I'm an enthusiastic learner with a passion for Machine Learning and Artificial Intelligence. I have a Bachelor’s Degree in Mathematics (with a focus on Computer Science), and a Master’s Degree in Data Science and Scientific Computing, which felt as the natural combination of my interests.

I have worked on several Machine Learning projects, available on GitHub, mainly in Deep Learning and Reinforcement Learning topics, one also developed in a HPC environment. I've done also two projects in software development: one in C++ using TravisCI for continuous integration and one in Java using Gradle and agile programming techniques. My main programming language is Python.

• Daily analysis of the EU Amazon XL network for a prompt resolution of service disruptions and potential structural problems, ensuring the best Customer Experience possible.
• Developing a bot to examine the current state of the network, reporting all the disruptions that occurred for a further deep dive.

• Using Reinforcement Learning to optimize the resolution of the city’s power grid outages.

Dissertation: Optimizing fault search in power grid outages through Reinforcement Learning. GitHub
Supervisors: Antonio Celani (ICTP), Andrea Zancola (AcegasApsAmga), Luca Bortolussi (UniTS), Emanuele Panizon (ICTP).

Relevant courses: Introduction to Machine Learning, Statistical Machine Learning, Information Retrieval, Deep Learning, Reinforcement Learning, Advanced Programming and Algorithmic Design, Software Development Methods, Data Management for Big Data.

Dissertation: Gröbner bases and computational applications Supervisor: Willem de Graaf (UniTN).

Relevant courses: Mathematical Statistics, Programming 2, Algorithms and Data Structures.

• Achieved an initial average of 12 points out of 448 (which would increase with more time and more cluster resources) in the game “Breakout” using Double (Deep) Q-Learning. GitHub

• Analyzed and forecasted the evolution of the Covid-19 outbreak in central Colombia in R using different Statistical Methods: Generalized Linear Models (GLM), Generalized Additive Model (GAM) and Bayesian models. GitHub

• Implementation and testing of a Binary Search Tree in C++, which is about 15% faster than std::map, depending on the operating system. GitHub

• Development of the game "Dots and boxes" and an intelligent player which learns how to play using Reinforcement Learning. GitHub

• A review of the literature concerning Graph Neural Networks for the course of "Deep Learning". GitHub

• Implementation in Python of an Information Retrieval system using the Boolean Model. GitHub

• Group project on the pen-and-paper Freedom game using Java and Gradle, we performed continuous integration using Travis CI, and adopted the Agile practices. GitHub

• Data Visualizations on some aspects of our relationship with the infosphere and how it changed with the rise of the Internet. GitHub

• Finite Element Solver for the Allen-Cahn Equation. GitHub

• Leaf classifier using Machine Learning.

Operating systems:

Programming Languages:

• 👀 I’m interested in Machine Learning and Artifical Intelligence
• 🌱 I’m currently studying for the ''AWS Certified Cloud Practitioner'' certification
• 🤝 Founding Member (2020) and Directive Board Member (2020–2021) of the “Artificial Intelligence Student Society” (AI2S). I was in charge of the Member Services.
• 💞 I love reading: I’m an avid reader of novels: classics, romance, crime, historical, and fantasy.