جست‌وجوی استاد و پژوهشگر

Brian Surgenorمشاهده پروفایل

استاد

• Mechanical Engineering
• Machine Vision Systems
• Autonomous Vehicles
• +۳ مورد دیگر

Professor Brian Surgenor is a faculty member at Queen's University's Department of Mechanical and Materials Engineering, part of the Smith Engineering faculty. He holds a B.Sc. (1977), M.Eng. (AECL/Whiteshell), and Ph.D. (1983) in Mechanical Engineering from Queen's University. His research focuses on machine vision systems for automation, autonomous vehicle navigation, and mechatronic system design education. He has held key administrative roles including Department Head (1993-2002), Associate Dean (2008-2013), and Vice-Dean (2013-2016). His work emphasizes interdisciplinary innovation, such as the Mitchell Hall design project and contributions to Ingenuity Labs. Education: B.Sc. Mechanical Engineering, Queen's University (1977) M.Eng. Engineering Physics, McMaster University (AECL/Whiteshell) Ph.D. Mechanical Engineering, Queen's University (1983) Research interests include: - Pneumatic servosystems - Intelligent algorithms for machine vision - Off-road autonomous vehicle systems - Mechatronics education methodologies - Hybrid powertrain systems for vehicles His recent publications (2017–2024) explore autonomous systems, machine vision applications, and fuel cell hybrid technologies. Notable trends include advancements in UAV-based infrastructure inspection, terrain-adaptive autonomous driving, and low-cost machine vision solutions for small part sorting. His work bridges theoretical control systems with practical industrial automation challenges. He has contributed to laboratory design for CDIO curricula and pioneered mechatronics education through problem-based learning. His administrative leadership has shaped Queen's engineering graduate programs and research infrastructure. Currently involved in Ingenuity Labs, fostering cross-disciplinary innovation.

Chengzong Pangمشاهده پروفایل

دانشیار

• Power Systems
• Electrical Engineering
• Control Systems
• +۷ مورد دیگر

Chengzong Pang is an Associate Professor and MSECE Graduate Coordinator at the Department of Electrical and Computer Engineering, College of Engineering, Wichita State University. His work focuses on power systems, electrical engineering innovations, and renewable energy integration. He specializes in transient stability analysis, control systems, and smart grid technologies. Research Interests: Dr. Pang's expertise includes advanced control strategies for power electronics (e.g., PMSM, UPQC), machine learning applications for grid stability (LSTM/SVM), and energy storage solutions for renewable integration. His research also addresses challenges in microgrid operation, subsynchronous oscillation mitigation, and battery storage systems. Key Trends in Publications: Over 20 years of publications (2002–2022) emphasize: (1) Machine learning for power system analysis, (2) Control system design for renewable integration, (3) Grid stability enhancement via advanced algorithms, and (4) Smart grid infrastructure optimization. Recent works (2021–2022) highlight transient stability prediction and ANFIS-based power quality solutions. Labs/Teams: Active in energy systems research groups focusing on renewable integration and grid modernization, though specific lab names are not explicitly stated in the provided texts.

İlhan Kocaarslanمشاهده پروفایل

استاد

• Control Systems Engineering
• Load Frequency Control
• Adaptive Control
• +۱۲ مورد دیگر

İlhan Kocaarslan is a Professor in the Department of Control and Automation Engineering at Istanbul Technical University (ITU), Faculty of Electrical and Electronic Engineering. His research focuses on advanced control systems, energy conversion, and sustainable transportation technologies. Research Interests: His work spans Load Frequency Control , Adaptive and Fuzzy Logic Control , PI Controllers , Electric Vehicle energy modeling , Battery and Fuel Cell systems , and Smart Grid integration . He actively contributes to innovations in renewable energy and electromobility. Publication Trends: Recent publications emphasize high-fidelity energy modeling for electric vehicles, optimization of battery systems, control strategies for fuel cells using fuzzy and Lyapunov-based PI controllers, and electromagnetic design for next-generation transportation like Hyperloop. His work bridges theoretical control design with practical energy applications. Scientific Awards: No awards mentioned in the provided text. Advising and Grants: He supervises 25 ongoing theses, indicating active mentorship. He is Principal Investigator (PI) on multiple research projects funded by ITU’s BAP and TTO programs, including initiatives on blockchain-based energy systems, hydrogen technologies, electric mobility, and cybersecurity-integrated sustainability platforms. Labs and Teams: While specific lab names are not mentioned, his role as PI on diverse energy and control projects suggests leadership in a multidisciplinary research group focused on smart energy systems, power electronics, and sustainable transportation at ITU.

