People

Alessandro Crivellari

CONTACT INFO


Alessandro Crivellari

Assistant Professor

 

Office :Room 508, Department of Geography

Email : alessandrocr@ntu.edu.tw

Phone :+886-2-33665828

 

 


BIOS


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. 


RESEARCH


GeoAI / Geospatial Data Science (Geoinformatics)


EDUCATION


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


COURSES


Introduction to Data Science and Machine Learning


PUBLICATIONS


AuthorDate of PublicationTitleSource
Chunzhu Wei, Hong Wei, Alessandro Crivellari, Taichang Liu, Yuanmei Wan, Wei Chen, and Yang Lu 2023-11 Gaofen-2 satellite image-based characterization of urban villages using multiple convolutional neural networks International Journal of Remote Sensing
Alessandro Crivellari, Hong Wei, Chunzhu Wei, Yuhui Shi 2023-07 Super-resolution GANs for upscaling unplanned urban settlements from remote sensing satellite imagery–the case of Chinese urban village detection International Journal of Digital Earth
Omid Ghorbanzadeh, Alessandro Crivellari, Dirk Tiede, Pedram Ghamisi, Stefan Lang 2022-12 Mapping dwellings in IDP/refugee settlements using deep learning Remote Sensing
Hao Jing, Xin He, Yong Tian, Michele Lancia, Guoliang Cao, Alessandro Crivellari, Zhilin Guo, Chunmiao Zheng 2022-11 Comparison and interpretation of data-driven models for simulating site-specific human-impacted groundwater dynamics in the North China Plain Journal of Hydrology
Alessandro Crivellari, Bernd Resch 2022-06 Investigating functional consistency of mobility-related urban zones via motion-driven embedding vectors and local POI-type distributions Computational Urban Science
Alessandro Crivellari, Euro Beinat, Sandor Caetano, Arnaud Seydoux, Thiago Cardoso 2022-02 Multi-target CNN-LSTM regressor for predicting urban distribution of short-term food delivery demand Journal of Business Research
Alessandro Crivellari, Bernd Resch, Yuhui Shi 2022-02 TraceBERT — A feasibility study on reconstructing spatial–temporal gaps from incomplete motion trajectories via BERT training process on discrete location sequences Sensors
Omid Ghorbanzadeh, Hejar Shahabi, Alessandro Crivellari, Saeid Homayouni, Thomas Blaschke, Pedram Ghamisi 2022-01 Landslide detection using deep learning and object-based image analysis Landslides
Omid Ghorbanzadeh, Alessandro Crivellari, Pedram Ghamisi, Hejar Shahabi, Thomas Blaschke 2021-07 A comprehensive transferability evaluation of U-Net and ResU-Net for landslide detection from Sentinel-2 data (case study areas from Taiwan, China, and Japan) Scientific Reports
Alessandro Crivellari, Alina Ristea 2021-04 CrimeVec — Exploring spatial-temporal based vector representations of urban crime types and crime-related urban regions ISPRS International Journal of Geo-Information
Alessandro Crivellari, Euro Beinat 2020-12 Forecasting spatially-distributed urban traffic volumes via multi-target LSTM-based neural network regressor Mathematics
Alessandro Crivellari, Euro Beinat 2020-06 Trace2trace — A feasibility study on neural machine translation applied to human motion trajectories Sensors
Alessandro Crivellari, Euro Beinat 2020-01 LSTM-based deep learning model for predicting individual mobility traces of short-term foreign tourists Sustainability
Alessandro Crivellari, Euro Beinat 2019-08 From motion activity to geo-embeddings: Generating and exploring vector representations of locations, traces and visitors through large-scale mobility data ISPRS International Journal of Geo-Information
Alessandro Crivellari, Euro Beinat 2019-07 Identifying foreign tourists’ nationality from mobility traces via LSTM neural network and location embeddings Applied Sciences
Anna Kovacs-Györi, Alina Ristea, Ronald Kolcsar, Bernd Resch, Alessandro Crivellari, Thomas Blaschke 2018-09 Beyond spatial proximity — Classifying parks and their visitors in London based on spatiotemporal and sentiment analysis of Twitter data ISPRS International Journal of Geo-Information

GRANTS


Fiscal YearPlan NameTitle
112 以生成式人工智慧保護人類移動軌跡之隱私 計畫主持人

AWARD


• 2nd prize at the Young Investigator Award 2020 (University of Salzburg)
• 2nd prize at the Mouse Behavior Challenge 2020 (Hiroshima University)
• 3rd prize at the Basketball Behavior Challenge 2020 (Hiroshima University)