My Vision
Driven by Innovation
I am a Data Scientist passionate about innovation and technology, with a strong academic background in Data Science and Statistics from Sapienza University of Rome. I possess advanced skills in machine learning, deep learning, and data management, and have worked on projects ranging from text analysis to image classification, predictive modeling, and data-driven decision systems. My expertise spans various industries, allowing me to adapt solutions to different challenges.
I have participated in various projects, both within companies and at the university, focusing on AI development, data management, and analysis to create tailored solutions that enhance decision-making and optimize data usage. Through these projects and collaborations, I have helped in leverage AI for smarter decision-making. I believe in the transformative power of technology to improve business efficiency and competitiveness.
My experiences
A Journey Through My Professional Growth
Explore the milestones that have shaped my path, from academic achievements to impactful work experiences.
Data Scientist
I'm working on developing generative AI solutions using LangChain, analyzing and managing data on Databricks using Python and SQL, and creating dashboards with Power BI.
External Consultant
I served as an external consultant with the main focus on increasing digitalization within the company.
External AI Consultant
I helped develop deep learning models to identify the right aligner for clients using mouth photos, employing custom architectures and fine-tuning HuggingFace models.
MSc in Data Science
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I worked on innovative projects using advanced deep learning and machine learning technologies, managing diverse data types like text, numbers, images, and 3D scans.
Training Camp
I enhanced my skills in the field of deep learning through theoretical and practical lessons. Applying this knowledge to the task of image classification.
Bachelor in Statistics
I gained a solid foundation in statistical disciplines, both theoretical and applied, along with extensive training in Computer Science, Mathematics, and Probability.
Real-World Impact
Highlighted Projects
Discover the solutions I've crafted to tackle real-world challenges.
Point cloud transformers for 3D fragment matching
- This project, part of a master's thesis in Data Science at Sapienza University, focuses on using deep learning models to assist in the reconstruction of fragmented artifacts. By leveraging Point Cloud Transformers (PCTs), the goal is to develop a neural network capable of predicting whether two 3D object fragments are adjacent. This technology offers practical support to archaeologists working to piece together historical artifacts, enhancing the reconstruction process with artificial intelligence.
Bitcoin Price Forecasting and Sentiment Analysis using Tweets
- The project aims to forecast Bitcoin prices by analyzing Twitter sentiment data. By using machine learning techniques and sentiment analysis, it identifies indicators that correlate with Bitcoin price movements. Various natural language processing models and forecasting methods are employed to improve prediction accuracy.
Deep Learning for Orthodontic Photos
- This project explores the application of machine learning and deep learning techniques to classify orthodontic images for treatment planning. Partnering with the aligner company Sorridi, the goal is to automate the pre-evaluation process, which is currently done manually by technicians. By analyzing dental photos, the system aims to classify treatment categories such as Soft, Semi-Medium, Medium, Semi-Hard, and Hard based on various dental conditions.
Leaf Disease Classification
- This project focuses on the automatic classification of corn leaf diseases using deep neural networks. The dataset includes over 4000 images categorized into four classes: Common Rust, Gray Leaf Spot, Blight, and Healthy. Through the use of Convolutional Neural Networks (CNNs) and advanced deep learning techniques, the model achieves a classification accuracy of 91.5%. This solution is highly effective for early disease detection in plants, with strong potential for agricultural applications.
Football Transfers Network Analisys
- This project delves into the intricate dynamics of the European football transfer market, analyzing player movements between top clubs across the seven major European leagues from 1992 to 2022. By modeling the transfer market as a complex network, where clubs are nodes and player transfers are weighted links, the project uncovers evolving trends in team interactions, transfer fees, and market structure.
About Me
A Glimpse Into My World
Learn more about who I am, what I do and what inspire me
3D Printing
Discover the endless possibilities of 3D printing! I am open to commissions.
My Toolbox
Uncover the Cutting-Edge Tools and Technologies Behind Data-Driven and AI-Powered Solutions
Beyond the Code
Explore my interests and hobbies beyond the digital realm
