Experience

Università di Pisa

• Higher Education
• 700 & Above Employee

• PHD Student

  • Nov 2021 - Present

  Student of the Italian National PhD in Artificial Intelligence https://www.phd-ai.it/en/359-2/ Admitted to the AI & Society track Relevant publications: * Main-author paper accepted at CIKM 2022 (A+ GGS rating) "Cascade-based Echo Chamber detection" * Paper accepted at ICWSM 2022 (A GGS rating) "The Effect of People Recommenders on Echo Chambers and Polarization" * Paper accepted at IDEAS 2023 (B GGS rating) “Exploiting Deep Learning and Explanation Methods for Movie Tag Prediction” * Main-author paper published at ISMIS 2022 (Q2 journal in AI) "Learning and Explanation of Extreme Multi-label Deep Classification Models for Media Content" * Co-author of several health-related publications involving statistical modeling. Service: * Review Committee of SAC 2023 - MLA track (A- GGS rating) * Reviewer for international journals: KAIS, TKDD. * Reviewer for international conferences: WWW, ECML-PKDD, WSDM, ICDM, ASONAM. * Co-supervised two M.Sc. thesis in Computer Science (work under review at A++ conference) Others: * 6-months industrial internship at Amazon Music, Personalization team Show less



Amazon Music

• United States
• Entertainment Providers
• 700 & Above Employee

• Applied Scientist

  • Nov 2022 - Apr 2023

  Amazon Music, ML for Personalization. Working on Catastrophic Forgetting in Learning-To-Rank models. Amazon Music, ML for Personalization. Working on Catastrophic Forgetting in Learning-To-Rank models.



Eurecat - Technology Centre of Catalonia

• Spain
• Research Services
• 500 - 600 Employee

• Visiting PHD Student

  • Jul 2022 - Jul 2022

  Collaboration with Dr. Francesco Fabbri to design a framework for studying the effects of Algorithmic Radicalization caused by Recommender Systems. Currently under review. Collaboration with Dr. Francesco Fabbri to design a framework for studying the effects of Algorithmic Radicalization caused by Recommender Systems. Currently under review.



ICAR-CNR

• Italy
• Research Services
• 1 - 100 Employee

• Research Fellow

  • Nov 2020 - Nov 2021

  This fellowship aims to develop innovative methods at the intersection between Research and Industry. Main topics: - Recommender Systems - Knowledge Graph - Content Enrichment: Automated tagging of unseen content. This fellowship aims to develop innovative methods at the intersection between Research and Industry. Main topics: - Recommender Systems - Knowledge Graph - Content Enrichment: Automated tagging of unseen content.



Revelis s.r.l.

• Italy
• IT Services and IT Consulting
• 1 - 100 Employee

• Data Scientist

  • Jan 2020 - May 2020

  Data Scientist in charge of developing software solutions for Machine Learning Projects. Problems: - Supervised Learning for chemical-physics properties. (Logistic Regression, Decision Trees, Greedy Algorithms for Outliers Detection) - Unsupervised Learning for Anomaly Detection. (AutoEncoder, KMeans, Random Forest, etc.) - N-step ahead forecasting for Time Series. (Poisson AutoRegressive Model) - Computer Vision for Public Security. (YOLO, SSD, RetinaNet, etc.). Industries: - Quarry Industry. - Railway Industry. - Public Security. Technology stack: - Python3 along with Pandas, Numpy, Scipy, Scikitlearn, Pytorch, Keras, PySpark and Matplotlib+Seaborn. - R along with MASS, e1071, ggplot, faraway and many other packages. - Jupyter Notebook, PyCharm and Git. - Familiarity with Docker and Kubernetes. Project Development Methodologies: - CRISP-DM - SCRUM Show less



Procura della Repubblica di Catanzaro

• Catanzaro, Italia

• Ausiliare Informatico

  • Nov 2019 - Dec 2019

  Svolto le funzioni di Ausiliare Tecnico Informatico nell'ambito di un processo penale per la Procura della Repubblica di Catanzaro. - Analisi forense di telefono cellulare, SIM e SD Card. Svolto le funzioni di Ausiliare Tecnico Informatico nell'ambito di un processo penale per la Procura della Repubblica di Catanzaro. - Analisi forense di telefono cellulare, SIM e SD Card.



Skienda S.r.l.

• Italy
• IT Services and IT Consulting
• 1 - 100 Employee

• Lecturer

  • May 2019 - May 2019

  Taught a 16 hours module about clustering and dimensionality reduction in a professional course for junior data scientists organized by Skienda. Topics: - What is Clustering? - Partitional clustering algorithms. - Hierarchical clustering algorithms. - Density-based algorithms. - Advanced methods: Spectral Clustering. - How to guess the right number of clusters: elbow method and AIC/BIC curves. - Measure the quality of clustering with internal and external criteria like NMI or Silhouette Coefficient. - Applications: Compress a jpeg image, find topics in text corpus and others. - What is Dimensionality Reduction? - Main techniques of dimensionality reduction like PCA, TruncatedSVD. - Use Case #1: PCA to visualize high dimensional datasets. - Use Case #2: PCA to reduce noise in high dimensional datasets. - Use Case #3: PCA to speed up algorithms. - Apply SVD to user-movie ratings matrix to explore latent topics. Additional hard skills: - Extensive use of Pandas and Numpy libraries to work with data. - Extensive use of Matplotlib and Seaborn to produce visual deliverables. Soft skills: - Storytelling using visualizations. - Pair programming during laboratory work. Feedback: - Students passed final questionnaire with an average grade of 8 out of 10. - Students developed portfolio projects about Clustering techniques. Show less



ISI Foundation

• Italy
• Research Services
• 1 - 100 Employee

• Research Intern

  • Feb 2019 - May 2019

  Research intern period to develop my master thesis. The location is the "Algorithmic Data Analytics" research group laboratory in Turin. Technical achievements: - Deep bibliographic research for what regards Opinion Dynamics models, Social Recommendations and Opinion Polarization. - Make use of Python line profiler to analyze code efficiency and, hence, to optimize execution time. Needed to perform Monte Carlo simulations. - Implementation of real world Link Recommendation algorithm like Twitter WTF[1]. - Exploited code solutions on remote server using SSH. - Use of Git as code versioning software. - Extensive use of Latex to produce daily/weekly reports. Soft-skills achievements: - Carried out autonomous work. - Daily and weekly update reporting + weekly brainstorming session within a three-people team. - Work side-by-side with top researchers who worked for Google and Yahoo. Expected output(Work in Progress): - Master Thesis to be completed as soon as possible. - Research Paper to be submitted as soon as possible. References: [1]: Gupta, P., Goel, A., Lin, J., Sharma, A., Wang, D., & Zadeh, R. (2013). WTF: the who to follow service at Twitter. WWW ’13 Proceedings of the 22nd international conference on World Wide Web, , 505-514. Show less