Machine learning,
shipped end to end.

Qualcomm

System on Chip Machine Learning Research and Development Intern

Cork, Ireland

• Machine learning for Electronic Design Automation (EDA) with a focus on placement and routing
• Generative AI for macro and mixed-size placement, and reinforcement learning for routing optimization
• Porting of ML models and libraries to Qualcomm's proprietary hardware and software stack, including Hexagon NPUs

PwC

Associate, Full Stack Software Engineering

Digital Innovation & Strategy · Milan, Italy

• Developed full-stack solutions with Java Spring Boot and Flutter for scalable document management systems
• Deployed AI features using Kubernetes on GCP/Azure and led project coordination with clients to meet business objectives
• Achieved top-tier performance, far surpassing expectations, and awarded Impact Tier 1 in Internal Performance Review

Accenture

Software Analyst

Financial Advisory Solutions & Technology · Padua, Italy

• Contributed to the development and maintenance of core banking software used by major Italian banks
• Built ML models on OpenTelemetry data to predict core microservice failures and improve scaling strategy

Università degli Studi di Milano-Bicocca

Undergraduate Researcher

Milan, Italy

• Developed ML models to estimate optimal Inversion Time (TI) in LGE MRI using SHAP values for interpretability and sensitivity analysis in the absence of analytic regression solutions
• Built TensorFlow models optimized for embedded and mobile execution with quantization and pruning for real-time use
• Created Flutter frontend with FastAPI backend and Firebase integration for real-time interaction with deployed ML models

Politecnico di Milano & KTH Royal Institute of Technology — EIT Master School

Double Degree Master of Engineering, High Performance Computing Engineering & ICT Innovation

Milan, Italy & Stockholm, Sweden

Courses: Advanced Methods for Scientific Computing, Applied Statistics, Artificial Neural Networks and Deep Learning, Bayesian Learning and Montecarlo Simulation, Advanced Mathematical Models in Finance

Ca' Foscari University of Venice — Department of Molecular Sciences and Nanosystems

Bachelor of Engineering, Engineering Physics

Venice, Italy

Thesis: Cloud-Deployed Machine Learning for Inversion Time Estimation in Late Gadolinium-Enhanced MRI (in publication, Insights into Imaging) — Prof. Marco Salvatore Nobile

Courses: Informatics I & II, Calculus I & II, Physics I & II, Quantum Mechanics, Statistics, Business Administration

• Developed ML model to predict optimal TI for LGE MRI, deployed on scalable cloud architecture with mobile frontend
• Awarded the role of Subject Matter Expert for INFO/01-A (Informatics) in recognition of the value of the thesis