Marco De Luca

Marco De Luca's picture

Ph.D. candidate in Ingegneria Informatica E Dei Sistemi , 41st cycle (2025-2028)
Department of Control and Computer Engineering (DAUIN)

Profile

PhD

Research topic

Graph neural networks, Reinforcement learning, Agentic AI, Knowledge-informed machine learning

Tutors

Keywords

Data science, Computer vision and AI

Biography

I am a PhD student in Computer and Control Engineering at the Politecnico di Torino, where my research focuses on the application of machine learning to complex, domain-specific problems. My main interests lie in artificial intelligence, particularly in understanding how information propagates through neural networks and how tailored architectures can support a broad range of scientific and industrial applications.

I earned both my Bachelor’s and Master’s degrees in Computer Engineering at the Politecnico di Torino. During my academic journey, I progressively specialized in artificial intelligence, driven by a strong interest in the intersection of computer science and mathematics. My Master’s thesis, which focused on the application of AI in climate science, reinforced my commitment to pursuing a research-oriented career.

Throughout my studies, I actively sought experiences beyond traditional coursework to broaden my multidisciplinary perspective. I participated in the Intraprendenti program, completed an Erasmus exchange semester in Denmark, and joined the Alta Scuola Politecnica program, jointly organized by Politecnico di Torino and Politecnico di Milano. I also contributed to the academic community as a teaching associate for several university-level courses, including Programming and Scientific Computing, Programming Techniques, Cybersecurity and National Defence, and Linear Algebra and Geometry.

In parallel with my academic path, I gained industry experience through an internship at Reply, where I worked as a full-stack developer, and later continued part-time while completing my studies. This experience strengthened my ability to connect theory with real-world applications and enhanced my skills in teamwork, time management, and problem-solving.

During my PhD, I aim to apply machine learning to support discovery and innovation in fields such as environmental science, economics, bioinformatics. Motivated by curiosity and determination, I am committed to advancing research that bridges academia and industry.

Teaching

Teachings

Master of Science

Research

Research groups