Building production-ready AI applications, structured reasoning pipelines, and reliability-oriented infrastructure. Combining engineering execution with critical reasoning.

LOADING MODULES...
[OK] LLM INFRASTRUCTURE
[OK] RAG PIPELINES
[OK] FULL-STACK DEV
_READY_TO_DEPLOY

AI-Powered Mobile Application
Designed, developed, and deployed a production-ready AI-powered mobile application from scratch. Currently running in TestFlight beta (~40 users). Built full architecture including auth, database, and AI automations.

Reliability & Compliance Infrastructure
Production-ready LLM control plane acting as a gateway between applications and LLM providers. Implemented retries, circuit breakers, caching, rate limiting, and safety evaluation pipelines.

Decision-Support System (Beta)
AI system that explicitly models scientific reasoning. Implements structured pipelines: problem definition → evidence mapping → gap analysis → hypothesis generation. Focused on high-risk domains like pharmacology.

Local-Aware Coding Assistant
Developer tool integrating fine-tuned open-source LLM with real project file structures. Enables secure multi-file context reasoning for debugging and refactoring with a read-only by default filesystem access model.
Authored an independent research paper proposing a phase-gated reasoning framework for LLM-driven decision support.
READ PAPERTheoretical research project on siRNA-based inhibition of the MSTN gene, covering sequence optimization and delivery strategies.
READ PAPERJavaScript, TypeScript, Python, MATLAB
React, React Native, Expo, UI/UX implementation
Node.js, Express, Firebase, Firestore, PostgreSQL
LLMs, RAG systems, vector embeddings, prompt engineering
Sapienza Università di Roma · 2024 – Present
EQF Level 6
Harvard University
Self-paced, non-credit. Completed core curriculum (C, Python, SQL, algorithms).
Liceo Scientifico Antonio Labriola · 2020 – 2024
EQF Level 4