جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence
• Medical Informatics
• Data Mining
• +۳ مورد دیگر

José Manuel Ferreira Machado is a Full Professor at the Department of Informatics, School of Engineering, University of Minho, where he has been affiliated since 1988. His research integrates Artificial Intelligence, Medical Informatics, and Data Mining, with applications in healthcare, industrial systems, and public services. He founded ALGORITMI's 'Knowledge Engineering' group and served as Director of the ALGORITMI R&D Center (2018-2024). Education: Agregado in Informatics (AI), Universidade de Trás-os-Montes e Alto Douro (2011-2012) PhD in Informatics (AI), Universidade do Minho (1995-2002) Licenciatura in Systems and Informatics Engineering, Universidade do Minho (1982-1988) Research Interests: Machado's work focuses on intelligent systems for healthcare (e.g., AIDA medical platform), industrial automation, and smart cities. He emphasizes real-world applications, including clinical decision support, predictive maintenance, and sustainable urban infrastructure. Publications: His recent articles (2022-2025) demonstrate a strong focus on healthcare AI (e.g., disease prediction, COVID-19 analytics) and smart systems (e.g., traffic optimization, energy sustainability), utilizing data mining and machine learning. Awards: Hospital of the Future (2007, 2008, 2009) Good Practices in Health (2014) Portugal Digital Awards (2016) IHF Awards (2021) Advising & Grants: Supervised 16 PhD, 101 MSc, and 4 post-doc students. Leads sub-projects in PRR agendas GReenAuto and Be.Neutral. Secured funding from FCT, EU, and industry partners (e.g., Bosch) for 50+ projects. Labs & Teams: Coordinates the 'Knowledge Engineering' research group at ALGORITMI, focusing on intelligent decision support and interoperability in healthcare and industry.

• Computer Science
• Electrical Engineering
• Machine Learning
• +۷ مورد دیگر

Andrew Ho is an active academic researcher with publications spanning computer science, electrical engineering, and interdisciplinary applications. His recent work focuses on hybridizable discontinuous Galerkin methods for plasma simulations (2024) and AI/LLM applications in scholarly knowledge organization. 2025: Project Alexandria (LLM for copyright-free knowledge) 2024: Hybridizable DG plasma methods, GPU-accelerated kinetic simulations 2023: Low-resource translation techniques 2022: Multimodal VR interfaces 2003-2006: High-speed serial link transceivers and radiography artifact detection His research interests include: Computer science applications in plasma physics and medical imaging LLM-based scholarly knowledge graphs and literature reviews High-speed communication systems Educational technology implementations Co-authors include Vladimir Stojanovic (Stanford, 2003-2005), Carl W. Werner (2003-2005), and Genia Vogman (GPU plasma simulations, 2024).

Bradley Schmerlمشاهده پروفایل

پژوهشگر

• Software Engineering
• Software Architecture
• Self-Adaptive Systems
• +۵ مورد دیگر

Bradley Schmerl serves as a Principal Systems Scientist in the Software and Societal Systems Department (S3D) within Carnegie Mellon University's School of Computer Science. His research advances software engineering practices for modern challenges in distributed heterogeneous systems, self-adaptation, and cyber-physical integration. He leads the ABLE research group and actively mentors students in the Masters in Software Engineering program while teaching core courses like Software Architecture and Software Engineering Practicum. Dr. Schmerl's work addresses critical challenges in composing continuously evolving software systems, including components from untrusted third parties and on-the-fly recomposition for environmental changes. His research develops reusable, analyzable tools for software composition with emphasis on model-based adaptation, uncertainty management, and cross-language integration. Key projects include Rainbow for runtime architecture reflection, Acme for formal architectural foundations, and Cyber-physical Systems research linking software models with physical dynamics. Analysis of his 2023-2025 publications reveals intensifying focus on robotics software architecture (particularly ROS-based systems), explainable AI for architectural tradeoff analysis, and configuration management in adaptive systems. Trends show growing integration of machine learning for auto-tuning, empirical studies of misconfigurations, and dimensionality reduction techniques for visualizing design spaces—consistently bridging theoretical rigor with practical tool development for real-world applications. Scientific Awards: No specific awards were documented in the source materials. Dr. Schmerl serves as Practice Area Lead and mentor in CMU's Masters in Software Engineering program, guiding client projects including Rainbow UI for self-adaptive framework interfaces, CoBot UI for telepresence robots, and Educational Telepresence Tasking Language development. His research receives support through ABLE group projects funded by grants targeting software architecture foundations, adaptation mechanisms, and cyber-physical system validation. As a core member of the ABLE research group, he directs investigations into architecture-based self-adaptation with active projects spanning Rainbow (runtime architecture models for dynamic adaptation), Acme (formal architectural styles and tools), and Cyber-physical Systems (software-physical model integration). The group also maintains legacy work in End-User Architecting, Architecture Evolution, and service-oriented platforms for intelligence analysis through SORASCS.