Qipei Meiمشاهده پروفایل

استادیار

• Civil Engineering
• Artificial Intelligence
• Robotics
• +۴ مورد دیگر

Qipei Mei is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of Alberta's Faculty of Engineering. With an MSc in Computer Science and a PhD in Structural Engineering, he bridges civil engineering with artificial intelligence to enhance infrastructure productivity and sustainability. His research spans AI-driven design automation, robotics for construction safety, and IoT-based condition assessment. PhD, Structural Engineering - University of Alberta (2020) MSc, Computer Science - Georgia Institute of Technology (2018) MSc, Structural Engineering - University of Alberta (2014) B.E., Civil Engineering - Huazhong University of Science and Technology (2011) Mei's work focuses on three key areas: leveraging data-driven methods for design automation, applying sensing/robotics to construction operations, and using digital twins for infrastructure assessment. His team explores generative AI for housing design, robotic construction in remote communities, and smart monitoring systems. Recent publications highlight advancements in: lateral capacity prediction for monopile foundations, transformer-based architectural layout analysis, large language models for building code compliance, vision-language models for safety hazard detection, and sensor networks for bridge monitoring. These works demonstrate interdisciplinary integration of AI, structural engineering, and IoT. Mei actively collaborates with diverse researchers and welcomes graduate students to his Smart Infrastructure Technologies (SITE) Research Group, part of the Infrastructure and Human Tech Lab (IHT-Lab). He teaches advanced topics in structural and civil engineering while pursuing industry-funded projects through NSERC, CFI, and Alberta Innovates.

• Software Technology
• Artificial Intelligence
• Educational Software
• +۵ مورد دیگر

Maria Virvou serves as Professor and Chair of the Department of Informatics at the University of Piraeus, where she also directs the Graduate Program in Informatics and leads the Research Laboratory 'Software Technology'. She holds significant institutional leadership roles including membership in the University Senate and has chaired the Department of Informatics for multiple terms. As Editor-in-Chief of Springer book series 'Learning and Analytics in Intelligent Systems' and 'Artificial Intelligence-Enhanced Software and Systems Engineering', she maintains substantial academic influence across international scholarly platforms. Dr. Virvou earned her PhD in Computer Science and Artificial Intelligence from the University of Sussex with a scholarship from the State Scholarships Foundation, a Master of Science in Computer Science from University College London, and her undergraduate degree from the Department of Mathematics at the National and Kapodistrian University of Athens. Her educational background in both mathematics and computer science has provided a strong foundation for her interdisciplinary research approach. Professor Virvou's research spans Software Technology, Artificial Intelligence, Educational Software and Games, User Modeling, and Human-Computer Interaction. She has pioneered work in personalized interactive software systems, applying fuzzy logic and machine learning techniques to create adaptive educational environments. Her recent work demonstrates a strategic expansion into AI applications for healthcare, with significant contributions to medical diagnostics using large language models and multimodal AI systems. She has also made notable advances in smart tourism applications through personalization techniques. With over 400 publications to her name, Professor Virvou's scholarly output shows a clear progression from foundational work in user modeling toward increasingly sophisticated AI applications across multiple domains. Her publication trends reveal a strategic focus on explainable AI, multimodal systems, and practical implementations that bridge theoretical advances with real-world applications, particularly in healthcare and education sectors. Ranked #1 worldwide in 'User Modelling' publications (147,450 total publications) according to Scopus Ranked #1 worldwide in 'Educational Software' publications according to both Scopus and Microsoft Academic Search Recognized among the top 2% of most influential Artificial Intelligence scientists worldwide by Stanford University General Co-Chair at the 14th IISA Conference 2023 Invited Keynote Speaker at the 35th IEEE International Conference on Software Engineering Education and Training (CSEE&T 2023) As Director of the Research Laboratory 'Software Technology', Professor Virvou has built a robust research team focused on AI applications across multiple domains. She co-founded and co-chairs the IEEE Intelligent Information Systems and Applications international conference series, creating a significant platform for scholarly exchange. Her leadership extends to editorial roles with major academic publishers and active participation in international research collaborations that have secured substantial funding for innovative projects in AI and software engineering.

