جست‌وجوی استاد و پژوهشگر

Diane Haeringمشاهده پروفایل

دانشیار

• Sports Biomechanics
• Human Movement Analysis
• Postural Control
• +۷ مورد دیگر

Diane Haering serves as an Associate Professor (Maître de conférences) at University of Rennes 2 in the Department of Science and Techniques of Physical and Sporting Activities (STAPS), where she conducts research at the M2S Laboratory. Her academic journey includes a PhD from Université de Montréal (2012-2015), followed by postdoctoral positions at University of Rennes IRISA (2015-2017) and Arts et Métiers Institut de Biomecanique Humaine Georges Charpak in Paris (2018-present). Dr. Haering's research focuses on two primary areas: (1) postural control and movement analysis in individuals with chronic obstructive pulmonary disease (COPD), examining how respiratory conditions affect balance and mobility during daily activities; and (2) sports biomechanics, particularly gymnastics landing mechanics, lumbar spine loading, and injury prevention. Her methodological approach combines traditional biomechanical analysis with emerging technologies including inertial measurement units (IMUs) and machine learning algorithms. 40 publications with 167 citations and 18,155 reads according to ResearchGate metrics Active research in COPD-related movement disorders and gymnastics biomechanics Methodological expertise in motion capture, IMU technology, and biomechanical modeling Strong interdisciplinary collaborations between sports science and clinical rehabilitation As a Maître de conférences at University of Rennes 2, Dr. Haering supervises students and contributes to both undergraduate and graduate education in sports science and biomechanics. Her research program bridges theoretical biomechanics with practical applications in sports performance enhancement and clinical rehabilitation, particularly for respiratory disease patients. The ATTRACTION study protocol represents one of her current major research initiatives examining postural control in COPD patients during activities of daily living.

Fabrice Lamarcheمشاهده پروفایل

دانشیار

• Virtual Humans
• Crowd Simulation
• Motion Planning
• +۵ مورد دیگر

Fabrice Lamarche serves as an Associate Professor at Université de Rennes 1 within the ESIR School of Engineering, while maintaining dual affiliation with the MimeTIC research team at IRISA / INRIA Rennes. His academic career spans uninterrupted service since 2004, evolving from Assistant Professor roles at IFSIC (2003-2009) to current positions at ESIR. As co-founder of Golaem (2009), he bridges academic research with commercial application in crowd simulation technology. His institutional journey includes sequential membership in SIAMES (2004-2006), Bunraku (2007-2011), and MimeTIC (2011-present) research teams at INRIA. Lamarche earned his PhD in Computer Sciences from Université de Rennes 1 in 2003 with thesis work on virtual human autonomy. His educational foundation includes a Master of Computer Sciences specializing in Computer Graphics and AI (1999-2000), a Master of Engineering from INSA de Rennes (1997-2000), and a Technical degree from IUT de Limoges (1995-1997). His research program centers on virtual human behavior modeling with emphasis on decision-making systems, path planning under environmental constraints, and crowd simulation architectures. Key innovations include TopoPlan for human-scale navigation and frameworks integrating high-level task scheduling with low-level motion planning. This work addresses fundamental challenges in creating autonomous virtual characters capable of navigating complex 3D environments while exhibiting realistic behaviors, with applications spanning virtual reality, gaming, and simulation-based training systems. Publication analysis reveals consistent output from 2001-2014, evolving from foundational behavioral animation (2001-2004) to sophisticated crowd simulation systems (2013-2014). A notable trajectory shows increasing integration of cognitive modeling with motion planning, alongside exploration of Brain-Computer Interfaces for virtual navigation. Recent work demonstrates particular strength in semantic decomposition of urban environments and time-space constrained task scheduling. His scientific contributions have earned significant recognition: Rennes city medal (2009) for research excellence Second prize at Deutsch Telekom Awards (FMX 2008) for TopoPlan/MKM integration As an active researcher and educator, Lamarche advises students through Université de Rennes 1 while leveraging INRIA resources and Golaem industry partnerships. His publication record indicates sustained grant funding, particularly through INRIA channels, with collaborative projects extending to neuroscience applications via Brain-Computer Interface research. The MimeTIC team affiliation provides infrastructure for multimodal interaction research in complex virtual environments. Lamarche's laboratory work through MimeTIC focuses on developing practical implementations of virtual human autonomy systems. His research group maintains strong industry connections via Golaem, which commercializes crowd simulation technology. Current efforts emphasize semantic understanding of virtual urban spaces and robust path planning under dynamic constraints, building on foundational work in topological navigation and behavioral decision systems.

