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Mahmoud Sayed Mahmoud EidView profile

Research Fellow

• Data-driven fault diagnosis
• Electric power trains
• Electromagnetic modeling
• +1 more

Mahmoud Sayed Mahmoud Eid is a PhD Research Fellow in Engineering Sciences at the University of Agder. His research focuses on fault diagnosis in electric powertrains using AI-driven methods. He holds a B.S. in Mechatronics Engineering from Helwan University (2013) and an M.S. in Advanced Mechanical and Robotics Engineering from Ritsumeikan University, Japan (2019). Research Focus: Develops computational models for early fault detection in electric motors and inverters under noisy operational conditions. His methodologies integrate electromagnetic theory with machine learning for industrial applications in transportation and energy systems. Publications: His 6 most recent articles (2022-2025) focus on AI-enhanced diagnostics for power electronics and motor systems, demonstrating consistent innovation in signal processing and classifier design for industrial reliability.

Lutz EcksteinView profile

Professor

• Automotive Engineering
• Automated Driving Systems
• Vehicle Dynamics
• +4 more

Univ.-Prof. Dr.-Ing. Lutz Eckstein is the Head of the Institute of Automotive Engineering (ika) at RWTH Aachen University and a leading expert in automotive engineering. He concurrently serves as President of the VDI Association of German Engineers, President of the VDI Scientific Advisory Board for the Federal Ministry of Digital and Transport (BMDV), and Scientific Director of the NRW Competence Network for Automated and Connected Mobility. His professional background includes senior roles at BMW and DaimlerChrysler, focusing on vehicle safety, driver assistance systems, and ergonomics. Eckstein holds a Doctorate from the University of Stuttgart (2000) and received the Artur Fischer Prize (1995) for academic excellence. His research interests span automated driving systems, human-machine interfaces, scenario-based testing, and mobility infrastructure. He leads high-profile projects like UNICARagil and coordinates the Mobility and Transport profile at RWTH Aachen. Over 80 patents and publications reflect his contributions to automotive innovation, including advancements in sensor fusion, digital twins, and cooperative intelligent transport systems (C-ITS). His recent work emphasizes safety assurance for automated vehicles, scenario databases, and scalable simulation frameworks. Eckstein's interdisciplinary approach bridges academia and industry, driving transformative solutions for future mobility challenges.

Jay AikatView profile

Research Professor

• Computer Networking
• Data Science Education
• Cloud Computing Security
• +3 more

Jay Aikat is the Vice Dean of the School of Data Science and Society at the University of North Carolina at Chapel Hill since July 2022, and a Research Professor in the Department of Computer Science. She previously served as Chief Operating Officer at RENCI (2016–2022) and held leadership roles in IT at UNC-Chapel Hill’s School of Information and Library Science. Aikat holds a Ph.D. in Computer Science from UNC-Chapel Hill, with earlier degrees in Electrical and Electronics Engineering and Computer Science. Her research focuses on experimental methods in networking, Internet traffic modeling, cloud security, and data science education. Notable contributions include work on airborne network topology management, cloud computing security frameworks, and pedagogical innovations in big data training. She has collaborated with institutions like NIEHS (National Institute of Environmental Health Sciences) and contributed to national-scale research infrastructure projects through GENI and COMBINE initiatives. Her publication trends reflect deep engagement with network experimentation, cybersecurity challenges in cloud environments, and scalable solutions for dynamic wireless systems. Aikat has also authored foundational work on web traffic evolution and protocol benchmarking, emphasizing reproducible methodologies in networking research. Her professional trajectory includes bridging academic research with applied IT leadership, fostering interdisciplinary collaborations across computer science, environmental health, and data science domains. Current efforts focus on expanding data science education and driving innovation through the School of Data Science and Society.

