جست‌وجوی استاد و پژوهشگر

• Stormwater Management
• Hydrology
• Environmental Monitoring
• +۵ مورد دیگر

Dr. Walter McDonald is an Associate Professor in the Department of Civil, Construction and Environmental Engineering at Marquette University . He specializes in water resources engineering, with a strong focus on stormwater management, hydrology, and environmental monitoring. His work integrates remote sensing, machine learning, and green infrastructure to address urban water challenges. Education: Ph.D. in Civil Engineering, Virginia Tech (2016) M.S. in Civil Engineering, Texas A&M University (2012) B.S. in Civil Engineering, Texas Tech University (2010) Research Interests: Dr. McDonald’s research is centered on urban water systems , particularly the impact of stormwater on environmental and public health. His work spans the use of green infrastructure to mitigate pollution, the detection and modeling of emerging contaminants such as antibiotic resistance genes, microplastics, and PFAS, and the application of drone-based remote sensing and machine learning for real-time monitoring of water systems. Scientific Awards: Way Klingler Early Career Award from Marquette University (April 2022) Grants and Funding: NSF Water Equipment & Policy I/UCRC – Principal Investigator on "Remote sensing and machine learning to assess urban watershed best management practices (Phase II)" ($89,962, 2024) U.S. Department of Defense Engineering Research and Development Center – Co-PI on "Novel Technologies to Mitigate Water Contamination for Resilient Infrastructure – Phase II" ($3.8M, 2022–2024) NSF STTR – PI on "Machine learning and video-based sensor for measuring sewer flows" ($256,000 total; $138,926 to MU, 2022–2024) NSF Water Equipment & Policy I/UCRC – PI on "Determining flow rates and flow sources in pipes using temperature data" ($50,000, 2023) Research Labs and Facilities: Dr. McDonald works closely with the Transportation Research Center (MUTRC) and utilizes departmental labs such as the Engineering Materials & Structural Testing Lab (EMSTL) , Hydraulics Lab , and the Water Quality Center to support his research activities.

Borja Garcia de Sotoمشاهده پروفایل

دانشیار

• Construction Automation
• Cybersecurity in the AEC Industry
• Artificial Intelligence
• +۵ مورد دیگر

Borja Garcia de Soto is an Associate Professor at New York University (NYU) and a Global Network Associate Professor in the Department of Civil and Urban Engineering at NYU's Tandon School of Engineering. He directs the S.M.A.R.T. Construction Research Group at NYU Abu Dhabi, focusing on construction automation, cybersecurity in the AEC industry, artificial intelligence, lean construction, and BIM. His research bridges technological innovation with practical construction challenges, emphasizing digital fabrication and smart infrastructure. He holds a PhD in Civil Engineering from ETH Zurich, an MSc in Engineering and Project Management from UC Berkeley, and dual MSc/BSc degrees in Civil Engineering from Florida International University (FIU), graduating cum laude. Research Interests: Construction automation, cybersecurity threats in AEC, AI applications, lean construction methodologies, BIM integration, digital twins, and robotic systems. Publications: Over 50 peer-reviewed works on topics spanning neural networks for construction scheduling, digital fabrication productivity, cybersecurity risk modeling, and BIM-based optimization tools. Awards: Honorary Fellow of ISTeA (2023), ALEC Innovation Day Partner of the Year (2023), SciRoc Competition Winner (2021), ICE Publishing Award (2016), and ETH Zurich Construction & Infrastructure Prize (2015). Editorial Roles: Associate Editor for Automation in Construction , Journal of Construction Robotics , and Smart and Sustainable Built Environment . Professional: Licensed Professional Engineer (California, Florida) with industry experience in structural engineering and project management.

Orphée De Clercqمشاهده پروفایل

استادیار

• Natural Language Processing
• Machine Learning
• Readability Prediction
• +۷ مورد دیگر

Orphée De Clercq is an Assistant Professor at Ghent University, specializing in language technology for educational applications. Her research focuses on leveraging Natural Language Processing (NLP) and Machine Learning (ML) to enhance computer-assisted language learning , readability prediction , and automated writing evaluation . She also explores sentiment analysis , emotion detection , and event coreference resolution in Dutch and multilingual contexts. Education : PhD in 2015 with groundbreaking work in readability prediction and fine-grained sentiment analysis for Dutch. Research Trends in her recent publications emphasize: Readability across domains and languages Emotion Detection using transformers and affect lexica Event Coreference in cross-document news Automated Writing Evaluation through NLP Implicit Sentiment Analysis in user-generated content Cross-Lingual Transfer with multilingual datasets She co-supervises four PhD students and contributes to interdisciplinary projects like Steunpunt Toetsen , SentEMO , and NewsDNA . Her teaching includes courses on digital communication and Computer-Assisted Language Learning .

