Present Institution:

Neuroscience Research Center
Department of Medical and Surgical Sciences
Magna Graecia University of Catanzaro
Italy.

Location:

Caranzaro IT

Career Status:

Faculty Academia
Associate Professor

Bio

As an Associate Professor in Applied Medical Technology and Methodology at the Neuroscience Research Center
Department of Medical and Surgical Sciences
Magna Graecia University of Catanzaro
Italy
my research focuses on the development and application of Artificial Intelligence (AI) and Machine Learning methods for the study of the human brain
building on a background in Biomedical and Computer Science Engineering. My work is particularly centered on Explainable Artificial Intelligence (XAI)
with the aim of enhancing the transparency
reliability
and clinical applicability of AI models in neuroimaging. I am especially interested in developing interpretable and trustworthy frameworks that can support biomarker discovery and decision-making in neurological disorders. I actively promote interdisciplinary research at the intersection of AI and neuroscience. In this context
I have organized and chaired three editions of the Special Session “Explainable Artificial Intelligence for Unveiling the Brain: From the Black-Box to the Glass-Box” at the International Conference on Brain Informatics (2021–2025). In addition to my research activities
I contribute to the scientific community through editorial roles. I serve as Associate Editor for Frontiers in Artificial Intelligence – Neurology and Frontiers in Neuroimaging (Neuroimaging Meta-Analyses section)
and as Editorial Board Member of Brain Sciences (MDPI)
section “Computational Neuroscience and Neuroinformatics”.

Interested in presenting:

1.Scientific presentations in your area of expertise
Computational Neuroscience
Neurodegenerative disorders
Techniques in Neuroscience
2.Career development/professional advancement
Writing better proposals for funding
Attracting Public/Government and Private work
Leading project teams
Improving leadership skills
How to run a lab
How to get published
Scientific Communication
Global Networking

Sample of a Science/Scholarship Abstract

In my past presentations
I've covered a diverse array of topics related to my expertise in applied medical technology
methodology
and neuroscience. These talks have included research presentations where I shared findings from my studies
discussed methodologies employed
and explored implications for the field. Two of my recent presentations include: - Conversion from Mild Cognitive Impairment to Alzheimer’s disease: a comparison of tree-based Machine Learning algorithms for Survival Analysis at The 16th International Conference on Brain Informatics 2023 (BI2023)
held from 1st-3rd August 2023 in Hoboken
NJ
USA. - Overlap between variable importance rankings in tree-based classification of Parkinson’s disease and SWEDD at AI in Aging and Age-related Disease
specifically in Oral Session 4: AI in Aging and Aging-related Disease Evaluation
on 12th November 2022
during an online conference organized by Elsevier in association with Tongji University. Invited keynote lectures have provided me with opportunities to deliver comprehensive overviews of specific topics
highlighting key findings
trends
and future directions. For example
as an invited speaker
I presented an oral communication titled Unveiling the Brain and its disorders through Artificial Intelligence at TT.I - Technical Multi-Track with Parallel SYMPOSIA
Innovative approaches in UNMET clinical needs for maximum health care impact - Medical Needs
NanoInnovation 2021
held from 21st-24th September in Rome
Italy. Participating in panel discussions has allowed for interdisciplinary dialogue and debate on various topics within the field
such as the integration of AI in healthcare or ethical considerations in neuroimaging research. For instance
I served as a panelist for Panel III: Open
Explainable
and Ethical Approaches to Brain Research: Opportunities and Challenges at The 15th International Conference on Brain Informatics 2022 (BI2022)
held on 17th June in Padua
Italy. Overall
my past presentations have encompassed a wide range of topics tailored to different audiences and settings
reflecting my commitment to advancing knowledge and fostering dialogue within the field of applied medical technology and neuroscience.

What type of talks have you presented in the past?

Alzheimer’s disease (AD) exhibits sex-linked variations
with women having higher prevalence
and few is known about sexual dimorphism in progressing from Mild Cognitive Impairment (MCI) to AD. Main aim of our study was to shed light on sex-specific conversion-to-AD risk fac-tors using Random Survival Forests (RSF)
a Machine Learning survival approach
and SHapley Additive exPlanations (SHAP) on dementia biomarkers of stable (sMCI) and progressive (pMCI) patients. With this purpose
we build two separate models for male (M-RSF) and female (F-RSF) cohorts to assess whether global explanations differ between sexes. Similarly
SHAP local explanations were obtained to investigate changes across sexes in feature contributions to individual risk predictions. M-RSF achieved higher performance on test set (0.87) than F-RSF (0.79)
and global explanations of male and female models had limited similarity (<71.1%). Common influential variables across sexes included brain glucose metabolism and CSF biomarkers. Conversely
M-RSF had notable contribution from hippocampus
which had lower impact in F-RSF
while verbal memory and executive-function were key contributors only in F-RSF. Our findings con-firmed that females had higher risk to progress to dementia
and moreover
we highlighted dis-tinct sex-driven patterns of variable importance
uncovering different feature contribution risk across sexes to decrease/increase of conversion-to-AD.