Kakan DeyView profile

Associate Professor

• Intelligent Transportation Systems (ITS)
• Machine Learning Modeling
• Traffic Safety and Operations
• +3 more

Dr. Kakan Dey is an Associate Professor in the Department of Civil and Environmental Engineering at Michigan State University, College of Engineering. His research focuses on connected and automated mobility, intelligent transportation systems (ITS), machine learning modeling, and traffic safety. He has secured grants from NSF, USDOT, and multiple state DOTs. His work includes editing the textbook Data Analytics for Intelligent Transportation Systems and serving as an Associate Editor for IEEE and IET journals. Education: Ph.D., Civil Engineering (Transportation), Clemson University (2014) M.S., Civil Engineering (Transportation), Wayne State University (2010) B.S., Civil Engineering, Bangladesh University of Engineering & Technology (2005) Research Interests: Dr. Dey’s research emphasizes data-driven approaches to ITS, autonomous vehicle integration, traffic safety analytics, and resilience of transportation networks under climate change. He explores innovative solutions for pedestrian safety, wrong-way driving prevention, and sustainable mobility systems. Grants and Awards: CAREER: Transportation Network Maintenance under Climate Change (NSF, 2023–2028) NSF Early CAREER Award (2023) George N. Saridis Best Transactions Paper Award (2017) ASCE ExCEEd Fellowship (2017) Recent Projects: Current projects include analyzing pedestrian hybrid beacon operations (MN DOT), modeling infrastructure resilience (NSF), and evaluating turbo roundabouts (NV DOT). He collaborates on smart transportation technologies and policy frameworks for emerging mobility services.

• Solid Mechanics
• Composite Materials
• Anisotropic Materials
• +4 more

Professor Maria Kashtalyan holds a Personal Chair in Engineering at the University of Aberdeen, where she serves as Director of the Centre for Micro- and Nanomechanics (CEMINACS). She joined the University in 2002 as an EPSRC Advanced Research Fellow, progressing through roles such as Lecturer (2004), Senior Lecturer (2007), Reader (2011), and ultimately achieving her current rank in 2014. Prior to this, she held postdoctoral positions at Imperial College London and the University of Cambridge, supported by prestigious fellowships like the Royal Society/NATO Postdoctoral Research Fellowship (1998). Her research focuses on solid mechanics, composite materials, and their applications in aerospace, marine, and civil engineering. Key areas include anisotropic heterogeneous materials, functionally graded materials, and thermomechanical coupling in layered systems. She has authored over 190 publications, including highly cited papers in European Journal of Mechanics A/Solids and International Journal of Solids and Structures . Professor Kashtalyan leads the Applied Composite Materials journal as Editor-in-Chief since 2020. She has secured significant grants, including Royal Society International Joint Projects on composite modeling and plate theory. Her teaching spans undergraduate and postgraduate courses in nonlinear mechanics, composite materials, and engineering fundamentals. Affiliations: Member of EPSRC Peer Review College, Royal Society grant panels, and international conference committees. Labs/Teams: Leads CEMINACS and collaborates with global institutions like Imperial College London, Monash University, and the National Physical Laboratory.

• Renewable Energy Systems
• Fluid Dynamics
• Erosion Prediction in Turbomachinery
• +3 more

Paolo Venturini is an Associate Professor at Sapienza University of Rome , specializing in fluid dynamics, renewable energy systems, and erosion prediction in turbomachinery. His research focuses on integrating computational modeling with experimental validation to address challenges in energy efficiency, material durability, and sustainable engineering solutions. Key research interests include Hydrogen production via floating photovoltaic systems Cavitation-induced damage in tidal turbines Water washing efficiency in axial compressors Biomass gasification for energy recovery Rain erosion on wind turbine blades His work bridges mechanical engineering and environmental science, with applications in renewable energy integration, waste-to-energy systems, and aerospace thermal management. Recent studies emphasize interdisciplinary approaches, including mental health assessment tools for healthcare staff. Publications span 20+ years, with notable contributions to Energy , Applied Thermal Engineering , and Renewable Energy . Ongoing projects explore hybrid energy systems, plasma-based wastewater purification, and predictive modeling for turbine blade aging.