Jason Chenمشاهده پروفایل

دانشیار

• Tourism Economics
• Tourism Demand Modelling
• Quantitative Research Methods
• +۳ مورد دیگر

Jason Chen is an Associate Professor in Tourism and Events Management at the University of Surrey, serving as Director of Postgraduate Research in the School of Hospitality and Tourism Management. He holds a PhD in Tourism Management from The Hong Kong Polytechnic University, alongside earlier degrees in Economics (BA, 2004) and Economics and Statistics (MSc, 2007). His research focuses on tourism economics, tourist behavior, demand forecasting, and quantitative methods. Notable projects include 'Understanding the Landscape of Inbound Tourism Measurement' and collaborations with organizations on tourism impact assessments. He has secured grants, including an ESRC grant for the School, and advises on postgraduate research programs. Teaching responsibilities include modules in International Tourism Management, Consumer Behavior, and Researcher Development. His recent publications emphasize spatiotemporal models, crisis management in tourism, and pro-environmental behavior interventions. He has contributed to policy-relevant studies on tourism's economic role and sustainability challenges. Key research themes include destination resilience, electric vehicle adoption, and behavioral nudging for sustainability. His work bridges academic theory with practical applications, supporting industry and policy stakeholders.

Mine Doganمشاهده پروفایل

استادیار

• Environmental Geophysics
• Groundwater Modeling
• Stochastic Hydrology
• +۳ مورد دیگر

Dr. Mine Dogan serves as Assistant Professor of Environmental Geophysics in the Department of Geological and Environmental Sciences at Western Michigan University, with her office located in 1121 Rood Hall (Kalamazoo, MI). She holds a Ph.D. from Michigan State University (2013) and previously held research positions at Clemson University's Department of Environmental Engineering and Earth Sciences. Education: Ph.D., Michigan State University, 2013 Her research integrates geophysics, hydrology, and environmental engineering to investigate subsurface processes using advanced methodologies including drone-based electromagnetic surveys, time-lapse monitoring, and 4D X-ray computed tomography. Key focus areas include tree root hydrology, contaminant transport in groundwater, permafrost characterization, and macropore flow dynamics in heterogeneous soils. Analysis of her recent publications (2018-2024) reveals strong emphasis on unmanned aerial systems for geophysical data acquisition, visualization of fluid transport mechanisms in porous media, and forensic/environmental applications of electromagnetic methods. Recurring themes include the role of biological structures in hydrological processes and innovative approaches to subsurface imaging. Scientific Awards: No awards documented in source material While her advising activities and grant funding remain unspecified in available information, her publication record demonstrates active collaboration across geophysics, hydrology, and environmental engineering disciplines. Laboratory facilities and research team structures are not detailed in the provided texts.

• Atmospheric Science
• Satellite Remote Sensing
• Air Pollution Monitoring
• +۵ مورد دیگر

Dr. Folkert Boersma is a Professor at Wageningen University and Research specializing in atmospheric science and satellite remote sensing. He leads significant international research projects focusing on air pollution monitoring, wildfire impacts, and climate change analysis using advanced satellite instrumentation. His research interests span atmospheric chemistry, environmental monitoring, and climate data analysis, with particular expertise in nitrogen dioxide (NO 2 ) measurements, carbon cycle analysis, and wildfire monitoring. Dr. Boersma's work integrates satellite data with ground-based measurements and computer models to understand complex environmental processes. His recent publications demonstrate a strong focus on improving the accuracy of satellite-based atmospheric measurements, with particular emphasis on TROPOMI observations. His research has advanced our understanding of urban and industrial emissions, ship pollution patterns, wildfire impacts, and carbon uptake dynamics. Dr. Boersma collaborates extensively with international partners including KNMI, SRON, and various European universities. INFLAMES project funding (5-year, nearly €18 million) Dr. Boersma actively supervises PhD students including Juliette Anema, Christoph Riess, Auke Visser, and Felipe Cifuentes, whose research focuses on satellite-based environmental monitoring. His work has significant implications for air quality management, climate policy development, and environmental protection strategies worldwide.