Pooya Davariمشاهده پروفایل

استاد

• Harmonic and EMI analysis and mitigation in grid-tied converters
• Electromagnetic interference and compatibility
• High power density power electronic systems
• +۲ مورد دیگر

Pooya Davari is a Professor and Head of the Section for Applied Power Electronic Systems at Aalborg University , Denmark. He leads the EMI/EMC in Power Electronics Research Group and serves as Vice Chair of the Energy Efficiency Mission. His research focuses on electromagnetic interference (EMI) and harmonic mitigation in power electronic systems, with over 200 publications and significant contributions to renewable energy integration. Education: B.Sc. and M.Sc. in Electronic Engineering (2004, 2008), Ph.D. in Power Electronics from Queensland University of Technology (2013) Prior Roles: Lecturer at QUT (2013–2014), Postdoc at AAU (2014) Research Interests: Harmonic and EMI analysis in grid-tied converters High power density converter design Signal processing for converter modeling Reliability of power electronic systems Article Trends: Recent work emphasizes EMI/EMC in renewable energy systems, wide bandgap semiconductors (SiC/GaN), and reliability modeling for EVs and hydrogen production via electrolysis. Sub-fields include converter topologies, grid integration challenges, and AI-driven diagnostics. Scientific Awards: Equinor 2022 Prize (Denmark’s oldest engineering award) IEEE EMC Society Young Professional Award (2020) World’s Top 2% Highly Cited Scientist (Stanford, 2021–2025) Multiple best paper awards (IEEE, Applied Sciences, etc.) Grants & Editorial Roles: Recipient of grants from Innovation Fund Denmark (Supra-EMC project), Horizon Europe (SOLARIS), and industry partnerships. Serves as Area Editor for IEEE Transactions on Transportation Electrification , Associate Editor for IEEE Transactions on Power Electronics , and Editor-in-Chief of Circuit World Journal (2020–2025). Labs & Standards: Coordinator of the EMC Laboratory at Aalborg University. Member of IEC standardization Working Groups 6 and 8 (TC77A), focusing on EMC strategies for power grids.

LJILJANA TRAJKOVICمشاهده پروفایل

استاد

• Communication Networks
• Nonlinear Circuits and Systems
• Electronics Engineering
• +۳ مورد دیگر

Ljiljana Trajkovic is a Professor in the Department of Engineering Science at Simon Fraser University's Faculty of Applied Sciences. She holds a Ph.D. from the University of California, Los Angeles (1986), M.Sc. from Syracuse University (1979), and Dipl.Ing. from the University of Pristina (1974). Her research focuses on communication networks, nonlinear circuits, and machine learning applications for network security. She actively contributes to IEEE initiatives, including roles as conference committee chair and editorial board member. Education highlights include a strong foundation in electrical engineering and advanced studies in circuit theory and systems science. Her work bridges theoretical analysis with practical applications, such as anomaly detection in communication networks using machine learning. She teaches courses like ENSC 220 D100 Electric Circuits I, integrating research insights into education. Research interests emphasize network security, traffic analysis, and distributed systems. Recent articles explore BGP anomaly classification, ransomware detection, and virtual network embedding. She collaborates on tools like VNE-Sim and Anonym for network analysis. Awards and recognitions are highlighted through her leadership roles in IEEE and academic contributions. Advising and grants involve mentoring graduate students in cybersecurity and networking projects. She leads research teams exploring complex networks and their applications in autonomous systems. Her lab focuses on interdisciplinary projects merging electronics engineering with AI-driven network solutions.

Maneesh Agrawalaمشاهده پروفایل

استاد

• Computer Graphics
• Human-Computer Interaction
• Visualization
• +۷ مورد دیگر

Maneesh Agrawala is the Forest Baskett Professor of Computer Science and Director of the Brown Institute for Media Innovation at Stanford University. He is also a consulting AI Scientist at Roblox. His research lies at the intersection of computer graphics, human-computer interaction (HCI), and visualization, with a focus on cognitive design principles for improving audio/visual media. He leads a vibrant research group and has advised numerous PhD students and postdocs. His research interests include: Computer Graphics Human-Computer Interaction Visualization and Visual Communication Cognitive Design Principles Generative AI and Diffusion Models Interactive Video and Sketch-based Interfaces Data and Information Visualization His recent publications (2023–2025) reflect a strong trend toward leveraging generative models—particularly diffusion models—for video and image synthesis, editing, and personalization. Key themes include controllable generation (e.g., SparseCtrl, ControlNet), sketch-to-image translation, relightable texturing, and tools that enhance visual storytelling and data communication. His work integrates cognitive science with computational tools to build systems that support human creativity and understanding. His scientific honors include: MacArthur Foundation Fellowship (2009) Alfred P. Sloan Foundation Fellowship (2007) NSF CAREER Award (2007) SIGGRAPH Significant New Researcher Award (2008) Allen Distinguished Investigator Award (2014) Induction into the SIGCHI Academy (2021) ACM Fellow (2022) Okawa Foundation Research Grant (2006) A dedicated mentor, Agrawala has advised a large cohort of students and postdocs, many of whom have gone on to influential positions in academia and industry. His lab develops tools for video editing (e.g., AnimateDiff, ControlNet), sketch-based design, and visualization (e.g., EmphasisChecker), often bridging theory with practical applications in media and education. He continues to be a leading figure in visual computing and interactive systems.

