جست‌وجوی استاد و پژوهشگر

Julien Tiernyمشاهده پروفایل

استاد

• Topological Data Analysis
• Scientific Visualization
• Data Compression
• +۲ مورد دیگر

Julien Tierny is a Professor at Ecole Polytechnique and a Senior Researcher (DR2) at CNRS within the Computer Science Department (LIP6) at Sorbonne Université, part of the APR team. His research focuses on Topological Data Analysis and Visualization, with a particular emphasis on developing efficient algorithms for scientific data processing and visualization. He leads the ERC-funded project TORI, which aims to reduce scientific data through in-situ topological methods. Education & Affiliations: PhD in Computer Science (2008), Université de Lille Habilitation Thesis (HDR, 2016), Sorbonne Université Principal Investigator of ERC Project TORI Research Interests: Topological Data Analysis, Scientific Visualization, High-Performance Computing, and Algorithm Design. His work bridges theoretical foundations with practical tools like the Topology ToolKit (TTK), widely used in visualization and data science. Awards & Recognition: ERC Starting Grant (2020) Best Paper Honorable Mention (IEEE VIS 2019) Best Paper Award (IEEE LDAV 2018) Teaching: Leads courses on Scientific Visualization, Topological Data Analysis, and Computer Graphics at Ecole Polytechnique and Sorbonne Université. Popular courses include 'Introduction to Topological Data Analysis' and 'Advanced Visualization Techniques'. Labs & Contributions: Co-developer of the Topology ToolKit (TTK), a widely adopted open-source library for topological data analysis. Active in IEEE Visualization conferences, publishing award-winning papers on distributed computing and topological simplification.

Sebastian Hügleمشاهده پروفایل

پژوهشگر

• Computational Design
• Robotic Fabrication
• Fiber Composite Manufacturing
• +۴ مورد دیگر

Sebastian Hügle is a Doctoral Researcher at the Institute of Aircraft Design (IFB) within the University of Stuttgart , focusing on integrative computational design and robotic construction . He contributes to the Cluster of Excellence IntCDC with expertise in process simulation , robotic path planning , and coreless filament winding technology . Research Interests: Computational design for fiber-polymer composites AI-driven data management in prefabrication Robotic automation for architectural systems Simulation of realistic fiber bundle architectures Teaching: Conducts seminars on Composite Design and Manufacturing Publication Trends: His recent work spans 2022–2024 , emphasizing robotic fabrication , data models , and AI integration in composite manufacturing. Key themes include offline programming , structural analysis , and adaptive construction systems.

• Digital Twin
• Aerospace Systems Prognostics
• Embedded Sensors
• +۶ مورد دیگر

Paul Major is a Full Professor in the Department of Mechanical and Aerospace Engineering at the Polytechnic University of Turin, where he has established himself as a leading researcher in aerospace systems. He serves as a member of the PhotoNext Interdepartmental Center for Applied Photonics and the University Internship Commission, demonstrating his commitment to interdisciplinary research and student development across multiple domains of engineering. Professor Major's research focuses on digital twin technology, prognostics and diagnostics of aerospace systems, and embedded sensor systems. His work bridges theoretical modeling with practical applications, particularly in the areas of augmented reality for aircraft monitoring, optical fiber sensors for structural health monitoring, and machine learning applications for predictive maintenance of electromechanical systems. His research has significant implications for improving aircraft safety, efficiency, and sustainability, with applications extending to lunar exploration technologies and space habitat design. His recent publications reveal a strong trend toward integrating advanced computational methods with physical systems, particularly in the domains of lunar exploration technology, additive manufacturing for aerospace applications, and sustainable aviation solutions. The interdisciplinary nature of his work spans aerospace engineering, computer science, materials science, and control systems, reflecting the increasingly interconnected nature of modern engineering research. His team has made significant contributions to optical sensor integration, AR visualization for maintenance, and prognostic frameworks for electromechanical systems. Professor Major actively mentors doctoral students, with current advisees including Matteo Bertone, Pierluigi Vergari, Armando Vittorio Atzori, and several others working on cutting-edge aerospace projects including lunar drones, aircraft anti-icing systems, and electromechanical actuator diagnostics. He has secured numerous research grants from both competitive funding bodies and commercial contracts, including projects like ASTRA (Advanced Space Tethers for Remote-sensing Applications), SmartCore, and FreME (Freno Multidisco Ad Attuazione Elettromeccanica Smart). He leads the ASTRA research group focused on Additive manufacturing for Systems and sTRuctures in Aerospace and is actively involved with the student team ICARUS. His work has practical applications in both terrestrial and space environments, with recent projects addressing lunar exploration technologies, sustainable aviation solutions, and advanced monitoring systems for aerospace applications.

Gokhan Serhatمشاهده پروفایل

استادیار

• Computational Mechanics
• Numerical Methods
• Design Optimization
• +۷ مورد دیگر