Baishakhi Rayمشاهده پروفایل

دانشیار

• Software Engineering
• Security
• Artificial Intelligence
• +۳ مورد دیگر

Baishakhi Ray is an Associate Professor of Computer Science at Columbia University, working at the intersection of AI, Software Engineering, and Security. She received her Ph.D. from the University of Texas, Austin, and has established herself as a leading researcher in applying artificial intelligence to software engineering challenges. Her educational background includes a Ph.D. from the University of Texas, Austin, which provided the foundation for her research career at the forefront of AI and software engineering. Dr. Ray's research focuses on leveraging artificial intelligence to solve fundamental challenges in software engineering and security. Her work spans multiple areas including code generation with large language models, vulnerability detection, software testing, and program analysis. She has pioneered approaches that combine deep learning with traditional software engineering techniques to create more robust, secure, and efficient software development processes. Her research has practical implications for improving code quality, enhancing software security, and accelerating development cycles through AI assistance. Her recent work demonstrates a strong emphasis on semantic-aware code generation, execution reasoning, and addressing hallucinations in code language models. She has also made significant contributions to evaluating the functionality and security of AI-generated code, identifying critical challenges in the practical adoption of AI for software development. Dr. Ray has received numerous prestigious awards recognizing her contributions to the field: IEEE TCSE Rising Star NSF CAREER award IBM faculty award VMware Faculty award Distinguished Paper awards at FSE'17, ASE'22, and ISSTA'23 ICSME Most Influential Paper award Publications featured in CACM Research Highlights As an Amazon Visiting Academic and active participant in major software engineering conferences, Dr. Ray has established herself as a thought leader in AI for software engineering. Her research has been widely covered in trade media, indicating its relevance and impact on industry practices. She has mentored numerous students through their research and has been instrumental in shaping the next generation of researchers in this interdisciplinary field. Her work demonstrates a consistent focus on bridging theoretical advances with practical applications, ensuring that her research has tangible benefits for the software development community. The trajectory of her publications shows an evolving research agenda that has successfully adapted to the rapidly changing landscape of AI and its applications to software engineering.

Polycarpou Mariosمشاهده پروفایل

استاد

• Neural networks
• Cyber-physical security
• Fault diagnosis
• +۴ مورد دیگر

Professor Marios Polycarpou is a leading academic in intelligent systems and control engineering at the University of Cyprus, serving as Director of the KIOS Research and Innovation Center. He holds concurrent roles as Visiting Professor at Imperial College London and Founding Member of the Cyprus Academy of Sciences. His expertise spans neural networks, cyber-physical security, and critical infrastructure systems. Education: B.A. Computer Science & B.Sc. Electrical Engineering, Rice University, 1987 M.S. & Ph.D. Electrical Engineering, University of Southern California, 1989-1992 Research Interests: Intelligent systems and networks Adaptive learning control systems Fault diagnosis methodologies Machine learning applications Critical infrastructure resilience Awards: IEEE Neural Networks Pioneer Award (2016) ERC Advanced and Synergy Grants IEEE/IFAC Fellowships Cyprus Distinguished Researcher Award (2015) Grants & Leadership: Directed over 40 research projects Presidency roles in IEEE Computational Intelligence Society and European Control Association Edited prestigious journals including IEEE Transactions on Neural Networks Led major conferences: 2020 IEEE World Congress on Computational Intelligence and 2018 European Control Conference. Labs & Teams: Founder of KIOS Center (EU-funded excellence center) Developed SEMIoTICS semantic control framework

Michalis Mountantonakisمشاهده پروفایل

پژوهشگر

• Large-Scale Semantic Data Integration
• Linked Open Data
• Semantic Web
• +۴ مورد دیگر

