Vahid Arbabi is an Assistant Professor in Orthopaedic Biomechanics at the Department of Orthopaedics, University Medical Center Utrecht (UMC Utrecht) / Utrecht University. He holds a PhD in Biomechanical Engineering from Delft University of Technology (TU Delft), where his doctoral work focused on multi-physics computational modelling of articular cartilage. His PhD research was recognised with the runner-up prize for the Best Doctoral Thesis Award in Biomechanics by the European Society of Biomechanics.

His research focuses on translational computational biomechanics, combining medical imaging, multi-physics modelling, and anatomy-aware computational pipelines to enable clinically relevant quantification, prediction, and patient-specific decision support in musculoskeletal disorders. A central theme across his work is the development of robust, interpretable, and scalable workflows that link imaging-derived anatomy and tissue characteristics to biomechanical descriptors and clinically meaningful outcomes.

He has been involved in several large collaborative programmes and international consortia. Within the IMI-APPROACH osteoarthritis programme, he contributed to imaging-driven quantification and modelling directions enabled by a richly phenotyped longitudinal cohort, supporting efforts in osteoarthritis stratification and prediction. In parallel, he has contributed to multidisciplinary clinical research in TOFA-PREDICT (psoriatic arthritis), where imaging and data-driven methods are integrated with clinical outcomes to study disease mechanisms and treatment response.

His current activities include EU-funded work in the Horizon Europe LUMINATE project (total budget €7.2 million), which aims to regenerate osteochondral tissue by developing a minimally invasive arthroscopic bioprinting approach to print and light-crosslink cell-laden photoresins directly inside osteochondral lesions of the knee, with the goal of restoring cartilage and bone architecture and preventing post-traumatic osteoarthritis. Within LUMINATE, he contributes through computational modelling (WP5), developing multi-physics frameworks that connect process physics, scaffold mechanics, and transport phenomena. This work supports parameter selection, mechanics and transport analyses, and predictive modelling of construct maturation and cartilage remodelling to guide design choices toward tissue-mimicking performance.

Overall, his research aims to advance in-silico and image-based orthopaedic engineering by bridging methodological rigour with practical clinical translation, supported by collaborative networks across academia, clinical partners, and industry.