Nicolas AGUIRRE

Nicolas AGUIRRE is a Researcher at the University of Technology of Troyes (UTT), specializing in cardiovascular health and machine learning applications. His work focuses on analyzing blood pressure waveforms and morphologies using advanced techniques like deep learning and CycleGAN. He has contributed to studies on central arterial dynamics, coronary artery assessment, and arterial-ventricular coupling impairments.

Key research interests include biomedical engineering, signal processing, and health informatics. His recent work emphasizes developing in silico models and non-invasive diagnostic tools, with publications in journals like Sensors. He has also explored educational initiatives in machine learning through the clusterAI pipeline in Argentina.

Collaborations involve projects on artificial neural networks for cardiovascular age assessment and attention mechanisms for blood pressure analysis. Despite his prolific publication record, no scientific awards or student advisement are explicitly listed here.