Nicolas Vignaisمشاهده پروفایل

استاد

• Biomechanics
• Physical Ergonomics
• Human Motion Analysis
• +۵ مورد دیگر

Nicolas Vignais is a Professor at the University of Rennes 2's Laboratory for Movement, Sport, and Health (M2S) and holds a concurrent position as an Associate Professor at the University of Paris-Saclay's Faculty of Sport Sciences (CIAMS Laboratory). His academic trajectory includes prior roles as an Assistant Professor at the University of Technology of Belfort-Montbéliard and a PostDoc at McMaster University. He earned his doctorate in Biomechanics from the University of Rennes 2. His research integrates biomechanics , physical ergonomics , and sports science , with emphases on: Human motion analysis using inertial sensors and VR Musculoskeletal modeling for exoskeleton control Ergonomic interventions in healthcare/industrial settings Sports performance quantification via instrumented wearables Recent publications demonstrate prolific output in human-robot interaction (15+ exoskeleton studies), biomechanical sensing (novel force/EMG methods), and applied ergonomics (hospital/industrial validation). Work consistently intersects engineering, physiology, and computational modeling. He leads the M2S Laboratory, focusing on movement innovation across sports, rehabilitation, and occupational domains. No awards or student supervision details are documented in available sources.

Sébastien Thomasseyمشاهده پروفایل

دانشیار

• Supply Chain Management
• Production Optimization
• Sales Forecasting
• +۴ مورد دیگر

Sébastien Thomassey is an Associate Professor at the National School of Arts and Textile Industries (ENSAIT), specializing in AI-driven solutions for textile engineering. His research focuses on optimizing fashion supply chains through machine learning applications in production management, sales forecasting, and sustainable manufacturing. He leads the Research Human Centered Design Group and coordinates multiple EU-funded projects including H2020's FBD-BModels and Erasmus+'s Digital Fashion initiative. His core research integrates: Supply chain optimization using AI forecasting models Textile manufacturing process automation Sustainable production lifecycle management Human-machine interaction in industrial settings Recent publications demonstrate strong emphasis on AI applications in textile anomaly detection (2024), digital twin technology (2023), and reinforcement learning for process optimization (2021). Awards include: Top 25 Most Cited Article in International Journal of Information Management (2021) He coordinates €5M+ in collaborative grants including: Fashion Trends 4.0 (Région Hauts-de-France) SMDTex Erasmus Mundus doctorate program H2020 FBD-BModels textile supply chain project Leads the Human Centered Design Group developing sensor-based textile tracking systems and industrial AI solutions.

Guillaume Mercereمشاهده پروفایل

استاد

• System Identification
• Model Learning
• Automatic Control
• +۶ مورد دیگر

Guillaume Mercere is a Full Professor in Automatic Control and Systems at ENSIP (Ecole Nationale Supérieure d'Ingénieurs de Poitiers), University of Poitiers. He maintains dual affiliations with Laboratory LIAS at both ENSIP in Poitiers and ISAE-ENSMA in Chasseneuil, conducting research in system identification and control theory. Professor Mercere teaches automatic control and signal processing at the Master's level, with additional expertise in numerical optimization, machine learning, and time series analysis. His teaching materials are available upon request, reflecting his commitment to educational transparency. Research Focus: Model learning, system identification, estimation theory, state space modeling, gray box modeling, linear parameter varying (LPV) systems, linear fractional representation (LFR), and subspace-based methods Application Areas: Electrical engineering, aeronautics, heat transfer, flexible/cable-driven manipulators, vehicle tire/road interactions, and image processing Analysis of his recent publications reveals a strong emphasis on recursive estimation methods (particularly total least squares), theoretical developments in LPV system representations, predictive control methodologies, and noise covariance estimation for Kalman filtering. His work bridges theoretical advances in identification methodologies with practical applications across multiple engineering domains, demonstrating both depth and breadth in his research program. Professor Mercere leads the Automatic Control Team at Laboratory LIAS, where he collaborates with researchers on theoretical and applied projects. His research group focuses on developing identification methodologies with practical implementation in real-world engineering systems, maintaining an active publication record through 2025 that demonstrates ongoing contributions to the field of system identification and control engineering.