• Embedded Systems
• Software Verification and Validation
• Model Checking
• +۵ مورد دیگر

Stefan Kowalewski serves as Professor of Embedded Software at RWTH Aachen University, leading the Chair of Embedded Software (Informatik 11) within the Department of Computer Science. His research spans critical domains including medical cyber-physical systems, automotive software, and industrial automation, with over 150 publications demonstrating sustained scholarly impact. Professor Kowalewski's work focuses on three interconnected research pillars: Embedded Systems Verification: Pioneering model checking techniques for PLC code, particularly addressing state space challenges in GRAFCET-based specifications Medical Cyber-Physical Systems: Developing safety-critical software for mechanical ventilation, extracorporeal membrane oxygenation, and ARDS diagnosis systems with strong clinical collaborations Automotive Software: Creating verification frameworks and safety architectures for automated vehicles through projects like UNICARagil Recent publications reveal an increasing integration of AI techniques with traditional verification methods, particularly for medical applications involving neonatal care and critical respiratory support. His 2024-2025 work shows particular emphasis on timing isolation in vehicle communication systems, middleware performance evaluation, and robust AI models for medical diagnosis. Professor Kowalewski maintains active collaborations with RWTH Aachen University Hospital's medical departments and automotive industry partners. His laboratory operates specialized facilities including the Cyber-Physical Mobility Lab for vehicle research and in-vivo testing setups for medical device validation. He has supervised numerous doctoral candidates, with recent students focusing on topics like ARDS classification algorithms, GRAFCET verification techniques, and safety architectures for software-defined vehicles. His educational contributions include developing remote teaching platforms for cyber-physical systems education.

Jelena Zdravkovicمشاهده پروفایل

استاد

• Requirements Engineering
• Enterprise Modeling
• Business Process Management
• +۶ مورد دیگر

Jelena Zdravkovic is a Professor and Head of the Department of Computer and Systems Sciences (DSV) at Stockholm University. She leads the PRECIS research group which focuses on Process, Requirements, Enterprise, Capability, and Information Systems modelling. Her work spans theoretical and practical aspects of enterprise and IT solutions with a particular emphasis on digital transformation. Professor Zdravkovic's research interests center around Digital Business Ecosystems , Digital Twins , and Data-driven Requirements Engineering . Her work in Enterprise Modeling explores capability-oriented and consumer-oriented approaches to requirements engineering. She investigates how digital transformation and big data can be leveraged to improve requirements elicitation processes, and how organizations can model and manage complex digital business ecosystems. Her research has significant implications for how businesses can adapt to rapidly changing technological environments while maintaining resilience and competitiveness. Her recent publications reveal a clear trajectory toward integrating artificial intelligence with digital modeling techniques, particularly in the context of smart buildings and business ecosystems. There's a consistent focus on how data-driven approaches can transform traditional requirements engineering practices, making them more responsive to the velocity and variety of digital data sources. Her work bridges theoretical modeling with practical applications across various industries including healthcare, energy, and transportation. Professor Zdravkovic has been actively involved in mentoring PhD students, including supervising research on the Management Framework of Resilient Digital Business Ecosystems. She has participated in numerous national and international projects focused on interoperability and model-driven engineering, securing research funding for innovative work at the intersection of business and technology. She leads the PRECIS research group which deals with theories, methods and tools for analysis and design of organizational and IT solutions in congruence. The group's research covers three key topics – Enterprise Modelling, Business Process Management, and Conceptual Modelling. Their work brings together academic rigor with practical applications to solve real-world business challenges through innovative information systems approaches.

