جست‌وجوی استاد و پژوهشگر

• Neuroscience
• Cognitive Neuroscience
• Alzheimer's Disease Research
• +۳ مورد دیگر

María Mercedes Atienza Ruiz is a University Professor in the Department of Physiology, Anatomy and Cell Biology at Universidad Pablo de Olavide, where she leads the LNF Functional Neuroscience research group and contributes to doctoral programs on Alzheimer's disease detection and memory mechanisms. Education: PhD in Neuroscience from the University of Seville (1999), thesis: 'Effect of the state of cerebral activation on the duration of auditory sensory memory' supervised by Dr. Carlos María Gómez González. Her research focuses on Alzheimer's and Parkinson's disease mechanisms, biomarker discovery (amyloid-beta, tau, salivary lactoferrin), and metabolic interactions with neurodegeneration. She investigates memory processes through neuroimaging, proteomics, and analysis of blood/saliva extracellular vesicles, with particular emphasis on insulin resistance, APOE ɛ4 effects, and age-related brain changes. Her work bridges basic neuroscience with clinical applications for early disease detection. Analysis of her 15 most recent publications (2021-2025) shows consistent focus on biomarker validation across biofluids, genetic risk factor interactions, and metabolic drivers of cognitive decline. Key methodologies include structural/functional neuroimaging, proteomic profiling, and longitudinal cohort studies targeting pre-symptomatic disease stages. Scientific Awards: No scientific awards were mentioned in the provided text. Dr. Atienza Ruiz actively supervises doctoral candidates in Alzheimer's disease research through UPO's programs on early detection and memory mechanisms, though specific student names weren't provided. Her LNF Functional Neuroscience group likely secures funding for biomarker discovery projects, with recent publications indicating ongoing investigations into metabolic-neurodegeneration links and therapeutic targets like angiotensin blockers. Research Group: LNF Functional Neuroscience

Mohamed Atiaمشاهده پروفایل

پژوهشگر

• Modular Robotics
• Soft Robotics
• Path Planning Algorithms
• +۳ مورد دیگر

Mohamed Atia is a Researcher in the Department of Electrical and Electronic Engineering at the University of Nottingham. His academic role focuses on robotic systems, with a PhD awarded in 2023 for his work on reconfigurable soft robots. His research aligns with UN Sustainable Development Goals related to innovation and education. Education: Doctor of Philosophy (2017–2022): Reconfigurable Soft Robots by Building Blocks , University of Nottingham Research Interests: Atia specializes in modular robotics, soft robotics, and path planning algorithms. His work integrates advanced materials with control systems, particularly in exoskeleton development. Recent studies explore machine learning applications in material science and 3D-printed composites. Research Trends: His publications emphasize reconfigurable robot design (2022–2024), path optimization for mobile systems (2020–2018), and exoskeleton control systems (2019–2017). The 2024 paper on machine learning for composites marks an interdisciplinary expansion. Impact & Collaborations: Participated in the CRADLE center, focusing on robotic autonomy in demanding environments. His work has been cited over 30+ times and reached 40+ readers on Mendeley. Labs/Teams: Part of the CRADLE research group, collaborating with experts in robotics, materials science, and biomedical engineering.

Hongyang Dongمشاهده پروفایل

استادیار

• Machine Learning
• Reinforcement Learning
• Control Theories
• +۷ مورد دیگر

Dr. Hongyang Dong is an Assistant Professor at the School of Engineering, University of Warwick. He previously served as a Research Fellow in Machine Learning and Intelligent Control at Warwick (2019–2022) before transitioning to his current role. His expertise spans control theories, machine learning, and their applications in complex systems like offshore renewable energy and autonomous robotics. Research Interests: Machine Learning, Reinforcement Learning, Deep Learning, Control Theories (Adaptive Dynamic Programming, Optimal Control), and applications in offshore wind energy systems and autonomous robotics. He teaches courses such as ES1A6 (Systems Modelling), ES2G2 (Electromechanical Design), and ES3E8 (Precision Control). Grants & Awards: Manchester Prize Finalist (2024) UKRI Grant: Smart, Aware, Integrated Wind Farm Control (ICONIC, 2023–2027, Co-Investigator) EPSRC Supergen Offshore Renewable Energy Hub Grant: Fault-Tolerant Wind Turbine Control (2021, Principal Investigator) UK-China EPSRC-NSFC Centre Grant: Semi-Active Structural Control (2020, Principal Investigator) His publications focus on reinforcement learning applications in wind farm control, spacecraft dynamics, and fault-tolerant systems, with over 30 papers in IEEE Transactions and other top journals.

