Introduction to Data Science and Machine Learning








































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Introduction to Data Science and Machine Learning
GeoAI / Geospatial Data Science (Geoinformatics)
My research explored artificial intelligence tools within the geographic domain, adapting state-of-the-art artificial neural network architectures into the context of geospatial analysis. It primarily involved human mobility processing (time-series-based formats) and remote sensing applications (image-based formats), targeting an automatic extraction and use of space-time information without any human knowledge assistance.
EDUCATION
Feb 2018 – May 2021:
•PhD in Applied Geoinformatics, University of Salzburg (Salzburg, Austria).
PhD Thesis: Artificial neural networks for human mobility analysis and spatial-temporal activity modeling.
(Supervisors: Prof. Euro Beinat, Dr. Pavlos Kazakopoulos).
• Oct 2015 – Dec 2017:
MSc in Biomedical Engineering, Politecnico di Milano (Milan, Italy).
Master Thesis: Identification of atrial fibrillation from RR intervals: a feasibility study on Long Short-Term Memory neural networks.
(Supervisors: Prof. Manuela Ferrario, Prof. Joseph Randall Moorman).
• Sep 2011 – Feb 2015:
BSc in Biomedical Engineering, Politecnico di Milano (Milan, Italy).
Bachelor Thesis: Biomedical sensor system for physical activity monitoring.
(Supervisor: Prof. Giambattista Gruosso).
WORK AND RESEARCH EXPERIENCE
•Aug 2021 – July 2023:
Postdoctoral Research Fellow in Artificial Intelligence at the Department of Computer Science and Engineering, Southern University of Science and Technology (Shenzhen, China).
Research topic: GeoAI – Artificial Intelligence for geospatial applications.
• Feb 2018 – May 2021:
PhD researcher in Applied Geoinformatics at the Doctoral College “GIScience”, Department of Geoinformatics - Z_GIS, University of Salzburg (Salzburg, Austria).
Fully-funded position by the Austrian Science Fund (FWF).
Research topic: Artificial neural networks for human mobility analysis and spatial-temporal activity modeling.
•Mar 2020 – Jul 2020:
Research intern in Naspers and Prosus AI team (Amsterdam, The Netherlands), and collaborations with iFood AI team (Sao Paulo, Brazil) on behalf of Prosus.
Paid internship position by Prosus, within the context of PhD research stay abroad.
Research topic: Predicting urban distribution of short-term food delivery demand (side works also comprise restaurant churn forecasting, demand shaping strategies
and customer recommendations).
• Mar 2017 – Sep 2017:
Visiting researcher at the University of Virginia Health System (Charlottesville, VA, USA).
Invited research guest for developing the experimental part of the Master Thesis.
Research topic: Deep learning for automatic cardiac arrhythmias detection
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