• Human Factors
• Cybersecurity
• Cognitive Science
• +۶ مورد دیگر

Dr. Oliver Guidetti serves as a Level A Lecturer in Psychology at the University of Wollongong, specializing in human factors, cyber vigilance, and applied cognitive science. His interdisciplinary research bridges psychology, cybersecurity, and artificial intelligence to address critical challenges in human-machine collaboration and security operations environments. His educational foundation includes: Bachelor of Mathematics from Edith Cowan University (2011-2014) Bachelor of Science in Psychology from Edith Cowan University (2011-2014) Bachelor of Science (Psychology Honours) from Edith Cowan University (2015) Doctor of Philosophy from Edith Cowan University (2019-2022) Guidetti's research centers on the cognitive and physiological dimensions of human performance in security contexts. He investigates how eye-tracking, biometric monitoring, and neuroergonomic approaches can optimize vigilance in cybersecurity operations, while exploring socio-technical impacts of AI on human decision-making. His work extends to digital relationship literacy and AI bias mitigation, demonstrating applications across defense, healthcare, and industrial settings through collaborations with the Department of Home Affairs and Western Australian Cyber Defence Taskforce. His 2023-2024 publications reveal a cohesive research trajectory focused on cyber vigilance task design, human-AI teaming frameworks, and neuroergonomic validation methods. The corpus shows increasing integration of biometric data with cognitive theory to develop real-time performance assessment tools, alongside growing attention to ethical AI governance and cross-sector resilience in critical infrastructure protection. As an educator, Guidetti supervises Honours and PhD students in human factors and AI-driven research while teaching psychology research methods and cybersecurity applications. He co-developed an Australian Psychological Society-certified professional development course for psychologists entering cybersecurity fields, demonstrating his commitment to translating research into industry practice. His professional leadership includes advising on cyber vigilance frameworks, developing AI bias mitigation strategies, and serving on APS committees focused on digital psychology applications. Current projects involve designing AI-driven dating simulators for relationship literacy interventions and creating certified training programs for security operations personnel.

Moe Mojtahediمشاهده پروفایل

مدرس ارشد

• Construction Management
• Urban and Regional Planning
• Operations Research
• +۸ مورد دیگر

Dr Moe Mojtahedi is a Senior Lecturer at the School of Built Environment, University of New South Wales (UNSW). He earned his PhD in 2014 from the School of Civil Engineering at the University of Sydney. As a certified Project Management Professional (PMP) and Professional Engineer (PEng) accredited by Engineers Australia, Dr Mojtahedi bridges academic research with practical application in construction management and disaster risk reduction. PhD (University of Sydney, 2014) MEngSc (University of New South Wales) B.E. (Industrial), Professional Engineer (Australia) His research focuses on the intersection of construction management , urban resilience , and disaster risk reduction , particularly examining: Climate change adaptation in infrastructure Post-disaster recovery frameworks Lean construction methodologies Decision support systems for risk management Evacuation planning optimization Resilient hospital infrastructure Recent publications analyze trends in disaster science using computational modeling, prefabricated construction for industrial buildings, and AI/ML applications in aged care facility evacuation. His 2025 ChemistryOpen article explores sustainable reaction media for chemoselective processes, demonstrating interdisciplinary reach. Scientific recognition includes: Research Excellence Awards (Engineers Australia, 2012 & 2013) Best Conference Paper (ICES, Salford, 2017) Elsevier Outstanding Contribution Award (International Journal of Project Management, 2017) Learning and Teaching Excellence (UNSW, 2017) As a supervisor, he guides 7 PhD candidates and has mentored 4 graduates, including Mahmoud Ershadi (project management office effectiveness) and Kamyar Kabirifar (construction waste management). He contributes to policy discussions on aligning National Construction Code with UN Sendai Framework and advocates for disaster science integration in built environment practices. His media contributions examine hospital flood risks and climate change adaptation in Australia.