Alireza Rezaeiمشاهده پروفایل

استادیار

• Construction Management
• Structural Mechanics
• Project Management
• +۸ مورد دیگر

Alireza Rezaei is an Assistant Professor (Teaching Focused) in the Department of Civil and Environmental Engineering at the School of Engineering, University of Warwick. He joined the university in 2018 after serving as a Senior Teaching Fellow. His teaching spans Construction Management modules for Civil Engineering students and the Civil and Infrastructure Engineering Degree Apprenticeship (CEDA) program. He has also taught Project Management workshops globally, including in South Africa, Malaysia, Cyprus, and Iran. Rezaei holds a BSc from the University of Tabriz (1997), an MSc from Mazandaran University of Science and Technology (2000), a PhD in Construction Management from Eastern Mediterranean University (2011), and an MSc in Real Estate Management from Birmingham City University (2018). His research focuses on construction management subfields like time/cost management, sustainability, occupational safety, and BIM implementation. He has designed reinforced concrete structures and managed mass-housing projects. His academic contributions include over 30 peer-reviewed journal articles and conference papers addressing topics such as urban vulnerability assessment, BIM adoption in education, and construction waste management. His work frequently bridges theoretical frameworks with practical applications in developing countries. Office hours are Tuesdays 10am-12pm during term time.

Ya Huangمشاهده پروفایل

دانشیار

• Biomechanics
• Human Motion Dynamics
• Vibration Analysis
• +۶ مورد دیگر

Ya Huang is an Associate Professor in Human Motion Dynamics at the University of Portsmouth, affiliated with the School of Electrical and Mechanical Engineering within the Faculty of Technology. He specializes in human responses to motion, signal processing, and vibration analysis. Huang joined Portsmouth in 2009 after postdoctoral research at the University of Sheffield on structural dynamics and earned his PhD in human responses to whole-body vibration from the Institute of Sound and Vibration Research (ISVR), University of Southampton (2008). Education: PhD in Human Responses to Whole-Body Vibration, University of Southampton (2008) Postdoctoral Researcher, Blast and Impact Dynamics Group, University of Sheffield Research Interests: Dr. Huang focuses on applying analytical and computational methods to understand human biomechanical responses to whole-body vibration and mechanical shocks across land, air, and sea transport. Key areas include: - Development of signal reconstruction methodologies for vibration analysis - Maritime safety through real-time wave imaging and vessel seakeeping optimization - Musculoskeletal modelling for crew bracing strategies on fast lifeboats Grants & Projects: EPSRC-funded project (EP/X035778/1) for real-time semantic wave imaging in maritime safety Royal National Lifeboat Institution (RNLI)-funded studies on crew dynamics on lifeboats Development of stereo vision systems for ocean wave analysis Awards: Best Conference Paper Award at IEEE Conference on Intelligent Systems (2020) Labs & Teams: Part of the Centre of Excellence in Defence, Risk & Resilience. Collaborates on projects involving hydrodynamics, autonomous vessels, and human-centred marine transport design.

• Next-Generation Wireless Networks
• Wireless Ad Hoc and Sensor Networks
• Cognitive Radio Networks
• +۵ مورد دیگر

Prof. Dr. V. Çağrı GÜNGÖR is a Professor and Department Chair of Computer Engineering at Abdullah Gül University, Kayseri, Turkey. He holds a Ph.D. from Georgia Institute of Technology and has been actively involved in research and academia since 2001. His primary roles include leading the Computer Engineering department and contributing to editorial boards of prestigious journals. Education: B.S. and M.S. in Electrical and Electronics Engineering (Middle East Technical University, 2001/2003); Ph.D. in Electrical and Computer Engineering from Georgia Tech (2007). Research focuses on next-generation wireless networks, smart grid communications, cognitive radio networks, underwater acoustic networks, and AI-driven data mining. His work bridges theoretical advancements with practical applications in smart grids and vehicular networks, emphasizing reliability and efficiency. Notable awards include TUBITAK Young Scientist Award (2017), BAGEP (2017), and IEEE Best Paper Awards (2012, 2006). He leads multiple research projects funded by TÜBİTAK, EU Marie Curie, and industry partners like Alcatel-Lucent and Eaton Corporation. Grants and projects include developing low-power WSNs for structural health monitoring, underwater acoustic networks, and smart grid communication frameworks. He has co-authored over 100 peer-reviewed publications and edited books on industrial wireless networks. Teaching courses include Computer Networks, Wireless Sensor Networks, and Capstone Design Projects. His lab explores cutting-edge solutions in IoT, vehicular networks, and AI-driven network optimization.