Tracy Beckerمشاهده پروفایل

استادیار مدعو

• Earthquake Engineering
• Structural Optimization
• Seismic Isolation
• +۳ مورد دیگر

Tracy Becker is an Adjunct Assistant Professor in the Department of Civil Engineering at McMaster University, where she has been since 2014. Her expertise lies in the design, modeling, and experimental testing of high-performance structural systems with a focus on seismic isolation. Education: BS in Structural Engineering, University of California, San Diego MS and PhD in Structural Engineering, Mechanics and Materials, University of California, Berkeley Post-doctoral research at Kyoto University's Disaster Prevention Research Institute Research Interests: Becker specializes in seismic isolation systems, hybrid simulation methods, and structural performance under extreme events. Her work spans bridge engineering, nuclear infrastructure protection, and innovative materials for earthquake resilience. She integrates computational modeling with experimental validation to address challenges in: Nonlinear system behavior in isolated structures Multi-hazard optimization for seismic and wind loads Bridge management using data-driven and fuzzy logic frameworks Advanced gusset plate design for seismic retrofit Adaptive isolation systems for nuclear facilities Probabilistic lifetime demand predictions for infrastructure Teaching: She has instructed courses in Seismic Design (CIVENG 4ED4), Structural Mechanics (CIVENG 2C04), and Earthquake Engineering (CIVENG 730) at McMaster University.

Lindsay McHenryمشاهده پروفایل

استاد

• Volcanic Ash Correlation
• Archaeological Stratigraphy
• Mars Geology Analogues
• +۲ مورد دیگر

Lindsay McHenry is Professor and Department Chair of Geosciences at the University of Wisconsin-Milwaukee. She holds a Ph.D. from Rutgers University, an M.S. from Dartmouth College, and a B.S. from Dartmouth College. Her research focuses on using volcanic ash composition to correlate archaeological sites in East Africa and identifying terrestrial analogues for Martian surface minerals. Her research interests include tephrostratigraphy for human evolution studies, Mars geology analogs, sulfate mineral formation processes, and paleolimnology of saline-alkaline systems. Recent publications demonstrate strong focus on Martian analog studies using terrestrial environments (Iceland, East African lakes), mineral mapping with remote sensing/ML techniques, and paleolake reconstruction. Work increasingly incorporates drone technology and machine learning for planetary exploration applications.

• Environmental Informatics
• Hydrology
• Water Resources Management
• +۳ مورد دیگر

Caterina Valeo is a Professor in the Department of Mechanical Engineering at the University of Victoria's Faculty of Engineering and Computer Science, holding a PhD from McMaster University. Her research focuses on environmental systems modeling with applications in forest management, urban water infrastructure, and climate resilience. Her work spans disturbance modeling in forested regions (including pine beetle infestations and forest fire impacts on watershed hydrology), sustainable urban water development through low-impact design tools like bioretention cells and permeable pavement, and climate change analysis using artificial neural networks for flood frequency prediction. She integrates hydrological, hydraulic, and water quality models to study pollutant dispersion in rivers and nearshore ecosystems, with emphasis on macrophyte-periphyton dynamics and dissolved oxygen impacts on aquatic habitats. Her research provides practical solutions for forest regeneration planning, stormwater management in Canadian climates, and climate-adaptive water infrastructure design through advanced computational approaches including fuzzy logic and neural network quantile estimation.

