Marc Fernández is a PhD candidate in Quantum Computing at the N3Cat group at Universitat Politècnica de Catalunya (UPC). He earned his Bachelor's degree in Physics Engineering from UPC in 2023, where his
academic journey was marked by a growing interest in numerical methods and machine learning. This passion led him to specialize in computer science and artificial intelligence. He further pursued this interest during his Master's degree in Physics Engineering (UPC, 2024), in which he focused on computational physics and neural networks applied to complex quantum many-body problems. During his Master's thesis, Marc's work was supported by a grant from the Catalonia Quantum Academy, which further fueled his research ambitions. His current focus is on researching methods to enhance the scalability and efficiency of quantum systems.
Marc Fernández is a PhD candidate in Quantum Computing at the N3Cat group at Universitat Politècnica de Catalunya (UPC). He earned his Bachelor's degree in Physics Engineering from UPC in 2023, where his
academic journey was marked by a growing interest in numerical methods and machine learning. This passion led him to specialize in computer science and artificial intelligence. He further pursued this interest during his Master's degree in Physics Engineering (UPC, 2024), in which he focused on computational physics and neural networks applied to complex quantum many-body problems. During his Master's thesis, Marc's work was supported by a grant from the Catalonia Quantum Academy, which further fueled his research ambitions. His current focus is on researching methods to enhance the scalability and efficiency of quantum systems.
