Gabriele.
Coding the future, line by line.
I’m a passionate software engineer researcher and student. I like to use modern technologies to make cool projects.
Hi, my name is
About Me
I am a software engineer student with a passion for complex systems. I have a background in computer engineering and software engineering, and I have a strong interest in physics. I am currently studying at KTH in Stockholm, Sweden.
I am currently working on my thesis, focused on fine-tuning Large Language Models for synthesizing Solidity code in smart contract development.
Here are a few technologies I've been working with recently:- Python
- Apache Spark
- Large Language Models
- Scala
- Solidity
- FastAPI
- Quantum Convolutional Neural Networks
- Generative Adversarial Networks
Experience
Research Assistant in the Theoretical Computer Science department, ASSERT research group
- Collected, processed, and published the largest collection of smart contracts and Solidity code in the world
- Fine-tuned CodeLLAMA to generate invariants in Solidity code to enhance smart contract security, using PEFT and QLoRA
- Developed a program for automatic program repair of Solidity code using smartbugs and OpenAI API"
- Contributed to the development of Portals, a framework that unifies the distributed dataflow streaming model and actor model
- Ported Scala APIs to Javascript, to run Portals in edge computing environments.
Software Engineer - Quantum Cryptography
-
CERN - European Organization for Nuclear Research
Apr 2021 - May 2022
- Developed a Quantum Key Distribution simulator, to exchange symmetric keys, based on BB84 in Python.
- Developed the backend for the simulator with peer-to-peer and client-server architectures using Redis and Flask
- Forked gRPC and reimplemented its transport level using my simulator to provide post-quantum encryption
- Integrated my simulator into federated learning frameworks (OpenFL, Flower) and into a medical data homomorphic encryption system.
Student team doing dissemination and development in cryptocurrencies:
- speaker at the BIT PoliTO podcast
- implemented Schnorr signatures in Python
- organised several events at Politecnico di Torino
Education
Aug 2022 - Jun 2024 (ongoing)
Master of Science in Software Engineering of Distributed Systems
KTH - Royal Institute of Technology
I focused on Data Science within the program’s designated track.
Anticipated thesis focuses on fine-tuning Large Language Models for synthesizing Solidity code in smart contract development.
2018 - 2022
Bachelor of Science in Computer Engineering
Politecnico di Torino
GPA:
107 out of 110
Distinguished participant in the “Percorso Giovani Talenti” an excellence program recognizing the top 200 students across all courses.
High School
Licero scientifico statale Piero Gobetti
Projects
Solidity
Large Language Models
Smart Contracts
Dataset
DISL
The largest dataset of Solidity code for training large language models. DISL is a dataset of 3.3 million smart contracts, and 500.000 uinque Solidity files.
Quantum
Python
FastAPI
Cryptography
QKDSimkit
A modular Python Quantum Key Distribution simulator that emulates the BB84 protocol and provides p2p and Server-Client interfaces.
Python
Redis
Vision AI
Collaborative Filtering
FrAIdge
An app that recognizes food in your fridge using Vision AI APIs and suggests recipes based on your ingredients and collaborative filtering
OpenFL
Python
Flower
GANs
Federated Learning
FL_Gan
Generative adversarial networks for generating MNIST handwritten digits using different Federated Learning frameworks (OpenFL and Flower)
Javascript
Scala
Actor Model
ScalaJS
Portals
A framework that unifies the Distributed Dataflow Streaming Model and Actor Model. With a focus on edge stateful serverless processing.
Python
Github API
Apache Spark
Flask
github-graph
A project to explore the connections between GitHub repositories and visualize the results in an interactive graph.
Python
Variational Autoencoders
Speech Recognition
Speech Synthesis
Quantum Machine Learning
Quantum speech recognition and synthesis
A project that explores the use of quantum machine learning for speech recognition and synthesis, in particular Quantum CNNs, and compares it to classical approaches such as VAEs.
Get in Touch
My inbox is always open. Whether you have a question or just want to say hi, feel free to reach out!