As an AI researcher at SMACT Competence Center, I develop and apply AI methods and solutions to optimize manufacturing processes in the agrifood industry. I collaborate with a multidisciplinary team of engineers, scientists, and domain experts to design, implement, and test novel algorithms and systems that enhance productivity, quality, and sustainability.I am also a PhD candidate in computer science at Università Ca' Foscari Venezia (and previously at The University of British Columbia), where I conduct research on explainable artificial intelligence (XAI), a field that aims to make AI models more explainable and accountable. My work at UBC focused on developing and evaluating XAI techniques for computational color constancy, a task that involves estimating the color of the ambient light from images or videos. I have published papers in prestigious journals and conferences in this area, and I received multiple scholarships and awards for my academic excellence and merit. My core competencies include machine learning, artificial neural networks, computer vision, and data analysis. I am passionate about advancing the state-of-the-art in AI and human-centred technology, and I aspire to contribute to the scientific and social impact of AI in various domains.