Gokhan Serhat is a tenure-track Assistant Professor at the Department of Mechanical Engineering , KU Leuven, stationed at the Bruges Campus. He conducts research within the Mecha(tro)nic Systems Dynamics Group and the M-Group and maintains a guest-scientist affiliation with the Max Planck Institute for Intelligent Systems. Education: Ph.D. in Mechanical Engineering, Koç University, 2018 (Marie Curie Fellow) M.Sc. in Computational Mechanics, Technical University of Munich, 2013 B.Sc. in Mechanical Engineering, Middle East Technical University, 2011 Research interests span computational mechanics, numerical methods, design & topology optimization, structural dynamics, composite materials, fiber-path optimisation, functionally graded structures, and bio-mechanical/haptic modelling. His work integrates high-fidelity simulation, laminate-parameter techniques, and additive-manufacturing constraints to create lightweight, variable-stiffness composite structures and tactile/biomechanical devices. Recent articles (2022-2025) reveal a strong trajectory in composite optimisation (anisotropic topology, lamination parameters, manufacturability) alongside interdisciplinary forays into biomechanics & haptics (fingertip dynamics, tactile displays, skin simulation). The portfolio is evenly split between computational-method development and application-oriented studies in aerospace, automotive, and human-interaction domains. Scientific recognition: Marie Curie Early-Stage Research Fellow (doctoral training grant) Research funding & leadership: Promoter, Flemish project “Fiber path and topology optimization of 3D printed composites” (2023-2027) Promoter, FWO/Flemish project “Concurrent fiber path and topology optimization of 3D printed composites” (2022-2024) He teaches three courses at KU Leuven Bruges: Structural Dynamics , Aerospace Structures & Lightweight Design and Mechatronic Design , and is an active member of the Faculty Council and the Department Council.

Raghav Gnanasambandamمشاهده پروفایل

استادیار

• Scientific Machine Learning
• Surrogate Modeling
• Uncertainty Quantification
• +۲ مورد دیگر

Raghav Gnanasambandam is an Assistant Professor in the Industrial & Manufacturing Engineering department at Florida A&M University-Florida State University College of Engineering. He holds a Ph.D. in Industrial and Systems Engineering from Virginia Tech (2024) and a dual bachelor's/master's degree in Mechanical Engineering from IIT Madras (2019). His research focuses on Scientific Machine Learning, Surrogate Modeling, Uncertainty Quantification, and Metal Additive Manufacturing. Educational Background: Ph.D., Industrial and Systems Engineering, Virginia Tech (2024) Dual Degree (B.S./M.S.), Mechanical Engineering, IIT Madras (2019) He develops physics-informed machine learning techniques for digital twins in manufacturing, with applications in laser scan path optimization, thermal modeling, and multi-physics simulations. His work combines deep learning with physical constraints to improve process efficiency and predictive accuracy. Scientific Awards: ISE Outstanding Doctoral Student, Virginia Tech, 2023 As principal investigator of the M2M Research Group, he leads projects supported by Amazon Web Services. His teaching includes courses in manufacturing systems and machine learning applications.

• Additive Manufacturing
• Precision Machining
• Smart Manufacturing
• +۳ مورد دیگر

Dr. Hossam Eldessouky serves as a Lecturer in Advanced Manufacturing within the School of Computing, Engineering and Technology at Robert Gordon University (RGU), UK. With over 18 years of combined academic and industrial experience, he directs research through the Composite Materials Manufacturing Research Group while maintaining active industry collaborations across Egypt, UAE, and international institutions including University of Birmingham and Al Imam Mohammad Ibn Saud Islamic University. His educational background includes: PhD in Mechanical Engineering (2018) from University of Bath MSc in Industrial and Management Engineering (2010) from Arab Academy for Science, Technology & Maritime Transport BSc in Industrial and Management Engineering (2006) from Arab Academy for Science, Technology & Maritime Transport Dr. Eldessouky's research focuses on advancing manufacturing technologies through five interconnected domains: Additive Manufacturing for medical/aerospace applications, Precision and Smart Machining systems, Reverse Engineering methodologies, Smart Materials integration, and Composite Materials fabrication. His work consistently bridges theoretical innovation with industrial implementation, particularly in developing sustainable manufacturing solutions and high-precision components. His publication record demonstrates consistent output in high-impact journals, with recent work emphasizing sustainability integration in engineering education (2025), lattice-structured medical implants (2022), and advanced machining optimization (2021-2022). The research shows strong interdisciplinary connections between materials science, biomedical engineering, and digital manufacturing. Professional recognitions include: Fellow of the Higher Education Academy (FHEA) Multiple Shield of Honour awards from AASTMT (2006-2019) Black Belt Lean Six Sigma and ISO 9001 Lead Auditor certifications Extensive consultancy portfolio including Kamal Saad Co. and Summer-moon Fish Industry Dr. Eldessouky actively supervises student research projects while developing industry-relevant curricula. His grant portfolio includes international collaborative projects focused on sustainable manufacturing and advanced materials. The Composite Materials Manufacturing Research Group provides students with access to state-of-the-art equipment and real-world problem-solving opportunities through ongoing industry partnerships.

Tales de Vargas Lisboaمشاهده پروفایل

پژوهشگر

• Composite Structures
• Numerical Modeling
• Lightweight Design
• +۳ مورد دیگر

Tales de Vargas Lisboa serves as a Researcher in the Tailored Lightweight Composites Department within the Polymer Materials Engineering Division at Leibniz Institute of Polymer Research Dresden. His work focuses on advanced computational methods for composite material design and analysis. His research spans Numerical and analytical modeling of composite structures Design optimization of Tailored Fiber Placement (TFP) components Nonlinear bending analysis of anisotropic plates Filament winding pattern generation with particular expertise in decomposition methods for solving complex structural mechanics problems. His publication record shows consistent contributions to mechanical engineering journals between 2017-2020, primarily addressing computational challenges in composite material behavior under various loading conditions. Key projects include International ZIM 'AniDo' and DAAD 'PROBRAL' collaborations. Led by Prof. Dr.-Ing. Axel Spickenheuer, the Tailored Lightweight Composites Department develops material-specific adaptations for continuous fiber-reinforced composites in extreme lightweight applications, with Lisboa contributing specialized computational expertise to the Advanced Composite Modeling research group. His technical capabilities bridge theoretical modeling and practical engineering applications, particularly in optimizing fiber paths and structural responses for high-performance composite components.