I'm Alberto G. Valerio
Ph.D. student in Digital Innovation and e-Health, a interdisciplinary and cutting-edge doctoral program focused on the design, development, and assessment of advanced AI-based technologies in the healthcare field.
About
I began my academic journey with a Bachelor's degree in Informatics and Technologies for Software Production, graduating with honors (110/110 cum laude). I then completed my Master's in Computer Science with a focus on Artificial Intelligence, also with distinction (110/110 cum laude and special mention). This strong academic background has not only strengthened my technical skills but has also fueled my interest in leveraging cutting-edge technologies, especially in computer vision and generative large language models.
In my doctoral research, I am exploring the potential of deep learning models to enhance medical diagnostics, treatment planning, and patient care within the realms of preventive and precision medicine, as well as neuroimaging. A key focus of my work is on explainability, which aims to make AI predictions more transparent and interpretable for healthcare professionals. Currently, I am developing models that integrate explainability with high-performance deep learning techniques, specifically for brain tumor segmentation and early detection of Alzheimer's disease, to ensure that the results are both accurate and actionable in clinical scenarios.
Before beginning my journey in research and academia and a new chapter of my life, I spent over 10 years working as a web software engineer. This professional background provided me with extensive industry experience in software development as well as practical problem-solving, which now enhances my approach to research and innovation.
Feel free to explore my website to learn more about my research, publications, and ongoing projects. I am always open to connect with researchers, clinicians, and anyone interested in the transformative power of AI and digital health.
Expertise
My research spans multiple interconnected domains and areas of interest, combining theoretical foundations with practical implementations. I leverage modern frameworks and libraries to develop innovative solutions, focusing on both established and emerging technologies. Through my work, I aim to bridge theoretical concepts with real-world applications, contributing to the advancement of the digital health while addressing contemporary challenges.
large language models
75%
Research
Below you will find a selection of my recent research contributions to peer-reviewed journals and conference proceedings. These publications reflect my ongoing work in advancing the field and collaborating with fellow researchers. Each entry includes links to the full text where available, along with any associated code repositories or supplementary materials.
2024 - Preprint
From Segmentation to Explanation: Generating Textual Reports from MRI with LLMs
G. Castellano, S. de Benedictis, K. Trufanova, A. G. Valerio, G. Vessio
Paper / Code / Demo /
BibTeX Citation
@article{castellano2024segmentation,
journal={Available at SSRN 4974224},
title={From Segmentation to Explanation: Generating Textual Reports from MRI with LLMs},
author={Castellano, Giovanna and de Benedictis, Salvatore and Trufanova, Katya and Valerio, Alberto G and Vessio, Gennaro},
doi={https://dx.doi.org/10.2139/ssrn.4974224}
}
2024 - Conference
RecSys CarbonAtor: Predicting Carbon Footprint of Recommendation System Models
G. Spillo, A. G. Valerio, F. Franchini, A. De Filippo, C. Musto, M. Milano, G. Semeraro
Code
News
Stay updated with my latest academic activities, including conference presentations, workshop participations, and research milestones. This section features recent achievements, upcoming events, and notable developments in my research journey. I regularly update this space to share significant moments and opportunities for collaboration.
There are no news at this moment, please come check later!
Download
As part of my doctoral program in Digital Innovation and e-Health, a major attention is dedicated to supervising student theses, guiding project work, and assisting in teaching. In this section, you will find a selection of useful resources, including seminar presentations, teaching materials, and other educational content. Feel free to explore this repository and use any of the available materials to support your own research or educational endeavors.
File information
A thesis template in English, mainly intended for master students, developed in LaTeX. The file contains useful tips, guidelines and formatting rules to follow for a well-crafted thesis work. The file can be processed by any online or local LaTeX compiler (e.g., Overleaf, MacTeX, TexLive).
Special thanks go to Dr. Gennaro Vessio for his tireless work and valuable contribution in making this file available.
File information
This document presents my research project on developing explainable AI models and proposes potential case studies for students in the Deep Learning course within the Master's Degree in Data Science, taught by Dr. Gennaro Vessio.
Download file
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