Diego Piccinotti Email & Phone Number

Modena, It

Modena, Emilia-Romagna, Italy

Modena, Emilia-Romagna, Italy

• Managed infrastructure, both cloud and on premise, for the Data Team, introducing release and deployment automation processes that greatly reduced the manual effort in maintaining our services• Was responsible for representing the team in cross functional projects, liaising with Engineering and Data Science to drive our infrastructure solutions towards the needs of the company• Built internal tooling to streamline operations in the team, leveraging a ReactJS / Python / MongoDB stack• Upskilled the team members on their Python learning path and worked with them on different projects to solidify their knowledge

Among the few Italian students selected to be mentees for LeadTheFuture, a leading mentorship non-profit organization for students in STEM, with acceptance rate below 20%. LeadTheFuture empowers top-performing students to achieve their goals and contribute to their communities by giving them one-on-one guidance from high-impact mentors coming from the world's leading STEM innovation hubs such as Silicon Valley and CERN.

Milano, Lombardia, Italia

Responsible for the design, implementation and deployment of ML based solutions.• Participated in the development of the AD cube platform, working with AWS cloud technologies, Docker and Python to ingest data from marketing platform APIs, deliver backend services to the platform and serve ML models through REST APIs.• Part of the consultant pool of the company, worked on Sales Forecasting solutions and Expert Learning techniques.

Milano, Lombardia, Italia

• Implemented a Monte-Carlo Tree Search based agent for pit-stop strategic planning in Formula 1, outperforming real strategies in simulation.• Built a ML-based model to predict drivers’ lap times in F1 races through regression.• Extended the original Python code base for single-player games to work in a multi-agent setting.

Parma, Italia

• Implemented a deep neural style transfer system based on CycleGAN, which matched state-of-the-art performance on CycleGAN paper’s reference dataset.• Adapted and tested the system to work with Adidas on a proprietary dataset of images of shoes, successfully converting sketches to final product pictures and vice-versa.• Acquired experience in neural networks design and implementation with Keras and Tensorflow in Python.

Master Of Science - Msc, Computer Science And Engineering, 106/110

Artificial Intelligence and Machine Learning track

Bachelor Of Science - Bsc, Computer Engineering, 110 Cum Laude

Ingegneria Informatica, Elettronica e delle Telecomunicazioni - Curriculum Ingegneria Informatica