Open to opportunities

Lucia Garozzo

@luciagarozzo

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Quantitative researcher applying mathematical modeling to data science and AI.

Sweden

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What I'm looking for

I’m looking to apply data science and AI to real-world challenges, combining rigorous quantitative research with practical engineering. I want to build reliable models, ship prototypes, and collaborate with teams to deliver impact.

I’m a quantitative researcher with a PhD in theoretical physics, and I focus on mathematical modelling and quantitative analysis. My work emphasizes efficient analytical and computational approaches for complex, high-energy physics interactions.

At Uppsala University, I developed and optimized symbolic and numerical computations to reduce runtime for large-scale scattering-amplitude calculations. I authored peer-reviewed publications and presented my findings to technical audiences, while also leading and evaluating coursework with structured feedback.

I’m equally interested in data science and AI applications to real-world challenges. Through ECHO ROOM at AI Sweden x Google, I built a conversational AI prototype with the Gemini API, persona-based prompt engineering, and a FAISS-backed retrieval-augmented generation pipeline, adding real-time audio via Google Text-to-Speech.

Experience

Work history, roles, and key accomplishments

Graduate Student Researcher

Uppsala University

Jan 2018 - Jan 2024 (6 years)

Conducted theoretical physics research on scattering amplitudes, developing analytical and computational approaches to model high-energy physics interactions. Optimized symbolic and numerical computations to reduce runtime of large-scale scattering-amplitude calculations and contributed to peer-reviewed publications and conference presentations.

Scattering Amplitude Calculations Field Theory Model Validation Symbolic Computation Computations Performance Optimization Peer Review Coursework Leadership

Echo Room Hackaton

AI Sweden × Google

May 2025 - Present (1 year 2 months)

Built a conversational AI prototype for multi-turn dialogue generation using the Gemini API and integrated real-time audio interaction. Implemented a retrieval-augmented generation pipeline with FAISS over uploaded documents to enable context-aware responses and secured 2nd place as a team.

Gemini API Multi Turn Dialogue Generation Retrieval Augmented Generation (RAG)Faiss Conversational AI

Education

Degrees, certifications, and relevant coursework

Uppsala University

PhD, Theoretical Physics

2018 - 2024

Activities and societies: Researched scattering amplitudes; optimized symbolic/numerical computations to reduce runtime; authored peer-reviewed publications; presented at international conferences; led and evaluated coursework and provided structured student feedback.

PhD studies in theoretical physics with research on scattering amplitudes. Developed and optimized analytical and computational approaches for high-energy physics interaction modeling and validated field-theory models.