جستجوی استاد راهنمای دانشگاهی

Anna Dysonمشاهده پروفایل

استاد پژوهش

• Sustainable Architecture
• Built Ecologies
• Solar Energy Systems
• +۳ مورد دیگر

Anna Dyson is an educator and Research Professor at the School of Architecture, Rensselaer Polytechnic Institute. She serves as Director of The Center for Architecture, Science, and Ecology (CASE), which oversees the Graduate Program in Architectural Sciences specializing in Built Ecologies. Her work focuses on integrating solar energy systems into architectural design to enhance environmental control and sustainability. The Center for Architecture, Science, and Ecology (CASE) is a key research unit under her direction, emphasizing interdisciplinary approaches to ecological architecture. Her research interests revolve around adaptive building technologies, solar energy integration in building envelopes, and sustainable architectural systems. She collaborates on projects that bridge architectural design with scientific principles to create energy-efficient and ecologically responsive structures. Recent publications (2014-2015) highlight advancements in modeling adaptive solar energy systems and high-efficiency building envelopes. These works contribute to broader discussions on sustainable urban infrastructure and climate-responsive design strategies. Lectures and events organized by her team include the Spring 2025 Lecture Series featuring prominent architects such as Thom Mayne and James Carpenter, emphasizing public engagement with architectural innovation. Labs/Teams: Directs Center for Architecture, Science, and Ecology (CASE) in New York, focused on built environment research and education.

Mahya Samمشاهده پروفایل

استاد آموزشی

• Human-Robot Collaboration
• Construction Resilience
• Architectural Engineering
• +۳ مورد دیگر

Mahya Sam, Ph.D., is an Assistant Teaching Professor at the Department of Civil Engineering, Florida International University. Her research focuses on human-robot collaboration in construction, construction resilience, architectural engineering, and sustainable construction practices. She has contributed to over a dozen peer-reviewed articles since 2020, exploring topics ranging from robotics integration in construction workflows to energy efficiency in building design. Dr. Sam earned her Ph.D. in Civil Engineering, reflecting her expertise in interdisciplinary approaches to civil engineering challenges. Her work emphasizes sustainable solutions, such as optimizing material selection for carbon footprint reduction and analyzing renewable energy trends for energy resilience. Her articles consistently highlight trends in automation adoption, construction industry strategies, and environmental sustainability. Key themes include evaluating human-robot collaboration perceptions, quantifying carbon emissions in educational buildings, and leveraging computational fluid dynamics for ventilation optimization in climate-specific designs. Despite her active research output, no scientific awards have been documented in the provided materials. Mahya Sam’s advising and grant activities remain unreported in the current data. She is affiliated with the Department of Civil Engineering and contributes to educational initiatives at FIU, though no specific labs or teams are mentioned.

Stephen Pistoriusمشاهده پروفایل

استاد

• Medical Physics
• Medical Imaging
• Image Reconstruction
• +۴ مورد دیگر

Stephen Pistorius is a Professor in the Department of Physics and Astronomy at the University of Manitoba's Faculty of Science. He serves as Associate Head and Director of the Medical Physics Program, focusing on interdisciplinary research at the intersection of medical physics, biomedical engineering, and artificial intelligence. Role : Professor, Associate Head, Director of Medical Physics Program Contact : Office 205 Allen Building, Stephen.Pistorius@umanitoba.ca , +1 204-474-6205 Research Interests Medical Imaging : Development and optimization of radar-based microwave sensing systems for breast cancer detection. Image Reconstruction : Innovation in computational algorithms for PET and microwave imaging. Artificial Intelligence : Application of machine learning to tumor detection and signal analysis. Publication Trends His recent work emphasizes microwave imaging hardware (antenna arrays, phantom materials), machine learning integration for tumor detection, and image quality metrics across modalities. Key subfields include radar systems , stochastic optimization , and clinical translation of microwave sensing . Additional Contributions He contributes to radiation oncology via EPID-based positioning automation and dose verification systems, while also addressing technical challenges in 3D-printed phantom modeling and microwave propagation in biological tissues.