Thuy T. Leمشاهده پروفایل

استاد

• Digital System Design
• Computer Architecture
• Hardware Accelerators
• +۶ مورد دیگر

Thuy T. Le is a Professor of Electrical Engineering at San Jose State University's College of Engineering. With a distinguished career spanning several decades, he teaches graduate and undergraduate courses in digital system design, computer architecture, microprocessor systems, and related fields. His academic journey began with earning B.S., M.S., and Ph.D. degrees from the University of California, Berkeley. Professor Le's research interests encompass a broad spectrum of cutting-edge technological domains. His primary focus areas include System-on-Chip (SoC) and Embedded System Design, Hardware Accelerators for complex algorithms, Quantum Computing, implementation of Probability theory and Monte Carlo simulation, and radiation effects on electronic devices and systems. His work bridges traditional electrical engineering with emerging computational paradigms, demonstrating a consistent ability to adapt to evolving technological landscapes while maintaining strong foundations in core engineering principles. Analysis of Professor Le's publication record reveals a consistent trajectory from nuclear reactor physics and computational methods toward modern hardware acceleration and quantum computing. His early work focused on nuclear reactor simulation and radiation shielding, then evolved to parallel computing and distributed systems, and has recently centered on hardware acceleration for complex algorithms, quantum computing applications, and AI hardware. This progression demonstrates his ability to transition between major technological paradigms while maintaining expertise in computational methods and hardware implementation. Professor Le has demonstrated significant leadership in professional service, having served as keynote speaker, general chair, technical program chair, session chair, reviewer, and committee member for numerous international conferences. His service extends beyond academia through his role as Co-Founder and Advisor of the Vietnamese Strategic Ventures Network and Chairman of the Board of the United States–Vietnam Foundation. In his educational role, Professor Le has made substantial contributions to engineering curriculum development and assessment. He has taught a wide range of courses including EE271 (Advanced Digital System Design), EE210, EE250, and various project/thesis courses. His research advising spans digital system design, ASIC, SOC, and hardware accelerators. He has also collaborated with local companies on projects related to high-performance system architectures, parallel algorithms, digital arithmetic, and System-on-Chip verification.

Antti H. Niemiمشاهده پروفایل

استاد

• Computational Solid Mechanics
• Structural Engineering
• Civil Engineering
• +۵ مورد دیگر

Antti H. Niemi is a Professor and Dean at the University of Oulu 's Faculty of Technology , specializing in computational solid and structural mechanics. His research focuses on advanced numerical methods for engineering analysis and design. Research areas include computational mechanics, structural engineering, and metamaterials Develops innovative finite element methods for thin-body problems Current projects address snow structures, timber building envelopes, and machine learning applications in mechanical systems His recent work emphasizes discontinuous Petrov-Galerkin (DPG) methods for plates and shells, with applications in civil and mechanical engineering. Publications cover: Snow and ice vaults (2024) Machine learning for steel beam capacity prediction (2024) Hygrothermal analysis of timber structures (2024) DPG formulation for Reissner-Mindlin plates (2023) Shell element benchmarking (2018-2022)

• Timber Engineering
• Structural Engineering
• Timber Frame Construction
• +۵ مورد دیگر

Professor Abdy Kermani serves as Professor and Director of the Centre for Timber Engineering within the School of Engineering and The Built Environment at Edinburgh Napier University. With over 80 research outputs spanning nearly two decades, his work focuses on advancing timber engineering practices and sustainable construction methodologies. His research portfolio includes significant contributions to timber frame construction, structural analysis, and innovative timber applications in building systems. Professor Kermani's research interests center on timber engineering with particular emphasis on structural performance, racking behavior in timber framed walls, vibration analysis of timber floors, and innovative applications of timber in bridge construction. His work bridges theoretical analysis with practical applications, addressing critical challenges in sustainable construction and building performance. Through his leadership at the Centre for Timber Engineering, he has developed methodologies for assessing timber structural elements and implemented innovative design approaches for timber construction systems. Analysis of Professor Kermani's 15 most recent publications reveals a consistent focus on timber structural performance, with particular attention to racking resistance in timber framed walls, vibration characteristics of timber floors, and innovative applications of timber in structural systems. His research demonstrates a progression from fundamental structural analysis toward practical implementation of timber engineering solutions, with increasing emphasis on computational modeling and optimization techniques in recent years. KTP Simpson Strong Tie (2007-2012): £191,048 - Developed structural elements for timber frame market providing racking resistance KTP Diageo Plc (2007-2011): £213,688 - Optimized whisky cask design POC: Composite Insulated Beams (2004-2009): £179,881 James Jones & Sons Ltd (2004-2006): £70,429 - Secured European Product Approval for timber products Oregan Timber Frame Ltd (2004-2006): £69,596 - Developed integrated manufacturing strategy Professor Kermani has supervised numerous doctoral students including Roshan Dhonju (Racking performance of platform timber framed walls), Ahmed Mohamed (Photogrammetric techniques for evaluating timber properties), Eleni Tsechelidou (Investigating gaps in civil engineering education), Zaihan Jalaludin (Water vapour sorption behaviour of wood), and Kenneth Leitch (Development of a hybrid racking panel). His leadership extends to the Centre for Timber Engineering, where he directs research initiatives focused on advancing timber construction technologies and promoting sustainable building practices through innovative engineering solutions.

