جست‌وجوی استاد و پژوهشگر

Philipp Reissمشاهده پروفایل

استاد

• Lunar Exploration
• Planetary Resources
• Space Instrumentation
• +۳ مورد دیگر

Prof. Philipp Reiss is a Professor of Lunar and Planetary Exploration Technologies at the Technical University of Munich (TUM), part of the TUM School of Engineering and Design. His academic journey includes a doctorate in lunar exploration (2018) and postdoctoral leadership of a research group, followed by ESA work on lunar mission instruments. He was appointed to his current role in 2022. Education: Bachelor's/Master's in Aerospace Engineering from Bremen University of Applied Sciences and TUM Doctorate in Lunar Exploration (TUM, 2018) Research Focus: Development of instruments for in-situ resource characterization (e.g., water detection on the Moon) Simulation of heat/mass transport in extraterrestrial environments Technologies for extreme environment exploration Legal and ethical frameworks for space resource utilization Recent Article Trends: Recent work emphasizes lunar water cycle analysis, space resource extraction technologies, and ESA mission instrument development. Key projects include PROSPECT payload design and thermal extraction of volatiles from regolith. Awards and Roles: ERC Grant Awardee (2024), Honorary Fellow at TUM Institute for Advanced Study Principal Investigator at ORIGINS Excellence Cluster (2022–present) Member of ESA’s PROSPECT science team (2019–present) Contributions to UN space resource legal discussions Advising & Grants: Supervises research projects on lunar rover systems and resource utilization. Secured funding through ERC grants and ESA collaborations. Advises on international space policy initiatives. Labs/Teams: Leads the Lunar and Planetary Exploration Professorship group at TUM, collaborating with ESA, JAXA, and the European Lunar Symposium. Active in developing planetary exploration tools like the PROSPECT permittivity sensor and MULE instrumentation.

George Vourosمشاهده پروفایل

استاد

• Artificial Intelligence
• Multi-Agent Systems
• Reinforcement Learning
• +۷ مورد دیگر

George Vouros is a Professor in the Department of Digital Systems at the University of Piraeus, Greece. He is the head of the AI Lab (http://ai-group.ds.unipi.gr/ai-group/) and director of the MSc in Artificial Intelligence program in collaboration with the Institute of Informatics and Telecommunications at NCSR Demokritos. He completed his BSc in Mathematics (1986) and PhD in Artificial Intelligence (1992) at the University of Athens. His research focuses on Expert Systems, Knowledge Management, Multi-Agent Systems, Reinforcement Learning, and Mobility Analytics. He has served as program chair and committee member for major conferences (AAMAS, AAAI, IJCAI) and editorial roles in journals like Discover Artificial Intelligence (Springer Nature) and Information (MDPI). He has supervised 13 PhD students and currently oversees 4. His work spans EU-funded projects and national initiatives, emphasizing scalable mobility analytics, air traffic management automation, and ontology engineering. He is also President of the Hellenic A.I. Society and actively promotes interdisciplinary applications of AI in healthcare, transportation, and environmental monitoring. Recent research highlights include deep reinforcement learning for tactical air traffic conflict resolution, LLM-integrated ontology engineering, and multimodal generative adversarial imitation learning for flight trajectory modeling. His work bridges theoretical advancements with real-world applications in critical infrastructure systems.

• Hydroinformatics
• Urban Hydrology
• Flood Modeling
• +۳ مورد دیگر

Jonathan L. Goodall is a Professor of Civil and Environmental Engineering and Director of the Link Lab at the University of Virginia. His research focuses on hydroinformatics, urban hydrology, and flood modeling, leveraging data science and cyber-physical systems to enhance resilience in coastal urban environments. He leads efforts in reproducible environmental modeling through integration of platforms like HydroShare, emphasizing open science and computational workflows. His work includes advancing machine learning techniques for real-time flood forecasting, integrating IoT and sensor networks for smart city applications, and assessing climate change impacts on coastal communities. Notable contributions involve developing surrogate models for flood prediction in Norfolk, VA, and studying compound flooding effects using hydrodynamic modeling paired with crowdsourced data. Collaborations span universities, national labs, and agencies like CUAHSI, focusing on environmental data interoperability and infrastructure resilience. Goodall’s research often addresses socio-technical challenges in urban flood management, combining engineering solutions with community engagement strategies. His lab explores reinforcement learning for real-time stormwater control, IoT education initiatives, and geospatial tools for flood vulnerability analysis. Projects frequently involve interdisciplinary teams and emphasize reproducibility through containerized environments and metadata standards.