Guangjian Zhangمشاهده پروفایل

دانشیار

• Psychometrics
• Factor Analysis
• Structural Equation Modeling
• +۳ مورد دیگر

Guangjian Zhang is an Associate Professor at the University of Notre Dame, affiliated with the Psychometrics and Dynamic Analysis (PDA) Lab. His primary research focuses on developing and improving quantitative methods in the behavioral and social sciences, particularly in factor analysis, structural equation modeling, time series analysis, and longitudinal data analysis. He holds a Ph.D. in Psychology from Ohio State University (2006) and an M.S. in Statistics from the same institution (2004), along with an M.Ed. in Psychology from Beijing University (1999) and a B. Med. from Tianjin Medical University (1994). Education: Ph.D. in Psychology, Ohio State University, 2006 M.S. in Statistics, Ohio State University, 2004 M.Ed. in Psychology, Beijing University, 1999 B. Med., Tianjin Medical University, 1994 His research interests emphasize enhancing measurement tools like questionnaires, with a focus on methodological advancements in psychometrics. His work spans dynamic factor analysis, multivariate time series, and computational efficiency in statistical methods. Notable contributions include the development of the EFAutilities package and bootstrap procedures for factor analysis validation. He teaches courses on statistics and advanced methodology in behavioral and social sciences. Dr. Zhang has published extensively on topics such as factor rotation, bootstrap standard errors, and longitudinal modeling. His research addresses challenges in psychological dynamics, clinical outcomes, and statistical methodologies, reflecting a commitment to bridging theoretical and applied quantitative psychology.

• Structural Engineering
• Seismic Design
• Finite Element Analysis
• +۳ مورد دیگر

Prof. Dr. Kutlu Darılmaz is a Professor in the Department of Civil Engineering at Istanbul Technical University, where he has held academic positions since 1996. He specializes in structural engineering with a focus on seismic design, finite element analysis, and composite materials. His research explores topics such as earthquake-resistant building design, torsion analysis in composite sections, and vibration behavior of advanced materials. Education: PhD in Structural Engineering (2003), Istanbul Technical University MSc in Structural Engineering (1997), Istanbul Technical University BEng in Civil Engineering (1995), Istanbul Technical University Research interests span structural dynamics, material behavior under cyclic loading, and computational methods in engineering. He has contributed extensively to understanding FRP-confined concrete members and the dynamic response of complex structures like helicoidal bars and FGM grid systems. His publications highlight trends in advanced materials for seismic resilience, finite element modeling techniques, and structural performance under extreme loads. While no awards were explicitly stated, his work reflects significant contributions to civil engineering practices. Grants and advising details are not detailed in the provided text, but his academic progression from Research Assistant to Professor underscores his institutional commitment.

Emmanuel Alejandro Flores Johnsonمشاهده پروفایل

عضو هیئت علمی

• Composite and hybrid materials
• Metals and alloy materials
• Numerical modelling
• +۹ مورد دیگر

Dr. Emmanuel Alejandro Flores Johnson is an Adjunct Senior Lecturer at the School of Mechanical and Manufacturing Engineering, Faculty of Engineering at the University of New South Wales (UNSW), and a Senior Structural Modeller at the Australian Nuclear Science and Technology Organisation (ANSTO). His research focuses on the performance of advanced structural materials under extreme conditions for applications in the nuclear industry and non-nuclear energy-generation systems using numerical modelling. Dr. Flores Johnson has extensive expertise in developing finite element simulations of non-linear material behaviour, including plasticity, damage and fracture mechanics, impact, and shock behaviour. His work spans various engineering materials and structures, including composites, metal alloys, polymers, concrete and bioinspired materials. He has been involved in international multi-disciplinary collaborations, industry-oriented projects, and defence projects requiring numerical modelling and experimental testing expertise. His research interests include: Composite and hybrid materials Metals and alloy materials Numerical modelling and mechanical characterisation Modelling and simulation Finite element analysis of non-linear material behaviour Plasticity, damage and fracture mechanics Dr. Flores Johnson's publication record demonstrates a strong focus on applying numerical methods to solve complex structural engineering problems, particularly in extreme environments. His recent work shows increasing emphasis on nuclear applications and non-nuclear energy systems, reflecting the growing importance of these sectors in materials research. Dr. Flores Johnson has received recognition for his contributions to structural modelling and materials science through various research collaborations and projects. His work bridges theoretical modelling with practical applications in critical industries. With over a decade of experience in both academic and research organization settings, Dr. Flores Johnson has developed a robust research program that combines advanced numerical techniques with experimental validation to address challenging problems in structural materials science.

