جست‌وجوی استاد و پژوهشگر

Andreas Møgelmoseمشاهده پروفایل

دانشیار

• Computer Vision
• Artificial Intelligence
• Autonomous Systems
• +۳ مورد دیگر

Andreas Møgelmose is an Associate Professor at Aalborg University's Department of Architecture, Design and Media Technology under the Technical Faculty of IT and Design. His research focuses on computer vision, artificial intelligence, and their applications in autonomous systems, driver assistance, and industrial vision. He leads projects like AI Color Fashion and Real-world adaption of generative AI for architecture. Møgelmose teaches introductory programming, computer vision, and advanced master's courses, emphasizing practical project-based learning. His work includes developing datasets such as the Multi-view Traffic Intersection Dataset (MTID) and exploring vision-language models for autonomous vehicle safety. He actively engages in media discussions on AI ethics and societal impacts. Research interests span dynamic gesture interpretation for cooperative autonomous vehicles, surgical skill assessment via automated metrics, and multimodal classification of environmental data. He has contributed to over 50 publications, including work on 3D object detection frameworks and generative AI education. Møgelmose collaborates on projects funded by industry partners like COWI and Danish government initiatives. His teaching philosophy centers on blended learning and practical application, fostering innovation in AI and computer vision education. Notable projects include AI:Xpertise Lab (2025–present), which explores AI-driven expertise systems, and collaborations on forest biodiversity analysis using LiDAR and orthophotos. His recent media engagements highlight societal AI challenges, emphasizing responsible implementation in public sectors.

Djamila Ouelhadjمشاهده پروفایل

استاد

• Operational Research
• Mathematical Optimisation
• Meta-heuristics and Hyper-heuristics
• +۶ مورد دیگر

Professor Djamila Ouelhadj of the University of Portsmouth is a leading academic in Operational Research, affiliated with the School of Mathematics and Physics and Centre for Operational Research and Logistics . She serves as Course Leader for MSc Logistics and Supply Chain Management and contributes to EU-funded projects like SEABILLA and LEANWIND . Her work spans mathematical optimization, meta-heuristics, and decision support systems applied to logistics, transportation, healthcare, and renewable energy. Research Themes : Operational Research, Logistics Analytics, AI for Decision Making, Sustainable Transportation Her recent publications focus on Mobility-as-a-Service (MaaS) systems, drone scheduling for wind farm inspection, and multi-criteria frameworks for inclusive transport. Articles highlight integration of machine learning , stochastic modeling , and robotics in solving real-world optimization problems. She employs multi-objective methods , simheuristics , and clustering techniques to address challenges in renewable energy, urban mobility, and security. Scientific Contributions include: Co-investigator on EU grants for maritime security and wind farm optimization Principal investigator for HEIF-funded Operational Research Centre Chair of scheduling streams at OR53-OR55 conferences Her advising extends to 15 theses, covering topics from nurse rostering to carbon footprint reduction. Collaborative grants include TSB and EU Horizon 2020 projects. She actively contributes to European Journal of Operational Research and leads the Logistics and Operational Research Group (LORG) in developing intelligent decision support systems for complex scheduling problems.

• Information Systems
• Digital Technologies and Migration
• ICT for Development (ICT4D)
• +۴ مورد دیگر

G Hari Harindranath is a Professor in the Department of Information and Operations Management at the School of Business and Management, Royal Holloway, University of London. He is also affiliated with the Centre for Critical and Historical Research on Organisation and Society. With over 86 research outputs, 11 projects, and 91 professional activities documented, Professor Harindranath maintains an active research profile with publications spanning from 2009 to 2025. His research interests focus on the intersection of digital technologies, migration, and development, with particular attention to how information systems affect vulnerable populations, social movements, and small and medium enterprises. His work adopts a critical perspective on technology, emphasizing responsible design and implementation that addresses real-world challenges rather than technological solutionism. Professor Harindranath's recent publications (2021-2025) demonstrate a clear thematic progression toward examining digital interventions for migrant communities, the impact of digital labor platforms, and responsible technology design for vulnerable groups. His work consistently emphasizes co-creation with end users and critical examination of technology's role in migration contexts, moving beyond simplistic 'app-based' solutions to address deeper structural issues. Scientific Recognition: Multiple best paper awards including for research on social media platforms and Egypt's social movements (2016) Best Paper Finalist for work on virtual classrooms during COVID-19 (2021) Highly Commended Award Winner at the 2013 Emerald Literati Network Awards 16 documented prizes reflecting consistent scholarly impact Professor Harindranath has supervised 6 students and maintains active collaborations, particularly with Tim Unwin and other researchers in the migration and technology space. His work bridges academic research with practical policy implications, as evidenced by publications in policy-oriented outlets like those from UNRISD and the ICT4D Collective. He has contributed significantly to understanding how digital technologies can be designed and implemented responsibly in migration contexts and for vulnerable populations.