• Automation Engineering
• Robotics
• Materials Science
• +۳ مورد دیگر

Andrés Suárez García is an Assistant Professor at the University of Vigo's Department of Systems and Automation Engineering. His teaching includes courses on Systems and Control Engineering, Industrial Computing, Robotics, and Automation Fundamentals. He has consistently taught across multiple academic years from 2014/2015 to 2024/2025, covering disciplines like structural mechanics, fluid dynamics, and manufacturing quality control. His research focuses on interdisciplinary engineering applications, emphasizing automation, robotics, additive manufacturing, and energy systems. Notable projects include optimizing 3D printing parameters, analyzing lithium-ion battery health using machine learning, and developing IoT-based educational platforms. He also explores naval and military engineering challenges, such as energy storage for submarines and structural design for space exploration vehicles. Over 20+ supervised final-year projects highlight his mentorship in cutting-edge technologies like piezoelectric energy harvesting, supercapacitor integration in military vessels, and AI-driven anomaly detection in maritime routes. His work bridges theoretical engineering principles with practical applications in defense, environmental monitoring, and sustainable infrastructure.

Henrik Madsenمشاهده پروفایل

استاد

• Energy Systems
• Stochastic Processes
• Demand Response
• +۷ مورد دیگر

Henrik Madsen is a Professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU). His work focuses on energy systems, stochastic processes, and mathematical modeling. He leads research in areas such as demand response in district heating, probabilistic forecasting, and integration of renewable energy sources. Madsen has supervised multiple PhD students and contributes to projects like the IEA DHC Annex TS9 and SEEDS initiative. His expertise includes statistical analysis, time series modeling, and data-driven approaches for energy systems. He actively engages in collaborative research on smart grids, thermal energy storage, and sustainable energy solutions. Education: Academic qualifications from DTU, though specific details are not provided in the text. Research Interests: Mathematical modeling of energy systems Probabilistic forecasting methodologies Integration of wind and solar power Dynamic modeling for district heating Data assimilation in hydrological systems Optimization of energy flexibility Publications & Trends: Recent works emphasize demand response strategies, district heating optimization, and machine learning tools like the nabqr Python package and evalprob4cast R package. His research bridges theoretical stochastic methods with practical applications in energy infrastructure. Grants & Projects: IEA DHC Annex TS9: Digitalization of district heating SEEDS: RES-integrated electrified heating systems Data-Driven Methods for Demand-Side Flexibility Labs/Teams: Collaborates with DTU's Dynamical Systems group and participates in interdisciplinary initiatives like the Frigg 2.0 energy system analysis framework.

• Building Ventilation
• HVAC Systems
• Thermal Comfort
• +۳ مورد دیگر

Simone Dugaria is a Senior Research Associate at the Institute of Building Technology and Energy (IGE) at Lucerne University of Applied Sciences and Arts (since 2023). He holds a Ph.D. in Energy Engineering from the University of Padua (2014-2017) and has held postdoctoral roles at the University of Padova (2017-2019) and the Free University of Bolzano-Bozen (2019-2022). His research focuses on building ventilation, HVAC systems, thermal comfort, indoor air quality, and heat transfer, bridging technical systems with human-centric environmental considerations. Education : Ph.D. in Industrial Engineering – Energy Engineering, University of Padova (2014-2017) Master in Energy Engineering, University of Padova (2014) Bachelor in Energy Engineering, University of Padova (2010) Technical High School in Electrotechnics and Automation, G. Galilei (2006) His research explores energy-efficient technologies for sustainable thermal systems, particularly in building environments. Recent projects include optimizing heat/moisture recovery in office buildings and reducing power peaks via enthalpy recovery. He contributes to applied research addressing real-world challenges in energy systems and indoor environmental quality. Key projects include the EISCH initiative on exhaust air heat pumps and the RePPER study on power peak reduction. His work emphasizes practical applications for enhancing energy efficiency and occupant comfort in built environments. Language skills: Italian (native), German (C1/B2), English (C1/B2).