Hao Liمشاهده پروفایل

پژوهشگر ارشد

• Topology Optimization
• Mechanical Engineering
• Thermal Systems
• +۲ مورد دیگر

Hao Li is a MSCA Postdoc Fellow and Visiting Scholar at LIP6 , affiliated with the University of Southern Denmark in the Department of Mechanical Engineering . His research focuses on advanced computational methods for topology optimization in thermal, fluid, and structural engineering systems. Education: Not explicitly stated in the provided text. Current Projects: Leading EU-funded research on heat exchanger design using multiscale models and machine learning. Dr. Li's work spans multiscale topology optimization, level-set methods, and fluid-structure interaction, with applications in microchannel cooling, compliant mechanisms, and biodegradable composites. His recent publications highlight advancements in 3D conjugate heat transfer, adaptive meshing, and eigenfrequency maximization. The trends in his research output (2017–2025) emphasize thermal-fluid systems , high-resolution structural optimization , and manufacturable composite designs . Notable subfields include triply periodic minimal surfaces for cooling channels, nonlinear buckling analysis, and phasor-based dehomogenization techniques. Teaching & Supervision: Currently supervising projects on topology optimization frameworks for heat sinks and high heat flux cooling. His past projects (2018–2023) include research on piezoelectric transducers and thermal-fluid system design. Labs & Collaborations: Collaborates with institutions in Japan and France, focusing on experimental validation and industrial applications. His network includes partnerships with researchers in structural mechanics, computational fluid dynamics, and additive manufacturing.

Luigi Palizzoloمشاهده پروفایل

دانشیار

• Structural Engineering
• Elastoplastic Analysis
• Seismic Design
• +۷ مورد دیگر

Luigi Palizzolo is an Associate Professor in the Faculty of Architecture at the University of Palermo , specializing in Structural Engineering . His academic career spans over three decades, with key roles in research, teaching, and international collaborations. Graduated in Civil Engineering (Building Section) in 1986 PhD in Structural Engineering (1994) His research focuses on advanced elastoplastic analysis , seismic protection devices , and optimal structural design . Current work emphasizes sustainable materials and computational modeling for structural systems. Recent publications highlight trends in masonry vault analysis , steel connection optimization , and geopolymer composites . His work bridges theoretical numerical methods with experimental validation. He has served on multiple scientific committees for international conferences and acts as a reviewer for leading journals. His administrative roles include Deputy Director of the Department of Structural and Geotechnical Engineering and active participation in PhD committees . Palizzolo supervises advanced research projects and contributes to local and national research initiatives , with a focus on seismic resilience and structural optimization .

• Automation Systems
• Control Engineering
• Cybersecurity
• +۵ مورد دیگر

Tomasz Makowski is a Lecturer at the Department of Infotronics and Cybersecurity within the Faculty of Electrical and Computer Engineering at Cracow University of Technology. His work focuses on automation systems, control engineering, and cybersecurity, with active collaborations in robotics and IoT projects. Current affiliation: Cracow University of Technology Academic rank: Lecturer Research interests include: Automation systems and PLC programming 3D printing and Fusion 360 modeling Robotics and sensor networks Human-machine interfaces (HMI) and RFID technology Recent publications highlight applications in: Electromagnetic launcher control 3D printing integrations Smart greenhouse automation Experimental PID algorithm testing Mobile delivery robotics

