Curriculum vitae
Experience
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Research Fellow at ISPAMM Lab Sapienza. Researcher in the field of machine learning and deep learning, with a focus on Natural Language Processing and Graph Neural Networks.
[January 2022 - November 2022] -
Tutor for students. Served as tutor/mentor for 40+ university/high school students, helping them with projects and homework (Maths, Latin, Ancient Greek, Physics).
[September 2016 - Present] -
ICF trainee Coach. Studying and training to become a life & business coach. Experience with 30+ hours as individual coach.
[February 2020 - Present] -
Teaching Assistant. Teaching assistant for the course of Neural Networks for Data Science applications, taught in the Master’s course in Data Science at Sapienza, University of Rome.
[September 2023 - present]
Education
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Visiting
The University of Edinburgh.
Edinburgh, Scotland, UK.
Worked mainly on NLP with a focus on efficient inference (KV Cache compression) and explainability.
[March 2024 - July 2024] -
PhD in Data Science
La Sapienza, University of Rome.
Focus on Modular and Dynamic Neural Networks.
Supervisor: Simone Scardapane
[November 2022-Present] - Master’s Degree in Engineering in Computer Science
La Sapienza, University of Rome.
Final Mark: 110/ 110 cum Laude.
[September 2019 - January 2022]Thesis, in collaboration with ENEL: Hybrid Siamese Neural Networks for object re-identification
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Erasmus
Universidad Politecnica de Valencia.
Valencia, Spain.
[February 2021 - July 2021] -
Bachelor’s Degree in Control and Computer Engineering
La Sapienza University of Rome.
Final Mark: 110/ 110 cum Laude.
[September 2016 - October 2019]Thesis: A comparison of relational and non relational Databases: MongoDB and PostgreSQL
- High school specializing in humanities and ancient languages
Liceo Classico Tito Lucrezio Caro, Rome. Final Mark: 100/100 [2011 - 2016]
Languages
- Italian: Native
- English: C2
- Spanish: C1
- Portuguese: B2 & learning
Publications
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Steering Knowledge Selection Behaviours in LLMs via SAE-Based Representation Engineering, 2024
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Analysing the Residual Stream of Language Models Under Knowledge Conflicts , 2024
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Adaptive Layer Selection for Efficient Vision Transformer Fine-Tuning, 2024
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A Simple and Effective \(L_2\) Norm-Based Strategy for KV Cache Compression, 2024
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Are We Done With MMLU?, 2024
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Adaptive Computation Modules: Granular Conditional Computation For Efficient Inference, 2024
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Adaptive Semantic Token Selection for AI-native Goal-oriented Communications, 2024
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Conditional computation in neural networks: principles and research trends, 2024
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Enhancing High-Energy Particle Physics Collision Analysis through Graph Data Attribution Techniques, 2024
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Cascaded Scaling Classifier: class incremental learning with probability scaling, 2023
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Re-identification of Objects From Aerial Photos With Hybrid Siamese Neural Networks, 2023
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On the Robustness of Vision Transformers For In-flight Monocular Depth Estimation, 2023