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Luca
La Fisca

Status: Project Liaison Officer for TRAIL / Postdoctoral Researcher

I defended my PhD thesis titled "Human-Centered xAI: Towards Overcoming Interpretation Biases in Biomedical Signal Analysis" on December 20th, 2023.

My research interests lie at the intersection of Explainable AI and Biomedical Signal Processing. I am particularly focused on enhancing the interpretation of biomedical signals such as Polysomnography (PSG) and Electroencephalography (EEG) to better understand and diagnose conditions like Sleep Apnea. My work aims to minimize biases in the interpretation of these signals, thereby improving the reliability and accuracy of medical diagnoses.

In my PhD research, I concentrated on the analysis of latent spaces to identify significant biomarkers for specific medical conditions or tasks. Additionally, I have a keen interest in the field of Neurofeedback, exploring how feedback mechanisms can be used to influence and improve neurological and physiological functions.

By leveraging Explainable AI techniques, my goal is to make complex AI models more transparent and interpretable, ensuring that healthcare professionals can trust and effectively use AI-driven insights in clinical settings.

ARIAC Work Package : WP1 -interactions between humans and AI: interactive/human-in-the-loop algorithms, user assistance/AI-in-the-loop, consensus mechanisms, imperfect multi-expert labels, explainable AI

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