Bachelor in Computer Science and Engineering, UniFi
2018 — 2021
Final grade 105/110
Thesis on “Reconstructing Scarlatti - AI-Driven Sonata Composition Using Weighted Graphs and CNNs”
About Me
Hi, I’m Marco Mistretta! 👋
I’m an AI enthusiast 🤖 with a strong background in Computer Engineering and Artificial Intelligence, currently pursuing my PhD at MICC, University of Florence, Italy 🇮🇹, under the supervision of Prof. Andrew D. Bagdanov.
I’m passionate about understanding how machines perceive and interpret the world 🌍, especially through the lens of Multimodal Learning 📚. I’m constantly exploring new ways to push the boundaries in:
- 🧠 Natural Language Processing (NLP): Teaching machines to understand/generate human language 🗣️.
- 🔍 Contrastive Self-Supervised Learning: Uncovering hidden insights from data without labels 🔑.
- 🔄 Incremental Learning: Enabling models to learn continuously while retaining knowledge 🧑🎓.
- 🎯 Few-Shot Learning & Test-Time Adaptation: Building systems that adapt with minimal data and optimize performance on the fly 🚀.
Education 🎓
Master in Artificial Intelligence, UniFi
2021 — 2023
Final grade 110/110 cum laude
Thesis on “RE-Tune - Incremental Fine-Tuning of Biomedical Vsion-Language Models”
PhD student in Artificial Intelligence, UniFi
September 2023 — present
Vision language models, multimodal learning, incremental learning
Few-shot learning, zero-shot learning, prompt learning
Programming Skills 💻
Python
90%
Java
70%
C/C++
60%
R
60%
MATLAB
60%
HTML/CSS
60%
Technologies 🔧
Pytorch
85%
Sklearn
80%
Pandas
80%
Numpy
80%
git
90%
Linux
70%
Docker
70%
Experience 💼
Tutor (TA) @ UniFi - Florence, Italy
Jan. 2019 - Dec. 2019
Research Fellow @ UniFi - Florence, Italy
Sept. 2023 - present
- Research on Vision-Language models
- Incremental Learning
- Few-shot learning
- Prompt Learning
- Zero-shot learning
Tutor (TA) @ UniFi - Florence, Italy
Jan. 2024 - present
- Tutor experience working with 200+ bachelor students
- Designed 3 months of frontal and interactive lessons on C/C++, python
- Oriented students on their thesis, on their internship and on their future career