🎯 Seeking Roles: Research or industry roles where
I can leverage my multi-disciplinary toolkit, combining low-level
systems logic, machine learning workflows, and modern web architecture,
to solve real-world problems in engineering, finance, and adjacent
fields.
Systems-Focused Developer: Translated technical
specifications into code to build tools used in production for
performance-critical distributed systems, deploying backends and
databases on cloud infrastructure in Python, Rust and C++, paired with
modern React/Next.js frontends.
Open-Source Maintainer: Shipped and continue to
maintain fully-tested and documented open-source libraries, taking full
ownership of the codebase, addressing contributions and feedback.
Distributed Computing & Cloud: Built
high-performance data pipelines on distributed architectures like
LEONARDO (EuroHPC), integrating databases and cloud-native services on
GCP and AWS via Docker, Redis, and CI/CD to ensure their long-term
reliability.
Contribution: Delivered a market-ready MVP as sole
engineer, winning 1st of 90 teams at an international competition by
transitioning a prototype into a production-grade platform.
Developed a layered LLM pipeline to automate the writing of study
guides from recordings and slides, handling the full development cycle
from backend to frontend and deployment to GCP.
Scaled backend throughput and reliability by offloading tasks to
BullMQ/Redis and automating the release cycle via CI/CD, halving
deployment costs and time.
Graduate Research Fellow, University of Bologna,
Feb.–Sept. 2025, Bologna, Italy
Tools: Python, HPC (SLURM), TensorFlow
Contribution: Deployed high-throughput data
pipelines on the LEONARDO (EuroHPC) distributed architecture, enabling
efficient processing of GB-scale simulation datasets.
Managed distributed workloads to optimize compute efficiency under
limited resources, significantly reducing processing time and costs for
large-scale tasks.
Standardized environments using containerization and
version-controlled configurations, ensuring the portability of the
pipeline and its reproducibility across distributed compute nodes.
🎓 Education
Master’s in Material Physics and Nanoscience,
University of Bologna (2023–2025)
Bachelor’s in Physics, University of Bologna
(2019–2023)
Coursework: ML Force Fields, Computational
Materials Modeling (DFT, MD), Solid-State Physics, Electronic Transport,
Cleanroom Fabrication & Characterization.
🏅 Publications & Awards
“Unraveling the Pathways of Tribochemical Reactions
Involving the ZDDP Lubricant Additive by Machine-Learning-Informed
Molecular Dynamics”, AMS Acta (Nov. 2025)