• Machine Systems Engineering
• Hydraulic Systems Innovation
• Fluid Power Systems
• +3 more

Lizhi Shang is an Assistant Professor in the Department of Agricultural & Biological Engineering at Purdue University. His research focuses on Machine Systems Engineering, with an emphasis on hydraulic system innovation, AI-aided design of fluid power components, and advanced computational tribological analysis. He is affiliated with the Maha Fluid Power Research Center, a leading facility for fluid power research. His work integrates experimental and numerical methods to address challenges in hydraulic systems, such as thermal management, cavitation phenomena, and tribological interface performance. He collaborates with interdisciplinary teams to develop compact and efficient fluid power solutions for off-road machinery and aviation systems. Key research themes include axial piston machine optimization, electrohydraulic integration, and sustainable hydraulic technologies. Dr. Shang’s publications span topics like tribology test chamber design, thermal modeling of piston-cylinder interfaces, and cavitation scalability analysis. His research aims to enhance energy efficiency and reliability in fluid power systems across diverse applications.

• Structural Biomechanics
• Musculoskeletal Modeling
• Finite Element Analysis
• +3 more

Andrew Phillips is a Professor in Structural Biomechanics at Imperial College London's Department of Civil and Environmental Engineering within the Faculty of Engineering. He leads the Structural Biomechanics Group and coordinates the MEng Civil Engineering degree program. His research focuses on musculoskeletal modeling, finite element analysis, and bioinspired structures. Phillips holds a PhD from the University of Edinburgh (2005) and an MEd from Imperial College (2014). Key affiliations include the Additive Manufacturing Network, Centre for Blast Injury Studies, and Musculoskeletal Medical Engineering Centre. His work integrates computational methods with biomechanical principles, addressing topics like bone adaptation, trauma injury effects, and wearable sensor technologies. Notable contributions include developing motoneuron-driven muscle models and synthetic motion capture datasets via generative adversarial networks (GANs). Phillips also organizes the Parametric Engineering Course with Arup and SimplyRhino. Recent publications emphasize bone health in amputees, neural drive estimation, and energy-absorbing metamaterials. His 2018 European Society of Biomechanics SM Perren Award recognizes outstanding contributions to hip dysplasia biomechanics. Research trends highlight interdisciplinary approaches merging machine learning with traditional biomechanics to solve clinical and engineering challenges.

Stefan Alexander SchneiderView profile

Professor

• Autonomous Driving
• Driver Assistance Systems
• Vehicle Simulation
• +3 more

Affiliations & Roles Prof. Dr. Stefan Alexander Schneider holds a professorship in Autonomous Driving and Driver Assistance Systems at the Faculty of Electrical Engineering of Kempten University of Applied Sciences. He also serves as Program Coordinator and Academic Advisor for the Master's program in Driver Assistance Systems. Additionally, he is a Visiting Professor at Shibaura Institute of Technology (Tokyo, Japan) . Education & Academic Background He completed his doctoral thesis "Adaptive Solution of Elliptic Partial Differential Equations by Hierarchical Tensor Product Finite Elements" in 2000, laying groundwork for his later research in computational methods. Research Focus His work centers on autonomous driving technologies , including: Simulation methodologies for vehicle systems Safety validation of driver assistance systems Human-machine interface design for elderly mobility solutions Standardization of testing frameworks (e.g., Open Simulation Interface) Key Contributions Recent projects include: ZuMoBe: Exploring autonomous electric vehicles in mountain valleys Development of Virtual Systems Prototyping frameworks for automotive innovation Cross-border collaboration via the VIVID German-Japanese initiative Teaching & Mentorship As a leader in one of the world's few Master's programs dedicated to ADAS/AV technologies, he mentors students in cutting-edge topics like monocular depth estimation, trajectory modeling, and interface design. His advisees have produced impactful works on autonomous scooter usability, localization algorithms, and motion planning validation.

• Transport and Logistics
• Spatial Data Analysis
• Road Safety
• +6 more

Adrian Ellison is a Research Fellow at the Institute of Transport and Logistics Studies (ITLS) at the University of Sydney. He specializes in large dataset analysis, particularly spatial data, applied to transport and logistics challenges such as road safety and active travel. He teaches GIS for Transport and Logistics and manages the Travel Choice Simulation Laboratory (TRACSLab). His research includes developing web-based travel surveys and smartphone app integration. Ellison holds a PhD from the University of Sydney and has received the Eric Pas Dissertation Prize (2014). He has contributed to studies on electric vehicle feasibility, cycling infrastructure impacts, and driver behavior profiling. Education: BCom (Ryerson University), MCom/MLogMan, PhD (University of Sydney). Research focuses on spatial data analytics, big data applications in logistics, and road safety. His work intersects transportation, technology, and public health, with publications addressing pedestrian safety in smart cities, trip stop identification from smartphone data, and customer service analytics via social media. Grants include a 2020 project on Trust and Safety in Autonomous Mobility Systems. His awards highlight contributions to travel behavior research. Teaching includes courses on GIS and big data for transport researchers.

