Arian Aghilinejad

Arian Aghilinejad is a Postdoctoral Scholar Research Associate in Aerospace at the California Institute of Technology, affiliated with the Graduate Aerospace Laboratories (GALCIT) within the Division of Engineering and Applied Science. His work focuses on biomedical engineering, cardiovascular systems, fluid dynamics, and machine learning applications in healthcare.

Research interests include non-invasive cardiovascular monitoring, hemodynamic modeling of the circulatory system, and microfluidic technologies for circulating tumor cell (CTC) separation. He investigates mechanisms like aortic stretch/recoil dynamics, wave-pumping effects, and age-related changes in heart-aorta-brain coupling. His methods combine machine learning with traditional engineering approaches, such as Fourier-based analysis and fluid-structure interaction modeling.

Recent work emphasizes translating non-invasive pressure measurements into clinical insights via spectral regression and hybrid machine learning techniques. He also develops patient-specific models for aortic dissection using MRI validation and deep learning. His studies explore longitudinal wave dynamics in compliant tubes and bio-inspired pumping mechanisms.

Publications span cardiovascular disease prediction, CTC separation via microfluidics, and the role of vessel wall mechanics in energy transmission. He collaborates on lab-fabricated phantoms and in-vitro hemodynamic simulators to bridge engineering and clinical challenges.