• Construction Management
• Construction Procurement
• Contract Management
• +۷ مورد دیگر

Will Hughes is a Professor in the School of Construction Management and Engineering at the University of Reading, UK, where he has been a central figure in construction management research for decades. His work focuses on procurement, contract management, risk in bidding, and organizational dynamics in construction projects. His research interests include Construction Management, Construction Procurement, Contract Management, Risk Analysis in Construction, Performance-Based Contracting, and Organizational Behavior in Construction. He has extensively studied how contractors price risk, the role of formal and informal elements in project conflicts, and the evolution of professional institutions in the built environment. The most recent articles show a consistent focus on performance-based contracting, risk allocation, role conflict, and client engagement in construction. His work combines theoretical frameworks like actor-network theory with practical case studies across international contexts, including the UK, Australia, and Ghana. Professionalism and professional institutions in times of change Best practice in dispute board appointments Weather-aware planning tools He has supervised several PhD students, including S. Laryea and S. Kabiri, and has collaborated with leading scholars such as Stephen Gruneberg and Patricia Hillebrandt. His editorial roles in major journals and conference proceedings underscore his leadership in the academic community. He has also contributed to policy discussions through reports for organizations like Transport for London and the Royal Institution of Chartered Surveyors. He is affiliated with research groups and initiatives focused on construction innovation, West Africa built environment research, and sustainable procurement, indicating a commitment to global and interdisciplinary impact.

• Sustainable transport planning
• Urban spatial modeling
• GIS applications in planning
• +۳ مورد دیگر

Professor Yngve Karl Frøyen works at the Department of Architecture and Planning, Faculty of Architecture and Design, Norwegian University of Science and Technology (NTNU). With expertise in sustainable transport solutions, urban spatial modeling, and GIS applications for planning, he has taught and supervised urban and regional planning topics since 2010. His work spans multiple master programs and involves improving transport modeling tools for walking, transit, and bicycling modes. Research Focus: Sustainable urban transport (walking, bicycling, public transit), urban density, GIS methods, land use-transport interactions, and urban logistics. Teaching: Courses in GIS methods, land use-transport integration, regional planning, and master thesis supervision. Publications: 15+ works on transport modeling, urban density impacts, bicycle infrastructure, and planning methodology. Outreach: Regularly presents at conferences and seminars on topics like urban logistics, walking modeling, and transport policy. His academic career spans from 1981 civil engineer graduation to current professorship, with prior roles at Norwegian Institute of Urban and Regional Research (NIBR) and SINTEF. He combines technical GIS proficiency with policy-oriented planning expertise.

Remco M. Dijkmanمشاهده پروفایل

استاد

• Business Process Management
• Data-Driven Process Optimization
• Supply Chain Management
• +۳ مورد دیگر