• Stochastic Processes
• Queueing Theory
• Large Deviations
• +۶ مورد دیگر

Bert Zwart is a Professor at Technische Universiteit Eindhoven and holds a Scientific Staff Member position at Centrum Wiskunde & Informatica (CWI), Amsterdam. He leads research groups in stochastic systems and optimization, with expertise in queueing theory, large deviations, and stochastic networks. His work bridges theoretical probability with applications in power systems, operations research, and telecommunications. Zwart has been awarded prestigious honors including the Dantzig Prize (2015), Erlang Prize (2008), and IBM Faculty Award (2008/2009). His research focuses on extreme-value analysis, heavy-tailed processes, and stochastic modeling of complex systems. Notable contributions include studies on fork-join queues, power flow dynamics, and random graph structures. Grants: Led or co-led multiple NWO-funded projects, including a €1.5M VICI grant (2015) for rare event research and a €420K TOP program grant for two-dimensional queueing models (2014–2018). Teaching: Recently taught courses such as Stochastic Decision Theory and Asymptotic Methods in Queueing Theory at TU Eindhoven. Labs/Teams: Active in CWI’s Stochastics group and collaborates with academic/industry partners like Shell and VU University. His recent articles analyze tail behaviors in fork-join systems, power grid optimization under stochastic loads, and dynamic random graph structures. Research emphasizes bridging theoretical insights with practical applications in high-reliability systems.

Girish Krishnanمشاهده پروفایل

استادیار

• MEMS Sensors
• Adaptive Structures
• Soft Robotics
• +۶ مورد دیگر

Girish Krishnan is an Assistant Professor in the Department of Mechanical Science & Engineering at the University of Illinois Urbana-Champaign, part of the Grainger College of Engineering. His research focuses on soft robotics, compliant mechanisms, and wearable assistive devices. He holds a BEng from R. V. College of Engineering, an MSc from the Indian Institute of Science, and a PhD from the University of Michigan. His work spans design, analysis, and application of fiber-reinforced actuators, pneumatic systems, and adaptive structures. Education: BEng in Mechanical Engineering, R. V. College of Engineering (2004) MSc in Engineering, Indian Institute of Science (2006) PhD in Mechanical Engineering, University of Michigan (2011) Research Interests: His studies include MEMS sensors, soft robotic actuators, and wearable exoskeletons. He explores architectures inspired by biological systems to enhance actuator performance and stiffness modulation. Recent work focuses on pneumatic muscle arrangements and self-contacting manipulators. Publications: Over 20+ peer-reviewed articles in journals like Smart Materials and Structures , ASME Journal of Mechanical Design , and conference proceedings of ICRA and IEEE Robotics. His research emphasizes practical applications in industrial and biomedical robotics. Awards: NSF CAREER Award (2015), Freudenstein Young Investigator Award (2017), and multiple teaching accolades including the 2016 Engineering Council Award for Excellence in Advising. His lab, the Monolithic Systems Lab, pioneers innovative designs in compliant mechanisms and soft systems. Grants & Advising: Led projects funded by NSF and industry, advising senior design teams on robotic systems. Contributions include developing curricula integrating project-based learning with departmental research.

Wei-Che Taiمشاهده پروفایل

دانشیار

• Dynamics and Vibration
• Smart Structures
• Energy Harvesting
• +۳ مورد دیگر

Wei-Che Tai is an Associate Professor of Mechanical Engineering at Michigan State University (MSU), affiliated with the College of Engineering. His research focuses on dynamics and vibration, smart structures, and energy harvesting, with applications in rotor dynamics, nonlinear systems, and energy harvesting for intelligent tires and vehicle suspensions. Tai holds a Ph.D. in Mechanical Engineering from the University of Washington (2014), an M.S. from the same institution (2012), and a B.S. from National Taiwan University (2007). Education Ph.D., Mechanical Engineering, University of Washington, 2014 M.S., Mechanical Engineering, University of Washington, 2012 B.S., Mechanical Engineering, National Taiwan University, 2007 Research Interests Tai’s work emphasizes nonlinear dynamics, vibration energy harvesting, and smart structural systems. He explores applications such as self-powered active vibration control for machinery, energy regenerative vehicle suspensions, and energy harvesters for intelligent tires. His research integrates mechanical design, mathematical modeling, and experimental validation to address challenges in energy conversion and structural dynamics. Publications His publications highlight advancements in vibration energy harvesting, nonlinear systems, and ocean wave energy conversion. Recent work includes studies on inerter-based vibration absorbers, stochastic resonance, and parametric resonance in rotating systems. These contributions span topics like broadband energy harvesting, wave energy platforms, and active suspension control. Labs and Teams Tai leads the Vibration and Dynamics Research Laboratory at MSU, focusing on experimental and computational studies of mechanical systems. His team collaborates on projects involving energy harvesting, nonlinear dynamics, and structural health monitoring.