AI/ML DEVELOPER & DATA SCIENTIST
Applied AI for real
industrial problems.
I build and deploy machine learning solutions across Computer Vision, predictive modeling, and Generative AI—combining an applied mathematics foundation with hands-on industrial development.
01 / SELECTED PROJECTS
Four featured case studies across industry,
machine learning, computer vision, and probability.
Prediction of machine processing times from structural and operational features, from model comparison and explainability through to deployment on a Linux server.
A YOLO-based workflow that turns technical drawings into machine-readable information by detecting production-relevant geometric features.
A comparative classification study focused on model choice, resampling strategies, and the precision–recall trade-off for next-day rain prediction.
Simulation of graph cover times showing how parallel random walks can dramatically change the scaling behavior of exploration.
Additional academic work across data analysis and statistical learning.
Exploratory analysis of Amazon India sales data, predictive analysis of rejected orders, and interactive visualization of insights.
Detection of anomalies in robotic movements using supervised and unsupervised methods, with evaluation of predictive performance and efficiency.
02 / EXPERIENCE
At Manni Sipre's Business Innovation Office, I work on AI solutions that connect models, software, and real industrial processes.
My path evolved from predictive analytics and dashboards to building, evaluating, and deploying AI systems for industrial use cases.
SEP 2025 — PRESENT
CURRENTManni Sipre S.p.A. · Manni Group
Building applied AI solutions across computer vision, generative AI, analytics, and software deployment, with a focus on tools that can support real production and business workflows.
YOLO and OpenCV pipelines for industrial technical drawings, including GPU training, evaluation, and optimization.
RAG prototypes and agentic workflows for documents, internal knowledge, and information retrieval.
Applications and microservices built with FastAPI, Docker, and REST APIs.
KPI dashboards and data-driven tools designed to support operational visibility and business processes.
OCT 2024 — AUG 2025
INTERNSHIPManni Sipre S.p.A.
Applied machine learning and analytics to industrial and commercial data, working on predictive models and interactive dashboards for operational use cases.
Production-time prediction, customer segmentation, and sales-volume forecasting.
Interactive dashboards for KPI monitoring and operational performance analysis.
03 / SKILLS
A practical stack for building, evaluating,
and deploying AI solutions end to end.
Predictive modeling, supervised and unsupervised learning, deep learning, model evaluation and explainability.
Object detection, classification and segmentation, with experience applying vision models to industrial technical drawings.
RAG systems, AI agents and document understanding, from prototyping to application-oriented workflows.
Data manipulation, exploration, visualization and reporting to support modeling and operational decision-making.
Turning experiments into usable services and applications, with attention to reproducibility, deployment and integration.
Java · MATLAB · Excel · VS Code
Italian — native · English — professional
04 / EDUCATION & CERTIFICATIONS
A background in applied mathematics and data science, complemented by focused training in AI agents and retrieval-augmented generation.
Focused on data analysis, predictive modeling, Machine Learning and Deep Learning, with practical work in Python and SQL.
Predicting industrial machinery processing times using Machine Learning, developed during an internship at Manni Sipre.
View thesis case studyBuilt a strong foundation in algebra, analysis, geometry, computational mathematics, probability and statistics, with applications to financial economics.
Simulation of the Credit Default Swap financial instrument using the Java programming language.