🇮🇹 Italian
Massimo Pignatti

Massimo Pignatti

About Me

I am passionate about Artificial Intelligence and Machine Learning, with a particular interest in the internal workings of models and their practical applications.

I have experience in developing machine learning models, data analysis, and building modern web applications.

I mainly focus on designing functional solutions to real-world problems, paying attention to both algorithmic aspects and software efficiency.

I am currently completing my Master’s degree in Artificial Intelligence at the University of Bologna.

Education

Internships & Work

Languages

Skills

Programming Languages

Python
Java
C++
C
JavaScript

Frameworks & Libraries

React
Next.js
Node.js
FastAPI

Machine Learning

TensorFlow
PyTorch
Scikit-learn
Hugging Face

Databases

PostgreSQL
MongoDB

Data Engineering

dbt
Apache Airflow

DevOps & Tools

Git
Linux
AWS S3
AWS EC2
Microsoft Azure

Portfolio

Spotify Playlist Generator

AI-based project for generating Spotify playlists by recognizing music genres.

View on GitHub

AltTablut

AI bot for the Tablut game, ranked second in a university competition.

View on GitHub

Tondo Website

Development of a customizable platform accessible via QR code. Allowed businesses to manage menus, buttons, and dynamic content. First challenge working with AWS S3 for scalable hosting.
Private code

FamilyApp

Family management app: shopping list, shared calendar, and activities.
Private code

CarParking

Real-time vehicle tracking using NFC technology.
Private code

Squealer Social Network

Full-stack developed social network inspired by Twitter.

View on GitHub

MailSender

Monitoring service that automatically sends emails based on system status.
Private code

BitChess

Strategic AI project to win in "Really Bad Chess" mode.
Code unavailable

B.Future Hackathon – Amadori

Third place as a team in the Amadori challenge at the B.Future Hackathon. In addition to the full‑stack web platform (frontend + backend), I designed a Linear Programming algorithm to efficiently manage minced‑meat batches and mixtures, optimising resource usage across the production process.

GenHack4 – Generative Modelling Hackathon

Award winner at GenHack4, an international hackathon on generative models. Designed pipelines for data downscaling and modelling of complex phenomena, including evaluation of model performance with dedicated metrics.

BookShelf Vision

Image Processing and Computer Vision project for reading books on shelves. The system detects book spines, segments text regions and extracts titles and authors via OCR, automatically building a digital catalogue.

Contact