Federica Sandroneمشاهده پروفایل

مدرس

• Rock Mechanics
• Tunnel Engineering
• Underground Construction
• +۴ مورد دیگر

Federica Sandrone is a Lecturer at the School of Architecture, Civil and Environmental Engineering (ENAC) at École Polytechnique Fédérale de Lausanne (EPFL), where she also serves as a Scientist at the Laboratory of Experimental Rock Mechanics (LEMR) within the Institute of Civil Engineering. Her academic career spans over 15 years with continuous contributions to tunnel engineering and rock mechanics research. Her research focuses on the intersection of rock mechanics and tunnel engineering, with particular expertise in tunnel pathology analysis, TBM performance in challenging geological conditions, and long-term tunnel behavior. Sandrone's work bridges theoretical analysis with practical engineering applications, addressing real-world problems in tunnel infrastructure management and maintenance. Her research methodology combines field investigations, laboratory testing, and numerical modeling to understand complex geomechanical behaviors. Analysis of her recent publications reveals a consistent focus on tunnel inspection methodologies, TBM performance prediction in difficult ground conditions, and the long-term behavior of tunnel structures. Her work has evolved from fundamental tunnel pathology studies to more advanced applications involving GIS integration, probabilistic modeling, and modern inspection techniques including laser scanning and image analysis. Engineer at SBB-Infrastructure (2008-present) responsible for Tunnels Management and Maintenance Assistant for Tunnel Engineering courses (2007-present) PhD supervision including Erika Paltrinieri's 2015 thesis on TBM performance Development of tunnel inspection methodologies and condition assessment procedures Her teaching activities include courses in Rock Mechanics and Underground Construction, where students learn about the mechanical behavior of rock materials, tunnel excavation and support design, planning and management of underground works, and risk assessment in tunnel construction.

• Model-Based Design
• Design Automation
• Optimization
• +۴ مورد دیگر

Marc C.W. Geilen is an Associate Professor at the Electronic Systems group , Eindhoven University of Technology. He leads the Model-Based Design Lab and contributes to the CompSOC Lab and High Tech Systems Center . His work focuses on model-based design methods, design automation, and optimization for real-time and embedded systems. Research Keywords: Cyber-Physical Systems, Real-Time Systems, Embedded Systems, Performance Analysis, Design Automation Key Collaborations: EU ECSEL TRANSACT project, SAM-FMS project, Arrowhead Tools initiative His recent publications address weakly-hard timing constraints in server-based systems, hybrid performance modeling for cyber-physical systems, and neural network optimization for communication. Article trends span Real-Time Scheduling , Trustworthy Modeling , Neural Network Efficiency , and Resource Allocation in distributed environments. Scientific Awards : Partial-Order Reduction for Performance Analysis (2018) Teaching activities include courses in Computational Modeling , Embedded Signal Processing , and Discrete Mathematics . He collaborates across projects like TRANSACT, SAM-FMS, and Arrowhead Tools, focusing on flexible manufacturing and cloud-to-edge transitions.