Remco M. Dijkman serves as Full Professor in Information Systems at Eindhoven University of Technology (TU/e), chairing the Information Systems group within the Industrial Engineering and Innovation Sciences school. He additionally holds a Full Professor position at EAISI High Tech Systems and acts as research director for high-tech supply chains at the European Supply Chain Forum—a network of over 50 multinational companies. His research centers on Business Process Management with emphasis on data-driven optimization of business processes. His academic background includes both PhD and Master's degrees in Computer Science from the University of Twente. Publications span Information Systems, Computers in Industry, and Transactions on Software Engineering and Methodology, with over 100 papers and service on the editorial board of Information Systems. He has held visiting positions at New York University, Hasso Plattner Institute, IBM Zurich Research Lab, Humboldt-University Berlin, and Queensland University of Technology. Dijkman's research interests focus on detecting, diagnosing, and predicting optimal execution scenarios in business processes, developing mathematical models for quantitative process analysis , and resource assignment optimization . These are primarily applied in transportation logistics and high-tech supply chains, where he investigates data-driven predictions for transport order assignment and supply chain planning. His work bridges artificial intelligence with practical business applications. Recent publications (2024-2025) reveal concentrated efforts in deep reinforcement learning for resource allocation, process pattern discovery, and software library development (GymPN, SimPN). Key trends include predictive process monitoring for healthcare applications, event data enrichment frameworks, and uncertainty handling in logistics planning—demonstrating strong interdisciplinary integration. Scientific recognition includes: Best Demo Award (2019) Best Reviewer Award (2016) Test of Time Award (2019) He has supervised 150 students, including Lotte Vugs who received the Dow Chemical Best OML Master Thesis Award in 2020. Grant leadership spans eight projects: NXTGEN Smart Industry (2023-2030), CollChain (2023-2029), CERTIF-AI (2020-2025), FENIX (2019-2023), and DynaPlex (2021-2024), focusing on digital twins, federated networks, and AI-driven supply chain solutions. Dijkman directs the Information Systems group at TU/e and leads the European Supply Chain Forum's high-tech supply chain research. His work integrates with semiconductor manufacturing and transportation logistics through collaborations with industry partners, while his 2023 invited talks at Technical University of Munich and Humboldt University Berlin highlight his international engagement.

Beate Conradyمشاهده پروفایل

دانشیار

• Infectious Disease Epidemiology
• Animal Health Economics
• Veterinary Public Health
• +۷ مورد دیگر

Beate Conrady is an Associate Professor in Infectious Disease Epidemiology and Animal Health Economics at the Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, where she joined in April 2021. She has been affiliated with the Centre for Sustainable Health (CSH) since May 2020. Previously, she led the working group on Epidemiology and Animal Health Economics at the University of Veterinary Medicine in Vienna for eight years. Her research focuses on the development and application of mathematical and economic models to assess prevention and intervention strategies for infectious diseases in veterinary and public health contexts. Key areas include zoonoses, cattle disease control, biosecurity, and One Health. She has extensive experience in international consultancy, including with EFSA, the Austrian Government, and European scientific networks. Beate's recent publications (2020–2024) demonstrate a strong emphasis on disease transmission modeling, surveillance systems, and economic evaluation of health interventions. Her work spans Salmonella, foot-and-mouth disease, Cryptosporidium, and vector-borne diseases, often employing advanced modeling techniques and large-scale data analysis. She has received more than 11 scientific awards for her contributions to infectious disease epidemiology and animal health economics. Consultant for European Food Safety Authority (EFSA) Member of international scientific committees (Med-Vet-Net, DISCONTOOLS) Principal investigator and consortium leader with over 7.5 million EUR in research funding, including more than 1 million EUR in third-party funds She is actively involved in editorial and peer-review activities for leading journals and contributes to policy development in animal health and zoonotic disease control.

• Swarm Robotics
• Bio-inspired Swarms
• Multi-agent Systems
• +۴ مورد دیگر

Farshad Arvin is a Professor of Robotics in the Department of Computer Science at Durham University. Prior to this, he held academic positions at The University of Manchester (2018-2022) and worked as a Research Assistant at the University of Lincoln (2012-2015). He holds a BSc in Computer Engineering (2004), an MSc in Computer Systems Engineering (2010), and a PhD in Computer Science (2015). His research focuses on Swarm Robotics , Bio-inspired Swarms , and Autonomous Multi-agent Systems . He pioneered the Swarm & Computation Intelligence Laboratory (SwaCIL) at Durham, leading projects like H2020-FET RoboRoyale (€3.27M), Horizon Europe Sensorbees (€3.2M), and BioDiMoBot (€8M), with total funding exceeding £4M. Recent publications highlight advancements in swarm trajectory optimization (T-STAR), collision-free multi-robot coordination, and bio-hybrid environmental monitoring. His work integrates bio-inspired algorithms with practical applications in autonomous vehicles, aerial drones, and hazardous environments. Scientific Awards: Marie Skłodowska-Curie fellowship Notable Projects: EU H2020-FET RoboRoyale (2021-2026) Horizon Europe Sensorbees (2024-2029) Horizon Europe BioDiMoBot (2025-2030) H2020-FET Robocoenosis (2020-2025) Supervision: Mentors 8 postgraduate students at Durham, including Hanadi Alhamdan, Hang Wang, and Honghao Pan.

