven Healthcare (CDDH, https://www.kth.se/cddh), and the Young Professional Cancer (YCP) group of the European Cancer Organisation (https://www.europeancancer.org/content/young-cancer-professionals.html).
I did teaching classes for the courses on Statistics, Machine Learning, Simulation and Modelling, and Project Carrier Course.
I was the main supervisor of nine thesis projects (four bachelor, and seven master students). See more on my KTH profile.
Traineeship on cloud computing to train machine learning models for scientific research
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National Institute of Nuclear Physics
May 2019 - July 2019
During my master thesis, I learnt how utilise cloud parallel computing techniques at the Italian National Institute of nuclear Physics (INFN).
I used the resources of the data-centre ReCaS (https://www.recas-bari.it/index.php/en/) to analyse large MRI datasets, create complex brain structure graphs, and run deep learning algorithms for brain age prediction.
My work lead to a scientific publication at the peer-reviewed journal Neuroimage (Bellantuono, L., Marzano, L., La Rocca, M., Duncan, D., Lombardi, A., Maggipinto, T., … & Bellotti, R. (2021). Predicting brain age with complex networks: From adolescence to adulthood. NeuroImage, 225, 117458.).
During my studies, as a competitive athlete in kayak, I worked part-time as a coach at the italian centre of sports (CUS) in Bari, Italy.
I was a certified by the italian federation of canoe and kayak as basic-level kayak coach.
My role was teaching how to kayak to children and university students at basic level.
Education
2020 - current
PhD candidate in Medicine and Technology
KTH Royal Institute of Technology
- Thesis title: Perspectives on designing data-driven approaches for real-world evidence in healthcare.
- Doctoral courses I took for my education duties (60 ECTS): Theory of Science and Research Method, Technological and Natural Sciences; Technology an Health; Transparency in Technical and Social Systems; Gaming and Participatory Simulation for Research and Design; Involving old people in engineering and design; Visualize your Science; Writing Scientific Articles; Nature Scientific Writing and Publishing Training; Serious Games for Analyzing and Supporting Complex Decision-Making; Entrepreneurship in Technology and Health; Physiologically Based Pharmacokinetic Modeling.
- Most of my publications are in affiliation with KTH. See more on my KTH profile.
2017 - 2019
Master Degree in Applied Physics (Cum Laude)
University of Bari Aldo Moro, Physics Department Michelangelo Merlin
- Thesis title: Deep Learning Methods for accurate prediction of brain age
- Publication: My thesis work was published on the peer reviewed journal Neuroimage
2018 - 2019
Erasmus+ Exchange
Université Lille 1
Erasmus exchange at Lille (France) during the first semester of the second year of the Master Degree.
2014 - 2017
Bachelor degree in Physics
University of Bari Aldo Moro, Physics Department Michelangelo Merlin
Thesis title. Algoritmi di deep learning dell’analisi di dati scientifici
Certified courses attended at other institutions
- 2022, Physiologically Based Pharmacokinetic Modeling Winter school, University of Eastern Finland, (2 days, 2 ECTS)
- 2022, Serious Games for Analysing and Supporting Complex Decision-Making Summer school, Radboud University (1 week, 3 ECTS)
- 2019, Data Science and Big Data Analytics Summer school, UCL - University College of London (3 weeks, 7.5 ECTS)
- 2019, Big Data in Health Research Summer school credits, University of Utrecht (1 week, 3 ECTS)
- 2018, Computational Engineering and Technical Physics. Computer Vision and Medical Imaging Summer school, Lappeenranta University of Technology (1 week, 3 ECTS)
Projects
Oncology
Small cell lung cancer
Real-world evidence to improve treatment decision and clinical trials design of small cell lung cancer
Doctoral thesis project in collaboration with the department of of Oncology-Pathology, Karolinska Institutet and the Thoracic Oncology Center, Karolinska University hospital (Stockholm, Sweden)
Health Systems
Operational Management
Emergency department and hospital overcrowding
Consultancy for the Akademiska sjukhuset hospital (Uppsala, Sweden). The purpose was to study and propose solutions to the overcrowding of the Emergency department and the hospital wards by analysing one year of healthcare production data.
Health Systems
Operational Management
Policy Making
Coordination of units for paediatric and adolescents psychiatric care units of Stockholm Region
Consultancy for the Stockholm region units of psychiatry care for children and adolescents, Barn och ungdomspsykiatri (BUP). The purpose was to conduct an exploratory analysis of the BUP units to discuss about workload issues and identify potential process improvements, from both logistic and clinical perspective.
Primary Healthcare delivery
Health Systems
Policy Making
What parameters should we improve or optimise in Swedish healthcare?
Series of proposals and students supervision for master thesis projects. Swedish primary healthcare delivery and emergency medicine were studied in dept using several approaches (e.g., simulation models, serious games, and explainable machine learning)
Achievements
Get in Touch
Mail me if you would like to receive my Resume/CV documentation. References are available under request. My inbox is always open. Whether you have a question or just want to say hi, I’ll try my best to get back to you! Vi ses snart!!!