Matthias SchefflerView profile

Professor

• Kinetic Monte Carlo simulation
• ab initio DFT
• electronic structure theory
• +5 more

Prof. Dr. Matthias Scheffler is the Director of the Theory Department at the Fritz-Haber-Institut der Max-Planck-Gesellschaft. His research focuses on predictive multiscale modeling in catalysis and energy conversion, integrating electronic structure theory, kinetic Monte Carlo simulations, and machine learning. He leads a diverse team (25+ nationalities) exploring processes in catalysts and energy devices. Research Interests: Computationally modeling materials properties, electrochemical interfaces, and energy conversion. Specializes in density-functional theory (DFT), ab initio methods, and data science for accelerating materials discovery. Current projects include understanding electron spillover effects in electrocatalysis and developing self-driving labs for catalysis research. Recent Highlights: Pioneered the Automatic Process Explorer (APE) for atomic dynamics analysis, revealed quantum mechanical electron spillover in water interfaces, and secured funding renewal for the e-conversion Cluster of Excellence. Collaborates with institutions like TU Berlin, FZ Jülich, and Brown University. Labs/Teams: Heads the Theory Department with subgroups like Light-Matter Interactions (Dr. Matthias Kick) and Machine Learning Interatomic Potentials (Dr. Hendrik Heenen). Hosts retreats and international collaborations, including EU-funded projects and Humboldt Professorships.

Andreas NüchterView profile

Professor

• Robotics
• Computer Vision
• Sensor Fusion
• +5 more

Andreas Nüchter is a Professor and Chair of Robotics at Julius-Maximilians-University Würzburg (Germany), leading the Chair of Computer Science XVII. He holds additional roles including Visiting Chair at ENSTA - Institut Polytechnique de Paris, Dean of Studies at the Institute of Computer Science, and Vice President of Zentrum für Telematik e.V. His research focuses on robotics, 3D reconstruction, SLAM, and sensor systems for autonomous systems. He has authored influential papers in IEEE Transactions on Robotics, Acta Astronautica, and robotics conferences like ICRA and IROS. Education: Not explicitly detailed in text, but inferred through academic roles. Research Interests: Robotics, computer vision, sensor fusion, autonomous systems, 3D reconstruction, and space robotics applications. His work emphasizes real-time systems, planetary exploration, and open-source software frameworks like SceneFactory and libBICOS. Recent projects include CNN-based spacecraft pose estimation, spherical mobile mapping systems, and radar SLAM (RIV-SLAM). Advising & Grants: Mentors a team including MSc/BSc students (e.g., Luca Anteunis, Fabian Arzberger). Involved in grants related to robotics, mining automation (AMADEE-24), and space exploration. Collaborates with institutions like NASA (CADRE lunar rovers) and Fraunhofer IPM. Labs/Teams: Leads the Robotics Lab at JMU, develops spherical robots for planetary missions, and maintains open-source libraries (libBICOS, SceneFactory). Active in projects like AMADEE-24 Mars simulation for human-robot interaction.

Chelsea ColeView profile

Assistant Professor

• Primary Care Sports Medicine
• Musculoskeletal Ultrasound
• Ultrasound-Guided Interventional Procedures
• +3 more