Hande Demirelمشاهده پروفایل

استاد

• GIS
• Remote Sensing
• Photogrammetry
• +۷ مورد دیگر

Prof. Hande Demirel is a Professor at the Department of Geomatics Engineering, Istanbul Technical University. She holds a PhD in Geoinformatics from Technical University of Berlin (2002). Her academic career includes roles as Associate Professor (2008–2019) and Assistant Professor (2004–2008) at ITU, alongside research at the European Commission Joint Research Center (2011–2014). She specializes in GIS applications, remote sensing, photogrammetry, and spatial data analysis. Education: B.Sc. (1996) and M.Sc. (1998) in Geodesy & Photogrammetry from ITU, followed by a PhD in Geoinformatics (2002) from TU Berlin. Awards include Best PhD Award (2003), DAAD Scholarship (2007), and Best Poster Award (2016). Research focuses on transportation accessibility, climate change impacts, 3D spatial modeling, and BIM-GIS integration. She leads projects like 'Building Information Model Based Fire Evacuation Simulation' (TUBITAK-funded) and 'Spatio-Temporal Accessibility Analysis in Istanbul'. Key contributions include over 30 peer-reviewed publications, including works on land use prediction, ship detection via AI, and indoor navigation systems. She advises numerous graduate students, with 15+ theses supervised since 2009. Active in professional societies including the German and American Associations for Remote Sensing.

Xiaohui Qiمشاهده پروفایل

استادیار

• Geotechnical Engineering
• Risk and Reliability Analysis
• Probabilistic Site Investigations
• +۳ مورد دیگر

Dr. Xiaohui Qi is an Assistant Professor in the Department of Mechanical and Construction Engineering at Northumbria University since 2020. His research focuses on reliability analysis of geotechnical structures, probabilistic site investigations, and data-driven methods for predicting geotechnical and geological properties. Prior affiliations include postdoctoral roles at Nanyang Technological University (2017-2020) and the University of Macau (2015-2017), alongside a PhD from Wuhan University (2015) and an exchange at the National University of Singapore (2012-2015). His work addresses uncertainty in geotechnical engineering through Bayesian back-analysis, spatial variability characterization, and AI-driven predictive modeling. Key interests include slope stability, braced excavations, and soil parameter estimation using limited data. Recent research trends emphasize integrating machine learning (e.g., Bayesian methods, generalized additive models) with geostatistical techniques for 3D site reconstruction and geological interface prediction. His studies often compare methodologies (e.g., coupled Markov chains vs. stochastic simulations) to optimize spatial prediction accuracy. Collaborations span institutions in Singapore, China, and elsewhere, with a focus on applications like subway construction and foundation design uncertainties. No scientific awards are listed, but his 1625 citations highlight impactful contributions to geotechnical reliability and data analytics.

J.A. (Anne) Beaulieuمشاهده پروفایل

دانشیار

• Knowledge Infrastructures
• Data Ethics
• Climate Change
• +۳ مورد دیگر

Professor Anne Beaulieu is an Associate Professor and holder of the Aletta Jacobs Chair in Knowledge Infrastructures at the University of Groningen’s Campus Fryslân. She leads the Data Research Centre and teaches in programs like Energy, Environment, and Climate. Her research focuses on how data infrastructures shape knowledge production and societal futures, emphasizing ethics, sustainability, and epistemic diversity. Key roles include Director of Knowledge Infrastructures, National Coordinator for STS PhD training, and Editorial Board member for the Liveable Futures Series. She has developed initiatives like the Data Wise minor and co-founded the Groningen Energy Summer School. Her research explores climate data ethics, biodiversity conservation, and responsible innovation. Notable awards include Council of Europe recognition for academic integrity education and a 2023-2024 IAS Fellowship. She advises numerous PhD students and actively contributes to interdisciplinary projects addressing global challenges like soil health and agricultural sustainability.

