Sokratis Anagnostopoulos

Sokratis Anagnostopoulos serves as a Doctoral Assistant at the Hemodynamics and Cardiovascular Technology Laboratory (LHTC) within the Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), while concurrently pursuing doctoral studies in the Mechanics program. His dual role bridges academic research and technical application in cardiovascular systems.

His research integrates cardiovascular engineering, computational hemodynamics, and machine learning to develop diagnostic models for arterial waveform analysis and pressure decay phenomena. Key focuses include physics-informed neural networks for fluid dynamics simulation, cardiac output estimation algorithms, and biomedical applications like tracheomalacia correction using hydrogels, demonstrating interdisciplinary innovation across medical and engineering domains.

Publication trends (2019-2025) reveal a strong trajectory in machine learning-driven cardiovascular modeling, with recent work emphasizing physics-informed neural networks for hemodynamic diagnostics and renewable energy optimization. Cross-cutting themes include in silico population modeling, diastolic pressure decay analysis, and multi-fidelity transfer learning for engineering systems.

No scientific awards were documented in available sources.

No student advisement or grant information was specified in the provided materials.

He operates within EPFL's Hemodynamics and Cardiovascular Technology Laboratory (LHTC), contributing to the Institute of Bioengineering's mission of advancing cardiovascular technology through computational and experimental approaches.