• Total Productive Maintenance
• Artificial Intelligence
• Multi-Criteria Decision Making
• +۳ مورد دیگر

Ebru Turanoglu Bekar is a Senior Lecturer at the Department of Industrial and Materials Science, Chalmers University of Technology, specializing in Smart Maintenance and Production Systems. She contributes to the Production Service Systems & Maintenance research group. Research Interests: Total Productive Maintenance (TPM), Artificial Intelligence applications in manufacturing, Multi-Criteria Decision Making, Performance Measurement systems Recent Focus: Development of data-driven algorithms for predictive maintenance, integration of digital twins in industrial contexts Key Projects: Factory SensAI (2025–2028) - Data integration for AI in manufacturing Trustworthy Predictive Maintenance TPdM (2022–2025)

FOONG Sew Bunمشاهده پروفایل

دانشیار مدعو

• IT Architecture Patterns
• Service-Oriented Architecture (SOA)
• Software Engineering Methodologies
• +۴ مورد دیگر

Professor FOONG Sew Bun is an Adjunct Associate Professor at the Department of Information Systems and Analytics, School of Computing, National University of Singapore. He holds dual roles as Chief Technology Officer (CTO) for IBM Singapore and IBM ASEAN Software Group, and previously served as Managing Director at DBS Bank, Deputy Chief Executive at GovTech, and Global Head of Digital Transformation at Standard Chartered Bank. His career spans over three decades in IT leadership, technical architecture, and national-level advisory roles. Education: BSc and MSc in Computer Science from the University of Texas at Austin. Research interests focus on IT architecture patterns, service-orientation, software reuse, enterprise architecture, and fuzzy logic. He has authored/co-authored multiple IBM Redbooks and peer-reviewed publications in AI and software engineering. Awards include the 2016 IT Professional of the Year (SCS), IBM Distinguished Engineer distinction, and leadership accolades from IBM. He chairs the National Infocomm Competency Framework Steering Committee and has held key roles in Singapore's IT policy-making bodies. Teaching includes courses on digital transformation in finance (FT5002) and AI-driven business innovations (IS4261). His professional activities span technical councils, industry certifications, and academic collaborations.

Soufiene Djahelمشاهده پروفایل

استاد

• Connected and Autonomous Vehicles (CAVs)
• Unmanned Aerial Vehicles (UAVs)
• Cyber Security
• +۷ مورد دیگر

Soufiene Djahel is a Professor at the Centre for Future Transport and Cities (CFTC) at Coventry University, UK. His research focuses on connected and autonomous vehicles (CAVs), unmanned aerial vehicles (UAVs), cyber security, and smart cities. He holds a PhD in Secure Routing and Medium Access Protocols from Université des Sciences et Technologies de Lille (2010), and has held academic positions including Senior Lecturer at the University of Huddersfield and Manchester Metropolitan University. His research interests include CAV coordination protocols, cyber-physical security solutions, and intelligent transportation systems. Djahel leads projects such as the £1.2M AeroPharma Logistics initiative and has secured funding from the Newton Fund and JSPS. He is a recipient of the 2021 JSPS Invitational Fellowship and has published extensively in IEEE journals and conferences. Current projects explore UAVs-as-a-service, digital twins for CAVs, and B5G/6G for smart infrastructure. He advises PhD students on topics like AI-based threat mitigation and transport electrification. Djahel also serves as an external examiner and editorial board member for journals like IEEE Transactions on Intelligent Transportation Systems.

Ramana Vinjamuriمشاهده پروفایل

دانشیار

• Brain-Machine Interfaces
• Neuroprosthetics and Exoskeletons
• Machine Learning
• +۴ مورد دیگر

Ramana Vinjamuri is an Associate Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC). He holds a secondary appointment as Visiting Professor at the Indian Institute of Technology, Hyderabad, India. His academic journey includes a Ph.D. in Electrical Engineering from the University of Pittsburgh (2008), M.S. in Bioinstrumentation from Villanova University (2004), and B.Tech. in Electrical and Electronics Engineering from Kakatiya University (2002). Dr. Vinjamuri's research focuses on Brain-Machine Interfaces (BMIs) for upper-limb prostheses control , neuroprosthetics and exoskeletons , machine learning in motor control , and neurophysiological signal processing . His work extends synergy-based models to control 37-dimensional hand movements, addresses human-robot interaction through emotionally intelligent systems, and develops neurotechnologies for substance use disorder using wearable sensors and AI. NSF CAREER Award (2019) NSF IUCRC BRAIN Center Planning Grant (2020) Harvey N Davis Distinguished Teaching Assistant Professor Award (2018) His publications demonstrate expertise in EEG and EMG signal analysis , deep learning for motor decoding , synergy modeling , and humanoid robot control . The Vinjamuri Lab at UMBC involves graduate, undergraduate, and high school researchers, with international collaborations in India and the US.