• Medical Imaging
• Computer Vision
• Deep Learning
• +۴ مورد دیگر

Dr Abdullah Nazib is a Research Fellow at Queensland University of Technology (QUT) in the Faculty of Engineering, School of Electrical Engineering & Robotics. His research focuses on applying advanced computational techniques to medical imaging challenges, particularly in cancer detection and treatment planning. His research interests include: Medical image registration and segmentation Deep learning architectures for healthcare applications 3D medical image analysis Prostate cancer detection and grading Organ segmentation for radiation therapy Radiomics-based diagnostic systems Analysis of Dr Nazib's publication history reveals a clear evolution from general computer vision research toward specialized medical applications. His recent work demonstrates significant contributions to uncertainty quantification in medical image segmentation and multimodal learning approaches for diagnostic imaging. The 2024 publications particularly highlight his focus on clinically relevant applications with immediate potential impact on cancer diagnosis and treatment planning. His collaborative research network includes strong partnerships with Dr Fookes, Dr Perrin, and other members of QUT's biomedical imaging group, reflecting an interdisciplinary approach that bridges computer science, engineering, and clinical medicine to develop practical AI solutions for healthcare challenges.

• Urban Climatology
• Environmental Geosciences
• Remote Sensing
• +۴ مورد دیگر

Dr. Carlos Bartesaghi Koc is a Senior Lecturer at the University of Adelaide's School of Architecture and Civil Engineering, within the Department of Architecture and Landscape Architecture. His research focuses on urban climatology, environmental geosciences, and the application of computational technologies like AI and IoT in design. He holds a PhD in Planning and Urban Development from UNSW (2018), recognized with the Dean's Award for Outstanding PhD Theses (2019). Prior to his current role, he held positions at UNSW as a sessional lecturer and at Deakin University as a lecturer in Architecture. His work bridges academia, policy, and industry, influencing urban planning decisions through remote sensing and predictive modeling. He is eligible to co-supervise Masters and PhD students. Research Interests: Urban microclimate analysis using remote sensing and spatial data science Climate-sensitive design supported by AI and IoT Green infrastructure typologies and their thermal impacts Policy-driven urban heat mitigation strategies Impact & Engagement: His research has been integrated into national and international policy documents, toolkits, and industry reports. He actively collaborates with governments and organizations to improve urban planning decisions. His outputs include a public profile with links to his academic website, YouTube channel, and Sketchfab site. Grants & Supervision: Eligible to supervise in Architecture and Environmental Design Focus on Masters/PhD co-supervision

• Artificial Intelligence
• Data Science
• Operations Research
• +۷ مورد دیگر

Wang Hai is an Associate Professor at the School of Computing and Information Systems (SCIS) at Singapore Management University (SMU) and a Visiting Professor at Carnegie Mellon University's Heinz College. His research focuses on data-driven optimization, smart cities, and transportation systems. He holds a PhD in Operations Research from MIT (2015). He has received multiple accolades, including being named a World's Top 1% Scientist (2024), Best Paper Awards in transportation science, and Singapore's Lee Kong Chian Fellowship. His work spans over 50 peer-reviewed articles in journals like Transportation Research Part B , Manufacturing and Service Operations Management , and Transportation Science . Wang has led significant grants totaling over $5M, including projects on AI-driven resource optimization and urban logistics sustainability. He advises students like YANG Jingfeng and Rajiv Ranjan KUMAR. His teaching includes courses on Smart City Operations Research (7.00/7.00 student evaluations) and Decision Making Under Uncertainty. He serves as an Associate Editor for Transportation Science , IISE Transactions , and Service Science . His research bridges urban systems, operations research, and policy, with industry collaborations at Meituan, Didi Chuxing, and Changi Airport Group.

