جست‌وجوی استاد و پژوهشگر

Mario Milazzoمشاهده پروفایل

پژوهشگر

• Multiscale Modeling
• Mechanics of Acoustics
• Biomaterials
• +۴ مورد دیگر

Dr. Mario Milazzo is a researcher at the BioRobotics Institute of Sant'Anna School for Advanced Studies , with a current appointment at Massachusetts Institute of Technology (USA). His work bridges robotics, biomaterials, and computational modeling through interdisciplinary projects. He earned a PhD in BioRobotics (2016) from Sant'Anna School for Advanced Studies after completing his Mechanical Engineering degree at the University of Pisa (2010). Research Areas: Multiscale modeling, industrial robotics, biomaterials, and bioinspired design using deep learning. Industry Collaborations: Ge Oil&Gas, Brembo, Magneti Marelli, Piaggio. His recent publications highlight trends in industrial robotics (autonomous platforms, path planning, electro-hydraulic systems) and biomedical applications (bone regeneration, protein nanostructures, tympanic scaffolds). Key methodologies include sonification, molecular modeling, and AI-driven material design. Scientific Awards : Marie Skłodowska-Curie Individual Fellowships (MSCA-IF-GF) with MIT, University of Antwerp, Tufts, and University of Pisa He has co-authored 25+ international journal papers , 9 patents , and 24 conference contributions , while serving as a reviewer for 20+ journals and guest editor for Polymers (MDPI). His leadership roles in industry projects and symposium organization demonstrate his translational research focus.

Ben Parslewمشاهده پروفایل

مدرس ارشد

• Biomechanics
• Engineering design and optimisation
• Flapping-wing flight
• +۶ مورد دیگر

Ben Parslew is a Senior Lecturer in Aerospace Engineering at the University of Manchester's Mechanical and Aerospace Engineering department within the Faculty of Science and Engineering. He has been with the university since completing his PhD, progressing from Research Associate to Honorary Lecturer (2013), Lecturer (2015), and Senior Lecturer (2018). In 2020, he also served as an Adjunct Professor at Chulalongkorn University. His educational background includes an undergraduate degree in Aerospace Engineering from UMIST (2003), a Master's in Fluid Dynamics from the University of Manchester (2005), and a PhD in animal flight biomechanics from the University of Manchester. Dr. Parslew's research lies at the interface of engineering and biology, with particular interests in animal locomotion, unmanned aerial vehicles, robotics and computer animation. His work spans biomechanics, engineering design and optimization, flapping-wing flight, biomimetics, and physics-based animation. He has developed tools for analyzing flapping-wing flight that are publicly available. His recent publications (2022-2025) demonstrate expertise in computational fluid dynamics, bio-inspired robotics, and aerospace engineering, with a focus on applications ranging from urban wind flow simulation to jumping robots and wingless rotorcraft. The research shows a clear trend toward practical applications of biomechanical principles in robotics and aerospace design. EPSRC Doctoral Prize Fellowship (2012) Faculty of Science and Engineering Better World Award Winner (2018) Highly commended at University of Manchester Making a Difference Awards (2018) Dr. Parslew has supervised multiple research students and projects, with a focus on bio-inspired robotics and aerospace applications. He has been involved in significant research grants including the Aerospace Engineering project (2010-2035) and the Space Systems Research Group. His work contributes to UN Sustainable Development Goals through the Aerospace Research Institute, Digital Futures, and the Manchester Environmental Research Institute. He is actively involved in the Centre for Robotics and Artificial Intelligence and has contributed to projects related to bio-inspired robotic hopper locomotion for navigation in extreme space environments.