Xiong Zhangمشاهده پروفایل

استاد

• Geotechnical Engineering
• Unsaturated Soils
• Frozen Ground Engineering
• +۵ مورد دیگر

Xiong Zhang is a Professor in the Department of Civil, Architectural and Environmental Engineering at Missouri University of Science and Technology (Missouri S&T), with additional affiliation to the Center for Intelligent Infrastructure. His research focuses on advanced geotechnical engineering methodologies addressing unsaturated soils, frozen ground, and infrastructure resilience. His educational background includes: Ph.D. in Civil Engineering from Texas A&M University Dr. Zhang's research spans critical geotechnical domains with emphasis on: Development of advanced laboratory techniques for rapid geomaterials characterization Constitutive modeling of hydro-mechanical behavior in unsaturated soils Numerical simulation of climate-soil-structure interactions Slope stability analysis and soil stabilization methods Frozen ground engineering applications Recent publications (2022-2025) reveal a strong trend toward innovative measurement techniques, particularly photogrammetry and computer vision for soil specimen analysis during triaxial testing. His work consistently addresses unsaturated soil mechanics challenges while expanding into practical infrastructure solutions like wicking geotextiles for pavement systems and permafrost region engineering. His scientific recognition includes: 2016 International Innovation Award in Unsaturated Soil Mechanics from the International Society for Soil Mechanics and Geotechnical Engineering As an active mentor and researcher, Dr. Zhang serves on editorial boards including the Canadian Geotechnical Journal and Geomechanics and Engineering. He holds leadership positions in international committees such as TC106 Unsaturated Soils and the ASCE GI Shallow Foundation Committee, demonstrating significant professional engagement. His work with the Center for Intelligent Infrastructure supports advanced infrastructure development through cutting-edge geotechnical research.

Ahmet Bindalمشاهده پروفایل

استاد

• Nano-scale Electron Devices
• Silicon Nanowire Transistors
• VLSI Architecture
• +۴ مورد دیگر

Professor Ahmet Bindal is a faculty member in the Department of Computer Engineering at San José State University . He earned his B.S. in Electrical Engineering from Bogazici University, Turkey, followed by M.S. and Ph.D. degrees from the University of California, Los Angeles. Industry Experience : 20 years at IBM, Intel, Philips, and Cadence Design Systems. Current Research : Nano-scale electron devices, silicon nanowire transistors, robotics, and VLSI architecture. Research Trends : His work focuses on silicon nanowire transistors for VLSI, FPGA, and robotics. Key themes include low-power/high-speed integrated circuits , dynamic logic design , neuromorphic engineering , and advanced semiconductor processing . Patents and Publications : He holds four U.S. patents (three with IBM, one with Intel). His 30+ journal and conference publications span nanowire transistors, FPGA architecture, robotics, and semiconductor process modeling. Teaching Contributions : Developed an undergraduate System-on-Chip (SoC) course and a MOSFET design laboratory at SJSU. Books Authored : Fundamentals of Computer Architecture and Design (Springer, 2017). Electronics for Embedded Systems (Springer, 2017). Silicon Nanowire Transistors (Springer, 2017).

Young Ook Kimمشاهده پروفایل

استاد

• Spatial Morphology
• Space Syntax
• Urban Design
• +۷ مورد دیگر

Young Ook Kim is a Professor at the Department of Architecture, Sejong University. His research focuses on spatial morphology, space syntax, and urban design, with applications in pedestrian behavior analysis and urban regeneration. 1999 Ph.D., University College London 1994 M.S., University of Colorado, Denver 1986 B.S., Yonsei University His work explores the relationship between spatial layouts and human behavior, particularly in crowded environments. Recent studies include predictive modeling for crowd accidents and agent-based simulations for subway station design. Key methodologies involve space syntax and computational modeling. Latest research trends emphasize pedestrian safety, urban walkability, and regional spatial characteristics, leveraging space syntax tools and agent-based simulations to analyze crowd dynamics and urban configurations. He has collaborated extensively on projects related to spatial configuration and urban planning, with contributions to conferences like the International Space Syntax Symposium. His h-index is 7, with 13 Scopus citations on recent works. 2024: Crowd accident risk prediction, improved agent simulations, and regional walking behavior studies 2023: Pedestrian behavior analysis in Seoul's Gangnam Station 2022: Mega-shelter layout planning and user-behavior studies