Cihan H. Dagliمشاهده پروفایل

استاد

• Systems Engineering
• Cyber-Physical Systems
• Machine Learning
• +۷ مورد دیگر

Cihan H. Dagli is a Professor of Systems Engineering and Engineering Management at Missouri University of Science and Technology (Missouri S&T). He is the founder of the Systems Engineering Graduate Program at Missouri S&T and directs the Smart Engineering Systems Lab (SESL). He serves as a Senior Investigator in the DoD Systems Engineering Research Center-URAC. His academic journey includes a Ph.D. in Applied Operations Research from the University of Birmingham (UK), with early work on water resource systems and evolving into systems engineering, cyber-physical systems, and machine learning. Research interests span systems architecting, computational intelligence, and deep learning applications in complex systems such as transportation, energy, and healthcare. He has secured over $25 million in grants, including a $10M DoD grant for the Systems Engineering Research Center-UARC. With 450+ publications and an h-index of 31, he is a Fellow of INCOSE (2008), IIE (2009), and IFPR (2019). He chairs the Complex Adaptive Systems conference series and advises over 35 PhD students across Engineering Management, Computer Science, and Systems Engineering. Recent work focuses on AI-driven kidney transplant optimization, meta-architectures for cyber-physical systems, and system-of-systems resilience. His educational contributions include developing the SEEE portal for systems engineering education and pioneering courses like Advanced Neural Networks and Complex System Modeling. Education: Ph.D., Applied Operations Research, University of Birmingham, UK (1979) Key Roles: Director of SESL, INCOSE Fellow, Omega Alpha Society Board Chairman Scientific Awards: Fellow of INCOSE (2008) Fellow of IIE (2009) Fellow of IFPR (2019) Member of Omega Alpha Association (2013) Advising and Grants: Advised 26 Engineering Management, 1 Computer Science, and 9 Systems Engineering PhD students Total grants: $25M+ from federal, industrial, and academic sources Labs/Teams: Smart Engineering Systems Lab (SESL) DoD Systems Engineering Research Center-URAC Complex Adaptive Systems conference organizer

János Kertészمشاهده پروفایل

استاد

• Network Science
• Computational Social Science
• Econophysics
• +۷ مورد دیگر

János Kertész is a Professor and Head of the Department of Network and Data Science at the Central European University (CEU), currently based in Vienna. He is also an elected member of the Hungarian Academy of Sciences. Previously, he held professorial and research positions at the Budapest University of Technology and Economics and the Hungarian Academy of Sciences, where he served as Director of the Institute of Physics. His research lies at the intersection of statistical physics and social sciences, with major contributions to network science, econophysics, computational social science, and algorithmic fairness. He investigates systemic risks in economic networks, opinion dynamics in algorithmically biased environments, poverty mapping using big data, and the role of automation in online extremism. The most recent articles highlight a strong trend in applying complex systems methodologies to real-world socioeconomic problems—particularly through large-scale network analysis, multimodal data integration, and policy-relevant modeling in inequality, supply chains, and digital fairness. His collaborative work spans institutions like the Complexity Science Hub (CSH) in Vienna. Elected member of the Hungarian Academy of Sciences He has advised numerous researchers and contributed to major interdisciplinary grants, particularly in complexity science and data-driven social science. His leadership in organizing NetSci 2023, the largest network science conference, underscores his role in fostering global scientific collaboration. He is central to projects involving high-resolution poverty mapping, economic systemic risk, and ethical AI applications. He is actively involved with the Complexity Science Hub (CSH), where CEU is a partner institution, and contributes to interdisciplinary teams working on economic modeling, social network analysis, and crisis preparedness using granular supply chain and VAT data.

• Statistical Learning
• High-Dimensional Data Analysis
• Network Statistics
• +۷ مورد دیگر

Charles Bouveyron is a Full Professor of Statistics at Université Côte d'Azur , Nice, France, and holds a Chair in Artificial Intelligence. He serves as Director of the Institut 3IA Côte d’Azur and leads the Inria research team MAASAI on Statistical Learning and Artificial Intelligence. He is an associate editor for The Annals of Applied Statistics and founded the Statlearn workshops . Research Interests: Statistical learning in high dimensions Learning on networks and functional data Deep latent variable models Adaptive learning with uncertain labels Applications in Medicine, Image Analysis, Astrophysics, and Humanities Notable Contributions: Developed multiple R packages including HDclassif , FisherEM , and FunLBM . Created the Linkage.fr platform for network analysis with textual edges. PhD Students: Current: Seydina Niang (Deep Generative Models), Kilian Burgi (Marine Diversity Monitoring), Baptiste Pouthier (Multimodal Learning) Former: Giulia Marchello (Dynamic Networks), Rémi Boutin (Network Analysis), Dingge Liang (Recommender Systems), Nicolas Jouvin (Latent Variable Models), Alexandre Saint-Dizier (Image Aggregation), Warith Harchaoui (Optimal Transport), Pierre-Alexandre Mattei (Sparse Clustering), Rawya Zreik (Temporal Networks), Anastasios Bellas (Anomaly Detection), Camille Brunet (Sparse Clustering) Contact: Email: charles.bouveyron@univ-cotedazur.fr / charles.bouveyron@inria.fr Postal: Equipe Maasai, Inria Sophia Antipolis, 2004 route des Lucioles, 06902 France