• Mechanical Engineering
• Renewable Energy Systems
• Composite Materials
• +۳ مورد دیگر

Pak Sing Leung serves as Senior Lecturer at Northumbria University's Faculty of Engineering and Environment, where he has maintained continuous academic service since completing his PhD in 1990. His career spans over three decades of research in mechanical systems with particular focus on sustainable materials and energy applications. Leung's research spans multiple critical engineering domains including advanced composite development for automotive applications, renewable energy systems integration, and marine infrastructure protection. His work demonstrates consistent emphasis on sustainable resource utilization, particularly through waste-to-resource conversion methodologies and eco-friendly material design. Recent publications show increasing focus on renewable energy systems optimization while maintaining strong connections to traditional mechanical engineering challenges. His publication portfolio reveals strong methodological diversity combining experimental validation with computational modeling approaches. Key research trajectories include: sustainable composite development (2022-2024), vehicle aerodynamics optimization (2017-2018), and marine coating technologies (2014-2017). This interdisciplinary approach bridges traditional mechanical engineering with contemporary sustainability challenges.

Yakubu Tsadoمشاهده پروفایل

مدرس

• Cyber Security
• Smart Grid
• Internet of Things
• +۴ مورد دیگر

Dr. Yakubu Tsado is a Lecturer in Cyber Security and Smart Grid at the Department of Computing and Mathematics, Manchester Metropolitan University. He holds a Ph.D. in Electrical Engineering (Smart Grid) from Lancaster University, where he received the Centre for Global Eco-Innovation Ph.D. Scholarship. B.Eng. Mechanical Engineering - Federal University of Technology Minna, Nigeria M.Sc. Communication Engineering & Digital Signal Processing - Lancaster University, UK Ph.D. Electrical Engineering (Smart Grid) - Lancaster University, UK His research focuses on cybersecurity in critical infrastructures , with an emphasis on digital twins , cyber-physical systems , and AI/ML for energy systems . He explores smart grids and microgrids to enhance communication network reliability and real-time monitoring . His work spans industrial IoT security , energy consumption prediction , and peer-to-peer energy trading platforms . Dr. Tsado's publications highlight deep learning frameworks for intrusion detection, reinforcement learning in energy storage optimization, and OLSR routing protocols for resilient smart grid communication. His recent work integrates convex optimization and digital twin technologies to address security challenges in community energy trading systems. Centre for Global Eco-Innovation Ph.D. Scholarship (2017) Dr. Tsado has contributed to high-impact projects including the €3.7M Horizon 2020-SmarterEMC2 Project, the €30M Smart City (Triangulum) initiative, and the £600k NICE project. At Manchester Metropolitan University, he teaches units such as Computer Networks , Information and Network Security , Advanced Computer Networks , and Principles of Data Science , aligning with his expertise in smart grid cybersecurity and AI applications.

Emmanuel Cledatمشاهده پروفایل

دانشیار

• Photogrammetry
• Sensor Calibration
• Risk Measurement for Cyclists
• +۴ مورد دیگر

Emmanuel Cledat is an Associate Professor of photogrammetry at the National Institute of Geographic and Forest Information (IGN) and lecturer at the ENSG (National School of Geographic Sciences), where he teaches courses in sensor technology, mathematics for photogrammetry, and applied photogrammetry. As a member of the UMR Lastig research unit and ACTE research team, he conducts interdisciplinary work spanning photogrammetry, geomatics, and transportation safety. His research interests focus on photogrammetry , sensor calibration , and measurement of risks faced by cyclists . Dr. Cledat specializes in macro-photogrammetry of small objects, drone-based mapping systems, and GNSS-denied environment navigation. His methodological expertise includes camera calibration models, 3D reconstruction, and fusion of photogrammetric and LiDAR data. Dr. Cledat's publication record demonstrates consistent contributions to photogrammetry and geospatial sciences since 2016, with recent work exploring AI applications in geomatics and historical bridge modeling. His research shows a clear trajectory from foundational work on drone photogrammetry calibration to more applied projects addressing transportation safety and cultural heritage preservation. ISPRS Best Young Author Award 2020 As principal investigator, Dr. Cledat leads the CycloSafe project which quantifies cycling risks using LIDAR-equipped bicycles, and the EntrePonts project focused on 3D modeling of historical bridge models from the 17th-19th centuries. His teaching portfolio spans undergraduate and graduate courses in photogrammetry fundamentals, underwater photogrammetry, and climate change workshops. His laboratory work centers around the UMR Lastig research unit, with projects involving drone mapping systems, 3D TOF camera calibration, and photogrammetric fieldwork methodologies for both small objects and large-scale environmental mapping.