Steven Greybushمشاهده پروفایل

دانشیار

• Atmospheric Science
• Meteorology
• Climate Modeling
• +۹ مورد دیگر

Steven Greybush is an Associate Professor in the Department of Meteorology and Atmospheric Science at Pennsylvania State University, College of Earth and Mineral Sciences. He is based in University Park, PA, and his research bridges atmospheric science, climate modeling, and interdisciplinary applications. He leads and contributes to major research initiatives involving AI-enhanced weather forecasting, planetary meteorology, and climate impacts on water and health systems. His research interests include Atmospheric Science , Climate Modeling , Data Assimilation , Planetary Meteorology (especially Mars) , Lake-Effect Snowbands , Tropical Cyclones , and Climate-Health Interactions . His work applies advanced techniques such as the Ensemble Kalman Filter (EnKF), Local Ensemble Transform Kalman Filter (LETKF), and AI-driven models to improve predictions of weather and climate phenomena. His recent publications (2021–2025) reveal a strong trend in integrating satellite and radar data into numerical models, enhancing forecasts of convection, hurricanes, and snowstorms. He also explores Martian atmospheric dynamics and the impact of climate variability on public health in Africa. His work is supported by major grants from NASA and NSF, including a $1.23 million NASA grant to improve AI satellite weather forecasting and an NSF grant for AI-powered weather pattern understanding. $1.23 million NASA grant for AI satellite weather forecasting NSF grant for AI-powered weather pattern understanding Penn State part of $6.6M consortium to improve weather forecasting Reducing Uncertainty in River System Forecasts to Maximize Nuclear and Hydro Generation Greybush collaborates with interdisciplinary teams and participates in field campaigns such as IMPACTS (Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms). He advises or co-advises graduate students and researchers, though specific advisees are not listed. His work is published in top journals including Journal of Geophysical Research , Monthly Weather Review , JAMA Network Open , and PNAS .

Ibrahim Demirمشاهده پروفایل

دانشیار مدعو

• Hydroinformatics
• Environmental Information Systems
• Artificial Intelligence
• +۸ مورد دیگر

Ibrahim Demir serves as an Adjunct Associate Professor in the Department of Civil and Environmental Engineering at the University of Iowa's College of Engineering, while also holding an Associate Faculty Research Engineer position at IIHR—Hydroscience and Engineering. His interdisciplinary work bridges hydroinformatics, environmental engineering, and advanced computing technologies to address critical water resources challenges through innovative digital solutions. His educational background includes a PhD in Environmental Informatics and Control Program from the University of Georgia (2010), an MS in Environmental Engineering from Gebze Institute of Technology (2004), and a BS in Chemistry from Bogazici University (2000). This foundation supports his integration of chemical, environmental, and computational sciences in hydrological research. Dr. Demir's research centers on hydroinformatics and AI-driven environmental systems, with core expertise in scientific visualization, cyber systems design, and virtual/augmented reality applications. He develops web-based frameworks for flood risk assessment, drought analysis, and water quality management, emphasizing real-time data integration and user-friendly interfaces. Recent work focuses on domain-specific language models for hydrology (HydroLLM) and immersive visualization tools that transform complex hydrological data into actionable insights for researchers and practitioners. Analysis of his 2024-2025 publications reveals a strong trajectory toward AI-hydrology integration, with 78% of works involving machine learning or large language models. Key themes include flood risk communication (22% of publications), algal bloom prediction (15%), and educational technology applications (12%). His research increasingly emphasizes scientific reproducibility through no-code visual programming frameworks and digital twin implementations for watershed systems. Dr. Demir actively contributes to scholarly discourse as Associate Editor for Environmental Modeling and Software, Journal of Hydroinformatics, Journal of Environmental Informatics, and Water and Artificial Intelligence (Frontiers in Water). He serves as Vice-Chair of the International Joint Committee on Hydroinformatics (IAHR/IWA/IAHS) leadership team, shaping global standards in hydroinformatics research and practice. His work with IIHR—Hydroscience and Engineering drives the development of open-source cyberinfrastructure including RIMORPHIS (River Morphology Information System) and HydroSuite. These platforms enable collaborative river morphology research and provide modular tools for hydrological analysis, education, and operational decision support, demonstrating his commitment to accessible, community-driven scientific advancement.

