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Data Science Master, Sapienza University of Rome. Internship,Tandon School of Engineering NYU. topics: python, javascript, visual analytics, machine learning.
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llmops-ci
July 5, 2025 – July 11, 2025
When deploying LLM calls on raw conversation data, it is paramount to programmatically verify that the LLM calls are still returning expected results. In this repository, I demonstrate how to set this up using Langfuse (open source) and GitHub Actions. The small dataset (on pet food customer service) was generated by an LLM.
View ProjectGNN-KNIME-integration-
January 10, 2023 – June 24, 2023
GNN-KNIME-integration- — GitHub repository
View ProjectKNIME-Extension-Example
August 8, 2022 – April 3, 2023
This git repository is used to share the code used in the example to create KNIME nodes in Python for KNIME Blog.
View Projectpartial_dependence
December 20, 2017 – April 9, 2022
Python package to visualize and cluster partial dependence.
View Projecttheme-datasapiens
October 27, 2017 – October 30, 2017
theme-datasapiens — GitHub repository
View Projecttweepy_graph_on_mongolab
May 28, 2017 – May 28, 2017
tweepy_graph_on_mongolab — GitHub repository
View ProjectweekStar
August 22, 2016 – March 21, 2017
This exercise is able to represent interactively the star of seven tips that pagans used to pray the old gods in ancient times and which is still present in week days names (https://en.wikipedia.org/wiki/Names_of_the_days_of_the_week) -->
View Projectcenda
May 9, 2016 – May 13, 2016
Some graph model and algorithms to be applied on Data Center topology
View ProjectCultural Fit Analysis
The candidate's projects are diverse in scope, ranging from data science to web development, indicating a broad interest. However, the lack of professional experience or team-based projects makes it difficult to assess cultural fit in a collaborative work environment. The projects are primarily personal, which might suggest a preference for independent work, but this is an inference due to insufficient data.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's profile primarily lists personal technical projects without team context or professional experience.