Rochdi MERZOUKIمشاهده پروفایل

استاد

• Robotics
• System of Systems
• Control Theory
• +۴ مورد دیگر

Rochdi MERZOUKI is a Professor at the University of Lille, serving as Teacher Thematic Group Facilitator for ToPSyS (Tolerance Prognosis System of Systems), Team Leader of SoftE, and Member of the Scientific Council. He maintains offices at Polytech'Lille (F001) and ESPRIT (S3.29) on the Scientific City campus within the Polytechnic School of Lille and Department of Information Technology and Telecommunications. His research spans Robotics (focusing on flexible/continuum manipulators and robotic satellites), System of Systems modeling using hypergraph approaches, Control Theory for autonomous vehicles and deformable manipulators, and Artificial Intelligence applications in 3D printing automation. Key methodologies include parametric curve-based dynamic control, stochastic supervision frameworks, and predictive modeling for resilient system design in construction and medical applications. His work bridges theoretical advances with practical implementations in autonomous navigation, low-carbon cementitious printing, and adaptive radiotherapy. Professor MERZOUKI has supervised 15 doctoral theses covering diverse domains: Autonomous navigation of heterogeneous robotic satellites (Loic Bal) AI-based prediction for robotic 3D printing with low-carbon materials (Ame Saleh Ali) Hypergraph modeling of multi-level stochastic systems (Steeve Kamga Mbakop) Dynamic control of flexible continuum manipulators (Jun Jiang) Resilient system of systems design (Ahmad Koubeissi) Unified system of systems modeling (Gerardo Ayala Jaimes) Control of over-actuated omnidirectional vehicles (Yehya Sharif) Robotization of communicating wheelchairs (Othman Lakhal) Hyper-redundant robots for construction (Ismail Bensekrane) Energy planning for autonomous driving (Ali Raad) Predictive models for adaptive radiotherapy (Abdeslem Smahi) Large-scale system monitoring for biological/water systems (Inderjeet Singh) Curve-based shape reconstruction of continuum manipulators (Xinrui Yang) 3D printing automation in uncontrolled environments (Thor Enrique Morales Bieze) Kinematic modeling of deformable manipulators (Publications DIARY) He leads the SoftE research team and is affiliated with CRIStAL laboratory, focusing on integrated system design, predictive prognosis, and cross-domain applications from aerospace to medical robotics. His supervision record demonstrates sustained research leadership from 2015 through 2024 in emerging engineering domains.

• Automatic Control
• Electrical Engineering
• Motor Control Systems
• +۷ مورد دیگر

Laurent Rambault is an Associate Professor with HDR (Habilitation à Diriger des Recherches) in Automatic Control and Systems at the University of Poitiers, France. He is affiliated with the Laboratory of Sensor Application Engineering (LIAS) at both ENSIP (École Nationale Supérieure d'Ingénieurs de Poitiers) and ISAE-ENSMA. His research focuses on advanced control systems, fault detection, and signal processing applications in electrical machinery and industrial processes. Dr. Rambault's primary research interests include sensorless control and fault detection in electrical machines, particularly induction motors and permanent magnet synchronous machines. He has developed significant expertise in tacholess order tracking methods, digital twin development for predictive maintenance, and advanced signal processing techniques for condition monitoring. His work bridges theoretical control systems with practical industrial applications across wind energy systems, industrial vacuum processes, and fluid dynamics. His research methodology often combines traditional signal processing with emerging machine learning techniques to improve diagnostic capabilities. His recent publications (2020-2024) demonstrate a clear progression toward more sophisticated diagnostic methodologies, with increasing integration of Physics-Informed CNNs alongside traditional signal processing approaches. His work shows strong industrial relevance, particularly in predictive maintenance applications for manufacturing and renewable energy sectors. The consistent publication record across high-impact journals reflects his sustained contribution to the field of electrical machine diagnostics. Dr. Rambault maintains active research collaborations with colleagues including Sebastien Cauet, Erik Etien, and Anas Sakout, as evidenced by his extensive co-authorship patterns. His laboratory work at LIAS focuses on developing advanced control strategies and diagnostic tools with direct industrial applications. The research group maintains strong connections with industry partners to ensure practical implementation of theoretical advances in control systems.

Hocine IMINEمشاهده پروفایل

استاد پژوهشی

• Intelligent Transportation Systems
• Vehicle Modeling and Stability
• Nonlinear Observation
• +۴ مورد دیگر

Hocine IMINE is a Research Director at Gustave Eiffel University, where he has been working since 2021 after previously joining IFSTTAR (French institute of science and technology for transport, development and networks) in 2005. He holds a PhD in Robotics and Automation from Versailles University (2003) and received his HDR (Habilitation à Diriger des Recherches) from Valenciennes University in 2012. He serves as Cohead of NEXTRIM Associated International Laboratory, established in 2021 with the University of Bologna, Italy. His primary research interests span Intelligent Transportation Systems, vehicle modeling and stability, nonlinear observation and control, simulation technologies, and cycling safety. Dr. IMINE has developed expertise in both heavy vehicle dynamics and bicycle/cyclist safety, with recent work focusing on bicycle simulators, cycling infrastructure assessment, and multimodal transportation systems. His research bridges theoretical control systems with practical transportation safety applications. Analysis of his recent publications reveals a clear evolution from heavy vehicle dynamics toward more comprehensive transportation systems research, with significant emphasis on vulnerable road users like cyclists. His work demonstrates strong methodological consistency in applying advanced control theory and observation techniques to transportation problems, while expanding into human factors and infrastructure assessment. Dr. IMINE actively supervises research students and collaborates with international partners, particularly through the NEXTRIM laboratory. His research group at the Perceptions, Interactions, Behaviors and Simulations Lab for road and street users (PICS-L) develops advanced simulation technologies for transportation safety research. Current projects focus on bicycle simulators, cycling infrastructure assessment, and multimodal transportation systems integration.