Vincent Jeseoمشاهده پروفایل

استادیار

• Relationship Marketing
• Services Marketing
• Sales Management
• +۲ مورد دیگر

Vincent Jeseo is an Assistant Professor at Rowan University's William G. Rohrer College of Business. His research focuses on relationship marketing in service environments, examining customer engagement and service failure management. Research explores: Customer-to-customer interaction dynamics Identification mechanisms in service loyalty AI applications in marketing Service failure recovery strategies Publications demonstrate progression from service engagement foundations (2021) toward AI applications (2025). Consistent focus on human elements in service relationships.

• Computer Vision
• Artificial Intelligence
• Multimodal Learning
• +۴ مورد دیگر

Ke Yan is an Associate Professor in the Department of Computer Science at the National University of Singapore's College of Design and Engineering. With extensive research output from 2021-2026, their work spans computer vision, artificial intelligence, and multimodal learning systems. National University of Singapore (Primary Affiliation) Collaborations with University of Electronic Science and Technology of China Research ties with Tencent Youtu Lab in Shanghai Research focuses on advancing computer vision techniques, particularly in medical image analysis, vision-language integration, and fault diagnosis systems. Their work bridges theoretical AI development with practical applications in healthcare, industrial systems, and environmental monitoring. Notable contributions include novel approaches to multimodal learning, medical image segmentation with sparse annotations, and improving reliability of large vision-language models. Recent publication trends (2024-2026) demonstrate increasing focus on multimodal systems, with significant contributions to vision-language model reliability, medical AI applications, and efficient transfer learning techniques. Their work frequently addresses critical challenges like hallucination mitigation in large models and sparse data scenarios in medical imaging. As an advisor, they mentor multiple researchers including Junlong Du, Shouhong Ding, and Zhiwen Lin, with whom they frequently collaborate on cutting-edge computer vision projects. Their research group maintains strong industry connections, particularly with Tencent's AI research division. The research is conducted within NUS's computer vision and AI research ecosystem, collaborating with multiple laboratories focused on multimodal intelligence and practical AI deployment in real-world systems.

• Civil Engineering
• Infrastructure Maintenance
• Climate Change Adaptation
• +۳ مورد دیگر

Irina Stipanovic is an Assistant Professor specializing in Market Dynamics, focusing on infrastructure maintenance, climate change adaptation, and railway systems. Her research integrates advanced technologies like Digital Twins and machine learning to enhance decision-making in civil engineering contexts. Her work addresses critical challenges in infrastructure management, including risk-based maintenance scheduling, structural health monitoring, and flood resilience. She explores innovative methods such as entity-embedding neural networks and vision-based 3D inspections to improve predictive maintenance and asset lifecycle management. Key themes in her research include: Railway earthwork maintenance under climate change Multi-objective decision models for infrastructure prioritization Integration of Structural Health Monitoring (SHM) into Digital Twin platforms Resilience planning for critical infrastructure against floods and other hazards She has contributed to EU initiatives on standardization of Digital Twin applications and has published extensively on railway, tunnel, and bridge management. Her work emphasizes data-driven approaches to sustainable infrastructure solutions.

• Service-Oriented Architectures
• Cloud Computing
• Data Management
• +۷ مورد دیگر