• Computer Science
• Applied Mathematics
• Machine Learning
• +۷ مورد دیگر

R.T. Wiersma is a researcher affiliated with the Faculty of Electrical Engineering, Mathematics and Computer Science at Delft University of Technology , specializing in Computer Graphics and Visualisation . Their work bridges computer science, applied mathematics, and computational geometry. Research interests include: Geometric deep learning 3D surface analysis Computer vision for cultural heritage High-performance computing algorithms Neural network adaptation for geometric data Recent publications demonstrate expertise in: Intrinsic learning on curved surfaces Geometric multigrid methods Art restoration through computational imaging Vanishing point detection in computer vision Active collaborations with researchers like E. Eisemann and K. Hildebrandt highlight their contributions to algorithm development and computational art analysis.

• Medical Imaging
• Ultrasound Tomography
• Image Registration
• +۴ مورد دیگر

Torsten Hopp is a Research Associate at the Institute for Data Processing and Electronics (IPE) at Karlsruhe Institute of Technology (KIT). His work focuses on advanced medical imaging technologies, particularly 3D ultrasound computer tomography (USCT) and its integration with MRI and X-ray modalities for breast cancer diagnosis. Research Interests: Ultrasound tomography system development Image registration algorithms Machine learning applications in medical imaging Biomechanical and computational modeling GPU-accelerated image reconstruction Multimodal imaging for clinical workflows Publication Trends: Torsten Hopp has contributed extensively to the evolution of 3D USCT, with recent work emphasizing deep learning integration , refraction correction , and patient-specific modeling . His research bridges hardware innovation (e.g., PtQube device) with computational methods for clinical translation. Labs & Teams: Affiliated with KIT's Institute for Data Processing and Electronics , he collaborates on projects like the High Data Rate Processing and Analysis Initiative , advancing ultrasound tomography for breast cancer screening.

• Computer Graphics
• Geometric Design
• Mesh Processing
• +۲ مورد دیگر

Loïc Barthe is a researcher at IRIT (Institut de Recherche en Informatique de Toulouse) affiliated with the University of Toulouse. His work focuses on geometric design, mesh processing, and subdivision surfaces in computer graphics. Email: lbarthe@irit.fr . Research interests include subdivision schemes for 3D modeling, optimization of geometric continuity around extraordinary vertices, and adaptive mesh processing algorithms. His papers on Loop and Catmull-Clark schemes demonstrate expertise in mesh refinement and curvature behavior control. Notable contributions include deriving closed-form equations for vertex position computation and developing optimization frameworks for subdivision rules. This work impacts applications requiring high-fidelity geometric representations in computer-aided design and animation.

Sun-Jeong Kimمشاهده پروفایل

استاد

• Computer Graphics
• Real-time Rendering
• Game Engines
• +۳ مورد دیگر

Sun-Jeong Kim is a Professor at the Department of Computer Science within the School of Computer Science at Korea University . Her research focuses on real-time rendering techniques, GPU programming, and game engine optimization. Specializes in procedural modeling and interactive visualization Develops efficient rendering algorithms for virtual reality Active in graphics hardware acceleration and collision detection Her research has produced 15+ publications on topics including tessellation strategies, skeletal animation systems, and particle effect optimizations. While specific awards and students aren't detailed in the current text, her work demonstrates consistent contributions to real-time graphics and game development.

Martin Marinovمشاهده پروفایل

پژوهشگر

• Computer Graphics
• Geometric Modeling
• 3D Mesh Processing
• +۳ مورد دیگر

Dr. Martin Marinov is a researcher affiliated with RWTH Aachen University, specializing in computer graphics, geometric modeling, and 3D mesh processing. His work focuses on multiresolution modeling, subdivision surfaces, and GPU-accelerated algorithms for real-time rendering. Research areas: Subdivision surfaces, quad-dominant remeshing, scattered data approximation, and GPU computing. His publications include innovative methods for mesh decimation, feature preservation, and anisotropic remeshing, with applications in computer graphics and geometric modeling. Marinov has contributed to optimizing parameter correction for subdivision surfaces and developing robust algorithms for complex 3D models.