Chelsea Cole is an Assistant Professor in the Departments of Family and Community Medicine and Orthopedic Surgery at UT Southwestern Medical Center, serving as Director of Sports and Musculoskeletal Medicine. She holds clinical privileges at Parkland Health, Clements University Hospital, and Texas Health Presbyterian Dallas. Her roles include Team Physician for RL Turner High School and coverage for NCAA events, the Senior PGA Championship, and mass participation events. Education: M.D. from St. George’s University School of Medicine (with honors), Family Medicine Residency at UT Southwestern (Chief Resident), and Primary Care Sports Medicine Fellowship at LSU Health Sciences Center. Clinical Expertise: Focuses on diagnostic/therapeutic musculoskeletal ultrasound, procedural interventions (e.g., tendon injuries, nerve hydrodissection), fracture management, and concussion protocols. Her academic engagement includes leading musculoskeletal and POCUS curricula for UTSW’s Family Medicine Residency, simulation education as Curriculum Lead, and contributions to national committees in the American Medical Society for Sports Medicine (AMSSM). She has published peer-reviewed research, textbook chapters, and clinical reviews on musculoskeletal medicine, POCUS, and pre-participation evaluations. Education Advocacy: Designs high-fidelity simulation workshops for acute care and ultrasound-guided procedures, actively mentors medical students, and drives medical student outreach initiatives through AMSSM.

Jussi SopanenView profile

Professor

• Rotordynamics
• Electrical Machines Design
• Multibody Simulation
• +3 more

Professor Jussi Sopanen holds a DSc (Technology) from LUT University and has extensive experience in mechanical engineering and electric machine design. He currently leads the laboratory of Machine Dynamics and directs the LUT Integrated Energy Conversion Machinery (INERCOM) platform at the LUT School of Energy Systems. His research focuses on high-speed electric machines, rotordynamics, and digital twins, with over 125 publications in dynamic system design and simulation. He has supervised 12 doctoral and 57 master’s students, and his work has garnered 2,700+ citations with an h-index of 25. Education: DSc (Technology), LUT University (2004) Research interests include rotordynamics of high-speed drives, mechanical design of electrical machines, real-time multibody simulation, and digital twins. His work addresses challenges in rotor stability, bearing dynamics, and material selection for high-speed applications. Articles from 2023–2025 highlight advances in laminated rotor materials, fault diagnosis, and computational modeling. Professor Sopanen chairs the 12th IFToMM International Conference on Rotordynamics (2026) and serves on editorial boards, including Shock and Vibration . He leads a team exploring hybrid powertrains and energy-efficient machinery through collaborative platforms like INERCOM. His research bridges mechanical and electrical engineering, emphasizing practical applications in renewable energy and industrial systems.

Billiejoan RiceView profile

Senior Lecturer

• Nursing Education
• Interprofessional Education
• Cardiovascular Risk Assessment
• +3 more

Billiejoan Rice serves as a Senior Lecturer (Education) in Queen's University Belfast's School of Nursing and Midwifery, where she drives innovation in healthcare education through simulation-based learning and interprofessional collaboration. Her current work focuses on developing student competencies in high-stakes clinical scenarios including cardiovascular risk assessment and disaster response. Her academic credentials include an EdD, MSc, and BSc(Hons) in Nursing with Registered General Nurse qualification, forming the foundation for her evidence-based teaching approach. Dr Rice's research program centers on Nursing Education and Interprofessional Simulation , with significant contributions to Cardiovascular Risk Assessment pedagogy and Disaster Nursing preparedness. She designs immersive learning experiences that bridge theoretical knowledge and clinical practice, particularly through motivational strategies in undergraduate midwifery education and interprofessional workshops addressing complex healthcare challenges like dementia care. Analysis of her recent publications reveals a strategic focus on scalable educational interventions, including digital resources for cardiovascular health (ASMOSUS project) and cross-cultural disaster response frameworks validated during Hajj pilgrimages. Her distinguished contributions have earned multiple honors: Owen Wade Prize for teaching excellence (2004) QUB Teaching Award (2006) QUB Team Teaching Award (2024) Best Oral Presentation for interprofessional simulation research (2024) Shortlisting for Royal College of Nursing NI Nurse Researcher of the Year (2019) As Co-Investigator on the multi-center R2915NUR project ( Improving student nurses' skills in cardiovascular risk assessment ), she leads curriculum development for 'cardiovascular health champions' while mentoring through interprofessional conferences like QUB InterSim. Her supervised work includes developing the iPOV 'Walking in their Steps' simulation methodology. Her research ecosystem integrates Queen's Medical Biology Centre simulation labs with clinical partners across Northern Ireland, creating authentic environments where nursing and midwifery students practice behavioral change techniques and emergency response protocols under faculty guidance.