Professor Kyriazis Dimosthenis holds a faculty position at the Department of Digital Systems, University of Piraeus. He earned his diploma in Electrical & Computer Engineering from the National Technical University of Athens (2001) and a cross-disciplinary MSc in Techno-Economic Systems (2004). His academic rank is Professor specializing in service-oriented architectures with a focus on quality of service and workflow management. He has led European projects like BigDataStack, CrowdHEALTH, and CYBELE, addressing challenges in cloud computing, edge computing, and AI-driven solutions for healthcare, finance, and industrial sectors. His research emphasizes resilient service-oriented systems, AI explainability, and human-centric digital transformation. Notable contributions include frameworks for dynamic resource allocation in hybrid cloud/edge environments, AI applications for maritime safety, and data governance solutions for cross-sector integration. He coordinates initiatives such as the Future Internet Architecture Board and Cloud QoS&SLAs, driving advancements in federated data marketplaces and sustainable computing practices. His recent work explores Large Language Model (LLM) applications in financial decision-making, conversational AI for MLOps, and neurosymbolic systems for defect detection. He also investigates XAI methodologies, including VirtualXAI, which leverages GPT-generated personas for explainability assessment. His projects often bridge technical innovation with societal impact, such as the iHELP platform for holistic health records and SmartCHANGE for behavioral change strategies in youth health. Key themes in his publications include bias mitigation in machine learning, dynamic deployment prediction in hybrid cloud settings, and energy-efficient data spaces for mobility. He has contributed to standards like the H2020-funded IRMOS and 5GTANGO, emphasizing interoperability and fault-tolerant architectures. His work frequently intersects with EU policy frameworks, particularly in data governance and ethical AI implementation.

Satyam Paulمشاهده پروفایل

مدرس ارشد

• Mechanical Engineering
• Control Theory
• Vibration Control
• +۵ مورد دیگر

Satyam Paul is a Senior Lecturer in Mechanical Engineering at Örebro University, Sweden. His academic journey includes roles as Senior Research Fellow at University of Nottingham (2022-2023), Assistant Professor at University of the West of England (2020-2021), and postdoctoral researcher positions at Örebro University (2018-2020) and Tecnológico de Monterrey (2018). He holds a PhD from CINVESTAV-IPN (Mexico), MSc in Mechatronics from VIT University (India), and BEng in Mechanical Engineering from NIT (India). Research Focus: Vibration control, fault detection in mechanical systems, control theory, and mechatronics. Key areas include active vibration control of structures, chatter suppression in milling processes, and fuzzy logic-based control systems. Research Projects: "A general digital twin driving mining innovation" (ongoing) "Production Centred Maintenance (PCM)" "Digital twin for sustainable production as a service" Awards: Full Fellowship Status (FHEA, UK) for teaching excellence in higher education. Grants & Labs: Active in the "Digitalized product and production development" research group. Leads projects combining statistical/logical modeling with industrial applications. Publications: Over 15 peer-reviewed articles in journals like Applied Sciences , IEEE Access , and Journal of Vibration and Control , plus book chapters and conference proceedings on structural control and mechatronics.

• Building Design and Performance
• Visual and Thermal Comfort
• Human Health and Wellbeing
• +۷ مورد دیگر

Veronica Garcia Hansen is an Associate Professor in the School of Architecture & Built Environment at Queensland University of Technology (QUT). Her research focuses on the interplay between building design and performance, emphasizing visual/thermal comfort, human health/wellbeing, and innovative methodologies using sensors, machine learning, and VR. She is an internationally recognized expert in high-performance building envelopes, daylighting, and lighting's non-visual health effects. Her 2020 WiSTEM2D award ($250k grant) supported 'healing environments in hospitals via efficient lighting design,' one of six global awards selected from 550 applications. Education: PhD (Queensland University of Technology), BArch (Other). Professional memberships include AIA, ASA, ISES, CIE (Division 3 Editor), and multiple editorial roles. Research Leadership: HDR Training Coordinator (2019–2021), Deputy Academic Lead (Architecture), and leader of QUT's Design Lab 'Emerging Technologies' program. She chairs CIE Division 3 (Interior Environment & Lighting Design) and represents Australia in IEA Task 61. Awards & Recognition: 2020 Johnson & Johnson Scholar; 2003 Asian Innovation Award (Bronze); Division Editor roles; and leadership in global architectural science initiatives. Supervision & Grants: Advised over 100 postgraduate students and led projects like 'Designing Healthy and Efficient Luminous Environments' (LP150100179). Current supervision includes lighting design strategies for healthcare staff wellbeing. Labs/Teams: Core member of QUT's Design Lab, focusing on emerging technologies and interdisciplinary architectural science research.

