I'm Italian, 24 years old, curious and energetic!
I am captivated by human ingenuity and the idea of empowering it with technology.
I am a Data Science student at EPFL in the beautiful Lausanne, Switzerland ⛰️
Currently, I am at ETH in Zurich, working with Zhijing Jin and Mrinmaya Sachan on the intersection of Causal Inference and AI agents.
Here you can find some of my thoughts on the future of AI agents.
On occasion, I help startups, either on technical aspects, or on strategic decisions.
I am looking for a full time position starting December 2024 or January 2025.
If you’re looking for someone that
- has technical expertise in AI but also cares about the business side,
- is able to prioritize and put things in a customer-centric perspective,
- loves the 0 to 1 of building a product, then I might be your guy.
I built Sentence Pair Finder, a system to find pairs of sentences which are similar in meaning but diverse in words in large corpora.
I worked on CausalQuest, a dataset of Natural Causal Quesitons (Paper under review)
🔭 I worked on building a vector search retrieval system and generative models for Gamma Ray Logs (Earth subsurface measurements) at Schlumberger-Doll Research, Cambridge, MA. (Patent pending approval)
Fine-tuning an AI Assistant for STEM Education
Development of an AI assistant specifically suited for STEM students. This included data gathering and preparation, training of a reward model (Deberta), fine-tuning of a large language model (Distilled GPT-2). Used the Antrophic-style Constitutional AI approach in order to bias the model towards providing clear, correct, complete, and rigourous answers.
Diffusion Models for Video Panoptic Segmentation
Re-implementation of the whole codebase of Pix2Seq-D, a diffusion-based model to approach segmentation tasks, in Pytorch from Tensorflow, and adapted of the architecture to the task of Video Panoptic Segmentation.
Development of a web app providing visualizations and search functionalities on train delays in Italy. The goal is to spread awareness about the quality of the service and prompt the company handling the railway system, to publish their data.
Causal Representation learning
Study with the goal of improving generalization capabilities of deep learning algorithms. Investigated the usage of Independence Regularization in Causal Representation Learning to increase the accuracy of a classifier on out-of-distribution data.
You can find more projects I've worked on and my full cv in my personal website.
If you want to connect with me, feel free to send me a DM on Linkedin!
Fun fact: I am a keen believer of Parkinson's Law