Lucas Sedran

Technical skills: • Deep Learning: model optimization (optimizers, loss functions, fitting), CNNs, RNNs, and NLP. • ML Ops: packaging, Cloud deployment, pipeline automation, and model lifecycle management. Pedagogical skills: • Simplifying and effectively conveying complex concepts to students. • Quickly identifying and resolving errors in students' code. • Providing personalized guidance to help students achieve practical understanding of algorithms.

Title: Enhancing Propulsion in Prosthetic Systems for Transfemoral Amputees • Multidisciplinary Project: Collaboration between researchers (ENSAM / IBHGC), engineers (Proteor), and clinicians (IRR de Nancy, INI/CERAH, HIA Percy). • Main Objective: Investigating the metabolic and mechanical overconsumption in lower limb amputees, particularly transfemoral amputees, by analyzing joint power during walking. • Innovative Prototyping: Development of a new prosthetic foot involving 3D design (Fusion 360), finite element simulation (Abaqus), additive manufacturing, mechanical testing, and motion analysis. • Data Processing: Participation in clinical studies, design of experimental protocols, data collection and analysis (Matlab) from quantified motion analysis (Vicon) and metabolic consumption (K5 Cosmed), statistical analysis (Matlab, R). • Organizational Skills: Ability to conceptualize complex phenomena, formulate problems, set priorities, and conduct rigorous technological and methodological monitoring. • Results Communication: Presentation of work at national and international scientific conferences and publication in scientific journals. Publications : • L. Sedran, X. Bonnet, I. Loiret, N. Martinet, C. Billon, H. Pillet, J. Paysant (2024). Quantification of push-off and collision work during step-to-step transition in amputees walking at self-selected speed: Effect of amputation level. Journal of Biomechanics, 163, 111943. 10.1016/j.jbiomech.2024.111943. • H. Pillet, X. Bonnet, A. Boos, L. Sedran, B. Watier (2022). Seeking for a better Human-Prosthesis energetic gait efficiency by quantifying both propulsion power and instability control. 566-571. 10.1109/Humanoids53995.2022.10000069. Supervision : Hélène Pillet, Xavier Bonnet, Clément Duraffourg

Real-time identification of walking situations (flat ground, slope, stairs) using a kinematic model with inertial measurement units (IMUs) embedded in a prosthetic leg for above-knee amputees (transfemoral amputation). Experimentation; motion analysis (Vicon); signal processing (Matlab).

Responsible for the design of the gripping system for the EMY exoskeleton as part of the BCI project at the Clinatec biomedical research center of CEA. The BCI (Brain-Computer Interface) project aims to enable tetraplegic individuals to regain mobility through an exoskeleton controlled by brain signals.

• Worker on the assembly line of industrial filters for wine • Installation of sensors, test, assembly, screaws