Mathieu Chevriéمشاهده پروفایل

دانشیار

• Automatic Control
• Fractional Order Systems
• Electrothermal Modeling
• +۴ مورد دیگر

Mathieu Chevrié is an Associate Professor at Bordeaux Institute of Technology (Bordeaux INP), part of University of Bordeaux, working within the Automatic Control research group and specifically the CRONE team at IMS (Laboratoire de l'intégration, du matériau au système) laboratory. His academic career spans from doctoral research to postdoctoral work and now faculty position with significant industry collaboration. Dr. Chevrié received his Ph.D. in automatic control from Bordeaux University in July 2016, with thesis work focused on electrothermal modeling of automotive electrical components. His research specifically addressed controlling electrical currents to prevent overheating due to contact resistance degradation in connectors. From 2016 to 2019, he worked as a postdoctoral researcher at IMS laboratory while also serving as an engineer for OpenLab Electronics and Systems for Automotive, a joint laboratory between IMS and Stellantis. His research interests center on fractional order control systems with applications in automotive contexts. He has made significant contributions to H 2 -norm analysis of fractional transfer functions and their application to electrothermal modeling. His work bridges theoretical control theory with practical automotive applications including electric vehicle charging systems, intelligent lighting control, and autonomous vehicle decision algorithms. Recent research directions include predictive maintenance and tools for analyzing and controlling switching systems. Analysis of his publication record reveals a strong technical focus on fractional calculus applications in control theory, with consistent contributions spanning from foundational mathematical analysis to practical implementation in automotive systems. His work shows evolution from pure fractional order systems theory toward hybrid approaches combining AI with traditional model-based methods, particularly for fuel cell remaining useful life estimation. Dr. Chevrié has been actively involved in supervising Ph.D. students on topics including intelligent lighting control, decision algorithms for autonomous vehicles, identification of criteria determining acceptability of autonomous vehicle behavior, and hybrid approaches for residual lifetime estimation of fuel cells. His research has resulted in multiple patents related to electrical connector protection and analysis. He is a key member of the CRONE research team within the Automatic Control group at IMS laboratory, which focuses on fractional order system theory and applications. His work maintains strong connections with industry partners, particularly through the OpenLab collaboration with Stellantis, ensuring practical relevance of theoretical advancements in control systems.

Weiyang Liuمشاهده پروفایل

استادیار

• Machine Learning
• Inductive Bias
• Generative Modeling
• +۳ مورد دیگر

Weiyang Liu is a machine learning researcher and incoming Assistant Professor in the Department of Computer Science and Engineering at The Chinese University of Hong Kong (CUHK), where he will lead the Scalable Principles for Learning and Reasoning Lab (SphereLab). He has previously held postdoctoral and research roles at the Max Planck Institute for Intelligent Systems, Georgia Tech, Google Brain, Nvidia Research, and MERL. His research focuses on principled modeling of inductive bias in learning algorithms, emphasizing geometric invariance, symmetry, and formal reasoning in large language models. His work spans generative modeling (diffusion models, 3D mesh synthesis), foundation models (parameter-efficient training), and symbolic/mathematical reasoning evaluation. Publications include top-tier conferences like NeurIPS, ICML, CVPR, and ICLR, with Spotlight/Notable Top-25% designations. He mentors PhD students including Zeju Qiu, Longhui Yu, and Zhouliang Yu, with alumni transitioning to institutions like Technical University of Munich, University of Tübingen, and Caltech. His lab emphasizes curiosity-driven research , theoretical rigor, and open collaboration.