Mathias Haageمشاهده پروفایل

مدرس ارشد

• Robotics
• Automation
• Construction
• +۳ مورد دیگر

Mathias Haage is a Senior Lecturer and Project Manager at the Department of Computer Science, Lund University, affiliated with the Faculty of Engineering (LTH). He is a member of LTH's Profile Areas in 'Circular Building Sector' and 'AI and Digitalization,' and part of ELLIIT: the Linköping-Lund initiative on IT and mobile communication. His research focuses on Robotics and Automation, particularly in construction and industrial applications. He leads projects like the 'Center for Construction Robotics' and 'RobotLab LTH,' emphasizing automation in construction processes and smart manufacturing. Key research topics include parallel-kinematic manipulators, industrial robot applications, and ontology-based knowledge representation for robotics. He has contributed to advancements in construction automation, flexible manufacturing systems, and robot skill reusability. His work aligns with UN Sustainable Development Goals related to industry, innovation, and infrastructure. Haage has supervised over 33 research outputs, including peer-reviewed conference papers and journal articles. Notable collaborations include projects with Heidelberg Materials Cement Sverige AB and FORMAS. He actively participates in initiatives like the Robotics Week for Schools and AI Lund seminars, promoting public engagement in robotics and AI.

• Software Engineering
• Probabilistic Programming
• Security and Penetration Testing
• +۵ مورد دیگر

Jürgen Cito is an Associate Professor in the Department of Software Engineering at the Faculty of Informatics, TU Wien, where he leads research in probabilistic programming, security, and configuration management. His work is supported by major grants from the Austrian Science Fund (FWF), European Commission, and Meta Platforms, Inc., with active projects spanning 2022-2027. His research focuses on the intersection of software engineering and machine learning, particularly in static analysis of probabilistic programs, AI-driven penetration testing, and infrastructure security. Key contributions include identifying secret exposure in configuration files, grammar inference for ad hoc parsers, and performance prediction from source code, often combining empirical studies with tool development. Analysis of his 15 most recent publications (2020-2024) reveals three dominant trends: (1) Security vulnerabilities in configuration management systems, especially secret leakage in dotfiles; (2) Application of large language models to offensive security testing; and (3) Machine learning techniques for performance prediction and AutoML optimization in software contexts. Cito has supervised 22 Master's students on cutting-edge topics including AI security, infrastructure as code, and program analysis. His current research portfolio includes: Types4Strings (FWF, 2024-2027): Type systems for string processing Cloud Open Source Research Mobility Network (EU, 2023-2026): Open-source cloud infrastructure Software Assistants for Probabilistic Programming (Meta, 2022-2026): AI tools for probabilistic code He is embedded in TU Wien's Institute of Software Technology and Interactive Systems (E194), collaborating on cross-institutional projects focused on software security and developer tooling, with particular emphasis on empirical validation of security practices and configuration management systems.

Josep Casanovasمشاهده پروفایل

استاد

• Modelling and Simulation
• Internet and Information Systems
• Urban Mobility
• +۴ مورد دیگر

Josep Casanovas is a Full Professor at the Statistics and Operations Research Department of the Technical University of Catalonia (UPC), affiliated with the Barcelona School of Informatics. He previously served as head of inLab FIB (2012-2020) and as dean (1998-2004) and vice-rector (2006-2011) of UPC, leading strategic initiatives in university governance and ICT policies. His research focuses on Modelling and Simulation , Internet and Information Systems , and Urban Mobility . He has led projects for the European Union, including C-ROADS Spain, REMEDiAL, and ECHORD++, addressing intelligent transport, software automation, and robotic innovation. Recent publications highlight his work on agent-based simulation for urban health, deep learning applications in traffic and energy savings, and wildfire management tools . He co-directs LogiSim and coordinates the Severo Ochoa Research Excellence Program at the Barcelona Supercomputing Center (BSC-CNS).