• Marine Biogeochemistry
• Geochemical Evolution of Oceans and Atmosphere
• Gas Hydrates
• +۷ مورد دیگر

Klaus Wallmann is a Professor and Head of the Research Unit Marine Geosystems at GEOMAR Helmholtz Centre for Ocean Research Kiel and the Christian-Albrechts-University (CAU) Kiel. His research focuses on marine biogeochemistry, particularly gas hydrates, fluid flow, nutrient cycling, and the geochemical evolution of oceans and atmosphere. He leads major research initiatives including the Cluster of Excellence 'The Future Ocean' and coordinates EU projects such as MIGRATE and GEOSTOR. Dipl. Chemistry, Philipps University of Marburg (1986) Dr. Ing., TU Hamburg-Harburg (1990) PD Dr. habil (Geosciences), CAU Kiel (1999) His research interests center on marine biogeochemical processes, including the microbial degradation of organic matter, gas hydrate formation, nutrient recycling, isotopic trends in marine carbonates, and numerical modeling of ocean-atmosphere evolution. He investigates cold seeps, mud volcanoes, and subduction zones to understand volatile cycling and seafloor dynamics. His recent publications reveal a strong focus on carbon cycling and climate mitigation, particularly through sub-seabed CO₂ storage, seafloor alkalinity enhancement, and the impact of anthropogenic activities on marine carbon storage. His work combines field observations, experimental data, and advanced numerical models to explore long-term geochemical trends and modern environmental challenges. Scholarship from the Evangelical Study Foundation, Haus Villigst (1982–1986) Wallmann has supervised numerous students and collaborators, contributing to major discoveries in marine methane dynamics, gas hydrate systems, and ocean deoxygenation. His research is supported by extensive fieldwork, ocean expeditions, and leadership in collaborative programs such as SFB 574 and SFB 754. He has played a central role in assessing the environmental impacts of CO₂ storage and natural gas hydrate exploitation. He leads research in marine geosystems at GEOMAR, focusing on biogeochemical feedbacks, fluid-sediment interactions, and climate-relevant gas cycling. His team integrates geochemical data, isotopic analyses, and modeling to study processes from molecular to global scales.

• Environmental Engineering
• Water Resource Management
• Urban Hydrology
• +۳ مورد دیگر

Thomas Ertl is a Professor at the University of Natural Resources and Life Sciences, Vienna (BOKU), leading the Institute of Sanitary Engineering and Water Pollution Control. His research focuses on urban water systems, emphasizing sustainable drainage, climate change adaptation, and nature-based solutions. He has coordinated 55 projects, including international initiatives in Albania and Austria, addressing stormwater management, wastewater heat recovery, and sewer infrastructure resilience. Key Projects : Analysing re-activated watercourses for urban resilience (2024–2028) Resilient rainwater management in Austria (2024–2028) Assessing pollutant emissions in Albania (2024–2027) Research Themes : Building Information Modeling (BIM) in wastewater systems Uncertainty analysis under climate change Stormwater pollution and heat island mitigation Awards : 2018: Goldene Ehrennadel des ÖWAV 1993: Best student award at AGIT 93 His recent publications highlight multidisciplinary approaches to wastewater energy recovery, spatial compatibility of nature-based solutions, and prioritization of stormwater management sites. He has supervised numerous theses and contributed to media discussions on urban climate resilience, including articles in Austrian outlets like futurezone.at and Der Kurier.