Michalis Mountantonakis is a Postdoctoral Researcher at FORTH and Laboratory Teaching Staff in the Department of Computer Science at the University of Crete, Greece. He holds a PhD (2020), MSc (2016), and BSc (2014) in Computer Science from the University of Crete, all with top grades. His research focuses on Large-Scale Semantic Data Integration, Linked Open Data, and Semantic Web technologies, with over 45 publications in top venues like ACM VLDB, ISWC, and ECML. He has been awarded the prestigious SWSA Distinguished Dissertation Award (2020) and the Maria Michael Manasaki Fellowship (2020). His work includes tools like LODsyndesis and LODChain, addressing challenges in knowledge graph connectivity and validation of AI-generated content. Education: PhD in Computer Science (2016-2020), University of Crete (Excellent GPA 9.74/10) MSc in Computer Science (2014-2016), University of Crete (Excellent GPA 9.87/10) BSc in Computer Science (2010-2014), University of Crete (2nd in class with GPA 8.42/10) Research Interests: His work bridges semantic web technologies with modern AI challenges, emphasizing large-scale data integration, knowledge graph applications, and validation frameworks. He has contributed to cultural heritage informatics, machine learning-augmented semantic systems, and cross-lingual NLP solutions. Recent trends include leveraging LLMs for query generation and semantic enrichment while ensuring factual accuracy through knowledge graph-driven validation. Key Achievements: Developed LODsyndesis, a global-scale semantic integration service Pioneered real-time validation of ChatGPT responses using RDF knowledge graphs Won Best Paper Award (ISWC 2022) for entity enrichment techniques Recipient of Stelios Orphanoudakis Undergraduate Fellowship (2013-2014) Participated in Roche Continents 2019 (top 100 European science students) Grants & Labs: His research has been supported by GSRT/HFRI. He collaborates with FORTH-ICS and leads projects in EU-funded initiatives like iMarine and BlueBridge. Current work focuses on governance models for ontologies, interoperable thesaurus creation (e.g., FoodEx2), and semantic analytics for cultural heritage datasets.

• Remote Sensing
• GIS
• Ecology
• +۶ مورد دیگر

Dr. Harm Bartholomeus is an Assistant Professor of Remote Sensing at the Department of Geo-information Science and Remote Sensing, Wageningen University & Research. He received his MSc in Physical Geography (2000) and a Geography teaching degree (2001) from Utrecht University. His career includes part-time PhD research (2004–2009) on soil property estimation via spectral measurements and vegetation influence. Since 2009, he has focused on remote sensing techniques like imaging spectroscopy, LiDAR, and UAV-based methods applied to forestry, soil science, and climate studies. In 2012, he co-founded the Wageningen UR Unmanned Aerial Remote Sensing Facility (UARSF), advancing UAV research in environmental studies. His expertise spans Ecology, Geographical Information Systems (GIS), Remote Sensing, Soil Science, Spectroscopy, and 3D analysis. He teaches courses such as Advanced Earth Observation, Remote Sensing and GIS Integration, and MSc thesis supervision in Geo-information Science and Remote Sensing. His work integrates cutting-edge technologies for environmental monitoring, including terrestrial laser scanning and drone-based sensing. Research interests include vegetation-soil interactions, UAV applications in agriculture and ecology, and climate resilience. He collaborates on projects like the UARSF and contributes to global initiatives like the IDEAS-QA4EO network. No scientific awards are explicitly mentioned, but his contributions to UAV and LiDAR methodologies are widely recognized. He advises MSc students on thesis and internship projects in remote sensing and geo-information science.

Longxiang Liمشاهده پروفایل

استادیار

• Environmental Health
• Exposure Assessment
• Spatial Analysis/GIS
• +۴ مورد دیگر

Longxiang Li is an Assistant Professor in the Gangarosa Department of Environmental Health at Emory University's Rollins School of Public Health. His research focuses on environmental pollutants' human health impacts, particularly unconventional oil and gas development (fracking) and radon exposure. Funded by NIH, he develops satellite-based machine learning models to assess exposure risks. Before joining Emory in 2024, he studied/worked at Harvard T.H. Chan School of Public Health. Education: Sc.D. from Harvard T.H. Chan School of Public Health; M.S. from Chinese Academy of Sciences; B.S. from China University of Geosciences (Beijing). Research interests include exposure assessment, spatial analysis/GIS, and machine learning applications in environmental health. Notable work includes high-resolution radon models and collaborations with the White House on radon-related lung cancer prevention strategies. Key articles focus on radon's effects on asthma, cancer, and pregnancy outcomes, using advanced modeling techniques. His work bridges environmental data science with public health policy. Affiliations: International Society of Environmental Epidemiology, International Society of Exposure Science, American Chemistry Society.

• Business Analytics
• Operations Research/Management
• Operational Analytics
• +۷ مورد دیگر

Mehdi Toloo is a Reader in Business Analytics at the University of Surrey's Surrey Business School. He holds a BSc, MSc, and PhD, and is a docent. Previously, he was a Professor at Technical University of Ostrava (Czech Republic) and Sultan Qaboos University (Oman). His research focuses on Business Analytics, Operations Research, Data Envelopment Analysis (DEA), and Decision Analysis. He has supervised over 40 postgraduate students and contributed to top-tier journals like European Journal of Operational Research and Omega. He is an editor for journals including Computers & Industrial Engineering and Decision Analytics. Recognized globally, he ranks in the top 2% of scientists worldwide in Business Analytics & Operations Research (2020-2024). His research projects include performance evaluation with unclassified factors, economies of scope in network DEA, and selective measures in DEA. He collaborates internationally on projects like robust optimization and supply chain sustainability. His teaching spans undergraduate courses in Operations Research, Mathematics for Business, and Programming, alongside postgraduate modules on Quantitative Methods and Advanced DEA. His work bridges theoretical and applied research, with applications in healthcare, renewable energy, and public policy.

