Dr Luca Modenese has wide interests in the field of computational biomechanics, ranging from developing methods to generate computational models of the musculoskeletal anatomy to using advanced dynamic analyses to understand the principles underlying human motion and motor control. These research topics of computational nature are always strictly connected to clinical applications, thanks to the collaboration with clinical figures such as gait analysis laboratories and surgeons.
Education and background
Luca Modenese was awarded a degree (summa cum laude) in Mechanical Engineering from the University of Padua in 2008 (Department of Industrial Engineering). After a brief period as Research Assistant, Luca started his doctoral training at Imperial College London, based in the Structural Biomechanics group. Luca received his PhD in 2013 and moved to Griffith University for a postdoc in the Centre for Musculoskeletal Research (now part of Menzie Health Institute Queensland), under the supervision of Prof. David Lloyd. During this period, he was awarded a visiting scholar fellowship to visit the Neuromuscular Biomechanics Lab at Stanford University. He also spent time as visiting researcher at the Auckland Bioengineering Institute and University of Padua. In 2015, Dr Modenese moved to the Deparment of Mechanical Engineering of Sheffield University (INSIGNEO Institute for in silico Medicine). During this appointment, he was involved in the European Project MD-Paedigree and the EPSRC project MultiSim, developing methods to generate patient-specific musculoskeletal models.
In 2017 Luca was awarded a prestigious Imperial College Research Fellowship for a project aiming to optimize the outcome of surgical interventions using a combination of advanced computational methods including patient-specific neuro-musculoskeletal modelling, finite element analysis and predictive simulations.
et al., 2022, Mathematical relationships between spinal motoneuron properties, Elife, Vol:11, ISSN:2050-084X
Bicer M, Phillips ATM, Modenese L, 2022, Altering the strength of the muscles crossing the lower limb joints only affects knee joint reaction forces, Gait & Posture, Vol:95, ISSN:0966-6362, Pages:210-216
et al., 2022, Estimation of the firing behaviour of a complete motoneuron pool by combining electromyography signal decomposition and realistic motoneuron modelling
Bicer M, Phillips A, Modenese L, 2022, Generative deep learning applied to biomechanics: creating an infinite number of realistic walking data for modelling and data augmentation purposes, 9th World Congress of Biomechanics
et al., Prediction of the firing behaviour of the motoneuron population for motoneuron-driven muscle modelling, 9th World Congress of Biomechanics