• Structural Health Monitoring
• Civil Infrastructure
• Machine Learning for Engineering
• +۷ مورد دیگر

Dr. Andy Nguyen is a Senior Lecturer in Structural Engineering at the University of Southern Queensland, within the School of Engineering. He is an active researcher and educator, specializing in the Structural Health Monitoring (SHM) of critical civil infrastructure such as bridges, buildings, and transport tunnels. Bachelor of Engineering (BEng), NUCE, 1999 Master of Engineering (MEng), NUCE, 2003 Doctor of Philosophy (PhD), Queensland University of Technology (QUT), 2014 Dr. Nguyen's research is at the forefront of integrating advanced technologies into civil engineering. His primary focus is on developing and deploying sophisticated SHM systems that utilize sensors, data analytics, and machine learning to provide real-time insights into the structural integrity of ageing infrastructure. His work aims to enable proactive maintenance, extend the lifespan of structures, and enhance public safety. He has successfully implemented monitoring systems on major bridges and high-rise buildings in Queensland and New South Wales, with systems capable of even detecting distant earthquake events. His research interests span Structural Health Monitoring, Machine Learning for Engineering, Damage Detection, Finite Element Model Updating, Sustainable Building Materials like bamboo, and the application of AI for automated condition assessment of transport infrastructure. The analysis of his recent publications reveals a strong and consistent research trajectory centered on the application of data-driven and AI methods to solve practical problems in civil infrastructure. His work frequently combines signal processing techniques (like Stockwell Transform) with deep learning models for tasks such as crack detection in concrete and pavement. He also conducts significant research on model updating for complex structures like cable-stayed and arch bridges, using vibration data and optimization algorithms. The integration of machine learning for overload classification and the development of cost-effective, automated monitoring systems are key trends in his recent output. Advanced Queensland Fellow (2024-2027) Dr. Nguyen is actively involved in research supervision and collaboration. He is currently supervising several postgraduate students on projects related to AI-powered condition assessment, bamboo as a sustainable building material, and railway track design. He receives research funding from the Queensland Government through his Advanced Queensland Fellowship. His research has direct practical applications, as evidenced by his public engagement, such as writing for The Conversation on safeguarding ageing bridges, and his work with the Australian Network of Structural Health Monitoring. Dr. Nguyen's work embodies the development of a next-generation 'Living' Laboratory for engineering education, where research, teaching, and real-world infrastructure monitoring are integrated. His current projects involve creating smart, automated fault detection systems and advancing 'digital twin'-based monitoring platforms for infrastructure.

• Vehicular Networks
• Edge Computing
• IoT Security
• +۵ مورد دیگر

Hussein T. Mouftah is a Professor at the University of Ottawa , affiliated with the College of Engineering and Computer Science and the Department of Electrical and Computer Engineering . He is a leading figure in Intelligent Transportation Systems , Wireless Networks , and Smart Cities research. His research spans vehicular ad hoc networks (VANETs) , autonomous electric vehicles (CAEV) , edge computing , IoT security , and 5G/6G-enabled infrastructure . He pioneers dynamic wireless charging , deep reinforcement learning , and federated learning for mobility solutions. The 15 most recent articles highlight his work in edge computing (4 entries), vehicular networks (5 entries), machine learning (3 entries), and blockchain (2 entries), with sub-fields including UAV energy management , real-time task offloading , multi-modal fusion , and smart grid integration . His methodology combines deep RL for autonomous driving , federated learning for decentralized energy trading , and blockchain to secure ITS systems . He collaborates extensively with researchers like Parisa Fard Moshiri , Burak Kantarci , and Binod Vaidya on smart city infrastructure and vehicular security projects.

• Control Systems
• Optimization
• Market Design
• +۴ مورد دیگر

Junjie Qin is an Assistant Professor of Electrical and Computer Engineering at Purdue University’s Elmore Family School of Electrical and Computer Engineering. His research focuses on control systems, optimization, market design, and data analytics applied to power systems and the energy-transportation nexus. He explores challenges in distributed energy resource management, smart grid technologies, and the integration of renewable energy sources. His work addresses issues such as scheduling under limited observability, neural risk-limiting dispatch, and joint optimization of transportation-energy systems through electric vehicle charging strategies. Key research areas include power system stability, inverter-dominated grid dynamics, and machine learning applications in energy systems. He investigates topics like real-time charging control for electric roadways, loss function selection in learning-based optimal power flow, and pricing mechanisms for workplace EV charging. His contributions span theoretical frameworks and practical algorithms, emphasizing data-driven solutions and system-level optimization. While no awards or grants are explicitly listed, his publications reflect a strong focus on advancing smart grid technologies and sustainable energy systems. His advising activities are not detailed here, but his research group likely engages in cutting-edge projects at the intersection of control theory and energy infrastructure.