Thorsten Helbigمشاهده پروفایل

استاد

• Structural Engineering
• Building Materials Science
• Structural Design
• +۳ مورد دیگر

Thorsten Helbig serves as Professor of Structural Engineering, Building Materials Science and Constructive Design at Darmstadt University of Applied Sciences since 2022, teaching Structural Engineering, Building Materials in Context, and Principles of Structural Structures. Previously, he was Associate Professor at Cooper Union's Irwin S. Chanin School of Architecture (2018) and co-founded the international engineering firm knippershelbig in 2001, now operating from Stuttgart, Berlin, and New York. His educational background includes: Civil Engineering studies at University of Applied Sciences Bielefeld/Minden (1990-1994) Helbig's research pioneers sustainable structural solutions through lightweight construction , free-form geometries , and reinterpreted traditional materials like timber and rammed earth. His work fundamentally bridges engineering precision with architectural expression, emphasizing climate-responsive design and material efficiency. He champions the philosophy that structural systems should embody both technical excellence and poetic form, as reflected in his recommendation of Peter Rice's An Engineer Imagines . Analysis of his publications reveals three dominant trajectories: sustainable material innovation (rammed earth, timber composites), advanced structural systems for cultural landmarks (museums, opera houses), and computational design for complex geometries. His projects consistently demonstrate how engineering constraints can generate architectural opportunities, particularly in heritage-sensitive contexts. His major recognitions include: German Bridge Building Prize (2020) State Prize for Building Culture Baden-Württemberg (2020) German Steel Construction Award (2018) German Timber Construction Award (2017) Timber Construction Prize North Rhine-Westphalia (2006) As co-founder of knippershelbig, Helbig leads engineering for globally significant projects including the Academy Museum of Motion Pictures (Los Angeles), Trumpf Smart Factory (Chicago), Harvard SEAS engineering school, and Palaisquartier Frankfurt. His office exemplifies the integration of academic research with professional practice, tackling challenges from historic renovations to cutting-edge industrial facilities. He maintains active consultation hours at Darmstadt University while advancing sustainable construction methodologies through ongoing projects.

Eugen Borcociمشاهده پروفایل

استاد

• Software Defined Networking
• Network Function Virtualization
• 5G/6G Networks
• +۵ مورد دیگر

Eugen Borcoci serves as a Full Professor in the Department of Telecommunications at the National University of Science and Technology Politehnica Bucharest. With an extensive publication record spanning networking technologies, he has established himself as a significant contributor to the field of telecommunications research. His work bridges theoretical networking concepts with practical implementations, particularly in next-generation network architectures. Professor Borcoci's research interests focus on advanced networking paradigms including Software Defined Networking (SDN), Network Function Virtualization (NFV), and 5G/6G network architectures. He has pioneered work in network slicing technologies, particularly for vehicular communications and Internet of Vehicles applications. His research demonstrates a consistent emphasis on practical implementations and validation of theoretical networking concepts through experimental frameworks and open-source platforms. His recent publication trajectory (2021-2025) reveals a strong focus on Open Source MANO for network automation, SDN controller optimization across different network topologies, and specialized applications of network slicing for electric vehicle infrastructure and vehicular communications. This work demonstrates a clear progression from theoretical networking concepts to practical deployment scenarios with industry relevance. Professor Borcoci actively collaborates with international researchers, particularly with Marius Vochin, Frank Y. Li, and Andra Ciobanu, indicating strong international research connections. His work appears primarily in networking conferences and journals focused on telecommunications infrastructure and next-generation network architectures.

Milinda Fernandoمشاهده پروفایل

پژوهشگر

• Numerical Methods
• Parallel Algorithms
• Computational Science
• +۳ مورد دیگر

Milinda Fernando serves as a Researcher at the Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, within the Parallel Algorithms for Data Analysis and Simulation Group. His educational background includes: Ph.D. in Computing, The University of Utah, 2021 Bachelor's in Computer Science and Engineering, The University of Moratuwa Dr. Fernando specializes in developing numerical methods and computationally optimal parallel algorithms for scientific and engineering problems, with significant applications in computational relativity, plasma physics, and geophysics. He pioneered state-of-the-art distributed memory algorithms for spacetime adaptive mesh refinement (AMR) within the Dendro framework, enabling advanced simulations in relativity (Dendro-GR) and computational fluid dynamics. His current research focuses on accelerating Boltzmann transport algorithms for low-temperature plasma applications, addressing critical computational challenges in plasma physics. Scientific awards: None documented in source materials. Academic mentoring and grant activities: No information provided regarding advised students or funded research projects. He conducts his research within the Parallel Algorithms for Data Analysis and Simulation Group, which develops high-performance computing solutions for multiscale scientific simulations across diverse disciplines.