I hold a bachelor's degree in Management and Computer Science from LUISS and I have gratuated with highest honors from the Data Science Master's Degree @Sapienza. I am now a PhD Student in Data Science @Sapienza.

Through university and (a lot of) self-studying I have a solid background in data science, from simple ETL to modelling. In particular, I have in-depth knowledge of:

• R for machine learning, modelling, statistics, reporting (R Markdown) and data manipulation, exploiting the tidyverse ecosystem far more than the base language.
• Python for scripting, manipulation, modelling and web scraping. Specifically, my experience revolves mostly around Pandas, NumPy, scikit and Tensorflow. Experience with Tensorflow has been both with Keras and more low-level APIs.
• KNIME Analytics Platform and KNIME Server, now Business Hub, due to university projects and work experience. Specifically, I am L1, L2 and L3 certified.
• Relational paradigm for databases and SQL.

I am a former Data Science Intern @KNIME, the software company behind KNIME Analytics Platform (and its enterprise version), a popular and powerful low-code tool to perform data science tasks, at every level. As an employee, I developed KNIME native low-code approaches for the Word2Vec complete pipeline and I also developed a fast new Python-based Word2Vec node based on Tensorflow, using a mix of low-level APIs (mainly for the pre-processing) and Keras for the modelling steps. The code for the node is publicly available in one of my repositories, at this link.

My research interests are mainly in mathematics: probability theory and statistical inference for stochastic processes (specifically, diffusions), theoretical computer science, algorithmic game theory and statistical learning theory applied to AGT topics. I work at the Department of Computer, Control, and Management Engineering @Sapienza in the group managed by Prof. Stefano Leonardi. I also help teaching a variety of courses in Sapienza, stemming from randomized algorithms to statistics and stochastic processes.

You can find here a list of publications and/or activities related to my research:

• Neural Drift Estimation for Ergodic Diffusions: Nonparametric Analysis and Numerical Exploration, New Trends in Functional Statistics and Related Fields, with Francesco Iafrate. The work is published as a proceeding of IWFOS 2025 (International Workshop on Functional and Operatorial Statistics), which was held in Novara, Italy.
• Nearly Tight Regret Bounds for Profit Maximization in Bilateral Trade, FOCS 2025, with Federico Fusco, Chris Schwiegelshohn and Paul Duetting. (See you in Sydney in December!) I also presented the work at EC (Economics and Computation) in Stanford this year.

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