Ayman Assi is a Professor at the Faculty of Medicine of Saint Joseph University of Beirut (Lebanon) and Director of the Laboratory of Biomechanics and Medical Imaging. His research focuses on postural and functional assessment in spinal deformities and cerebral palsy, with a particular emphasis on 3D patient-specific musculoskeletal modeling. He collaborates closely with the Institut de Biomécanique Humaine Georges Charpak (Arts et Métiers, Paris) and the Spine Department at Lenox Hill Hospital (New York). He served as President of the European Society for Movement Analysis in Adults and Children (ESMAC) from 2021 to 2025 and is an active member of the EUROSPINE Program Committee. He also acts as a consultant for biomedical companies. In parallel with his academic activities, he is actively engaged in human rights advocacy and received a Special Mention of the Human Rights Prize from the French Republic in 2022.

When alignment is not enough: integrating function in the assessment of spinal deformities

Degeneration of musculoskeletal tissues with ageing, particularly in the spine, leads to Adult Spinal Deformity (ASD), characterized by altered spino-pelvic alignment, postural imbalance, and compensatory mechanisms involving the pelvis, hips, and knees. At the other end of the lifespan, adolescent idiopathic scoliosis (AIS) represents a major spinal deformity affecting posture and function during growth, with potential long-term consequences into adulthood. Across both conditions, patients experience impaired function and reduced quality of life, while surgical realignment – especially in ASD – remains associated with high mechanical complication rates. Despite their central role in clinical decision-making, static radiographs fail to capture functional adaptations that critically influence outcomes. This keynote will highlight how integrating functional evaluation into the assessment of spinal deformities across the lifespan can provide new insights for treatment decision-making and improve patient-specific care.

Dr. Eline van der Kruk is an Associate Professor in the Department of Biomechanical Engineering at Delft University of Technology, where she leads the BODIES research group (Biomechanical Optimization of Daily life, Exercise, and Sports). Her research focuses on optimizing human movement across diverse populations, from elite athletes to frail older adults, with a strong emphasis on personalized musculoskeletal modeling. As motion analysis increasingly moves beyond laboratory settings into clinics, homes, and sports fields through wearable sensors and smartphone-based tracking, the need for accurate and scalable modeling approaches continues to grow.

In recent years, Dr. van der Kruk has highlighted BIASmechanics, demonstrating that many existing datasets and models are biased and insufficiently capture relationships across sex, age, and ethnic background, leading to inaccurate personalization. She currently leads European (Diversity Outside In) and national (Breaking BIASmechanics) funded projects that collect population-level in vivo data across demographic factors and model parameters. These projects develop novel scaling and modeling approaches to enable rapid and accessible generation of personalized models.

In addition to her research, Dr. van der Kruk is a member of the Young Royal Netherlands Academy of Arts and Sciences (KNAW), where she promotes diversity and engages in public science communication.

The Human Behind the Model

Musculoskeletal models are becoming increasingly accessible and widely used, especially as human motion capture moves beyond the lab into real-world settings. Yet, while clear differences exist in musculoskeletal injuries, pathologies, and performance across sex, age, and ethnicity, how well do our models truly reflect the diversity of the populations we study?

In this talk we will explore questions about representation in musculoskeletal modeling: Who currently serves as the data template for our models? Who are the participants we measure in experiments? Which subjects are captured—and which are overlooked? And, who is the human shaping the models we rely on?

Amir Patel is a robotics researcher with over 16 years of experience in both industry and academia. He is currently an Associate Professor in Robotics & AI the Department of Computer Science at University College London (UCL). Prior to this, he was in the Department of Electrical Engineering at the University of Cape Town (UCT), as well as the director of the African Robotics Unit (ARU). His research involves studying the manoeuvrability of robotic and biological systems such as the cheetah. He has held visiting positions at Carnegie Mellon University (2018) and Johns Hopkins University (2018) as well as University of Oxford (2023). Some of his accolades include a Google Research Scholar (one of the first two African recipients), two Oppenheimer Memorial Trust Fellowships, a MathWorks Research Award (the first ever African recipient) and the National Research Foundation (NRF) Emerging Researcher Award.

Crossing Borders in Biomechanics: Leveraging Robotics to Measure Movement in the Wild

Traditional motion analysis, whether for humans or animals, faces a common boundary: the walls of the laboratory. While optical motion capture provides gold-standard precision, it often restricts our understanding of movement to controlled, simplified environments. In this talk, I will explore how we can cross the disciplinary borders between robotics, ecology and biomechanics to overcome this challenge.

Focusing on the cheetah (the pinnacle of terrestrial agility) I will discuss my lab’s work in developing novel sensing systems and control-theoretic models to quantify rapid manoeuvring in the wild. By treating the animal through the lens of robotics, we employ techniques from embedded systems, sensor fusion and trajectory optimisation to capture whole-body dynamics during high-speed hunts.

I will demonstrate how these engineering approaches, necessitated by the extreme constraints of the African savanna, offer a new paradigm for human movement sciences. Specifically, I will highlight how these ‘wild’ motion analysis technologies can enable professionals to move beyond the gait lab, quantifying patient movement in the real world to provide deeper, more ecologically valid insights into human mobility.