Anders Perssonمشاهده پروفایل

استاد

• Medical Imaging
• Cardiovascular Imaging
• CT Technology
• +۳ مورد دیگر

Anders Persson is Professor and Head of the Division of Diagnostics and Specialist Medicine at Linköping University, where he also serves as Director of the Center for Medical Image Science and Visualization (CMIV). His pioneering research develops advanced cardiovascular imaging techniques using photon-counting CT technology and computational fluid dynamics. Professor Persson's innovations include rapid cardiac imaging protocols capturing blood flow in a single heartbeat, AI algorithms for automated coronary calcium scoring, and patient-specific computational modeling of cardiac hemodynamics. His work with SCAPIS (Swedish CArdiopulmonary bioImage Study) examines population-level cardiopulmonary health patterns and atherosclerosis development. Recent publications focus on optimizing photon-counting CT for cardiac applications, reducing metal artifacts from implants, and developing deep learning solutions for cardiac segmentation. His research aims to enable earlier detection of cardiovascular disease through advanced imaging biomarkers. No scientific awards are documented in this profile. Professor Persson leads initiatives translating medical imaging innovations into clinical practice for improved cardiovascular diagnosis.

Li Leidaمشاهده پروفایل

استاد

• Computer Vision
• Image and Video Quality Assessment
• Computational Aesthetics
• +۳ مورد دیگر

Professor Li Leida is a National Young Talent and doctoral supervisor at Xidian University's School of Artificial Intelligence. His research focuses on computer vision, image/video quality assessment, computational aesthetics, and visual sentiment analysis. He leads the Brain-like Visual Perception and Evaluation Laboratory and collaborates with industry partners like OPPO, Huawei, and Tencent. He has published over 90 papers in top venues like TPAMI and CVPR, with 6 highly cited papers and 8,400+ citations. He serves as deputy editor-in-chief of IEEE Transactions on Image Processing and is a senior member of IEEE/CCF/CSIG. Education & Academic Roles: PhD Supervisor/Master Supervisor Member of OPPO Computational Imaging Expert Committee Area Chair for ACM Multimedia 2025 Research Interests: Dr. Li's work bridges theoretical computer vision with practical applications in imaging quality, aesthetic evaluation, and sentiment analysis. His team develops benchmarks like AesBench for large model evaluation. Recent advancements include scanned image enhancement algorithms and personalized aesthetic datasets like PARA. Industry Impact: OPPO ColorOS integration Live broadcast camera technologies DXOMARK Portrait Quality Assessment Challenge winner (2024) Awards & Recognition: First Prize in Shaanxi Natural Science (2021) 2022 OPPO Industry Collaboration Award Stanford's Top 2% Global Scientists (2023-2024) Grants & Labs: Secured 5 National Natural Science Foundation projects. Active in lab collaborations with companies like DJI and Huawei's imaging teams.

Semih Doğuمشاهده پروفایل

استادیار

• Electromagnetic Theory
• Microwave Imaging
• Inverse Scattering Problems
• +۳ مورد دیگر

Semih Doğu is an Assistant Professor at the Department of Electronics and Communication Engineering , Faculty of Electrical and Electronics Engineering , Istanbul Technical University . His research focuses on Electromagnetic Theory , Microwave Imaging , Inverse Scattering Problems , and Antenna Design . Doctorate: Istanbul Technical University (2023) Master's: Istanbul Technical University (2017) Bachelor's: Yıldız Technical University (2015) His research interests emphasize microwave-based diagnostics, including: Microwave imaging for breast cancer detection Antenna optimization for medical and security applications Inverse problem solving in electromagnetic systems Through-the-wall imaging for surveillance Semih Doğu's recent publications demonstrate his expertise in: Neural networks for temperature monitoring in hyperthermia Ku/Ka-band antenna designs for satellite systems Microwave salinity sensing Algorithm development for improved imaging accuracy He contributes to the ITU Electromagnetics Research Group , participating in projects like: Microwave Brain and Breast Imaging Device Development Compressed Sensing for Energy-Efficient Communication Microwave Tissue Analysis