• Computer Science
• Machine Learning
• IoT
• +۷ مورد دیگر

Ali Hassan is a researcher affiliated with the National University of Sciences and Technology (NUST), School of Electrical Engineering and Computer Science, Department of Computer and Software Engineering. His work spans multiple domains in computer science, engineering, and applied mathematics, focusing on areas such as machine learning, IoT, energy systems, and medical informatics. His research explores: Reinforcement learning applications for battlefield information systems IoT antenna design and performance evaluation Optimization of second-life battery systems in electric vehicles Transformers for real-time vehicle collision avoidance Image hashing techniques using visual attention models Neural network-based phasor estimation for power grids Biomedical sensor systems for non-invasive health monitoring Mathematical modeling of viral dynamics Recent publications demonstrate his emphasis on interdisciplinary approaches combining AI, signal processing, and sustainability. He has collaborated with institutions across Pakistan, France, Saudi Arabia, and the USA, with a focus on practical implementations in cybersecurity, energy optimization, and healthcare technology.

Ganesh Neelakanta Iyerمشاهده پروفایل

مدرس

• Software Engineering
• Agile Software Development
• Cloud Computing
• +۱۳ مورد دیگر

Ganesh Neelakanta Iyer is a Lecturer in the Department of Computer Science at the School of Computing, National University of Singapore (NUS). He holds a PhD (2012) and MSc (2008) from NUS and a B.Tech. in Computer Science and Engineering from Mahatma Gandhi University, India (2004), where he ranked first. He brings over a decade of industry experience from companies like Salesforce, NXP, and Progress Software, and prior academic roles at Amrita Vishwa Vidyapeetham and IIIT-Hyderabad. His research interests span Software Engineering , Cloud/Edge Computing , Machine Learning , AI for Cultural Heritage , and Software Engineering Education . He founded the STeAdS (Software Engineering and Technological Advancements for Society) research group in 2021, focusing on technology applications in healthcare, education, and traditional arts like Kathakali and Wayang Kulit. The recent publications highlight a strong trend in AI-driven educational technologies , including LLMs for curriculum customization, web-based DevOps learning platforms, and agile project management tools. Another major theme is AI in cultural preservation , with works on Kathakali gesture and facial expression recognition. A third stream involves distributed systems and networking , particularly in edge computing and federated learning. Faculty Teaching Excellence Award 2024, NUS AWS Educate Cloud Faculty Ambassador (2019, 2020) Certified Kubernetes Administrator (CKA) University Topper (First Rank, 2004) NUS Postgraduate Research Scholarship (2009–2012) Dr. Iyer mentors students through UROP, FYP, Master’s, and PhD projects, and has led numerous grants and initiatives in cloud computing education and AI for societal benefit. He has delivered workshops and keynote speeches across the USA, Europe, Australia, and Asia. He actively leads the STeAdS virtual research group, fostering global collaborations. As a maestro in Kathakali, he integrates traditional art with technology, composing and staging performances while applying AI to preserve and analyze this heritage.

Edzordzi Agbozoمشاهده پروفایل

استاد

• Technical and Professional Communication
• Rhetoric of Health and Medicine
• Digital and Visual Rhetoric
• +۴ مورد دیگر

Edzordzi Agbozo is a faculty member at the University of North Carolina Wilmington , with research expertise in technical and professional communication, rhetoric of health and medicine, digital and visual rhetoric, and applied linguistics. His work bridges technoculture, critical discourse studies, and transnational technology analysis. Research Interests: Technology development, localization, and user experience Health crisis communication and medical colonialism Digital rhetoric and visual engagement Language policy and translanguaging in education Decolonial approaches to technical communication Publications: 15+ peer-reviewed works on AI archives, pandemic mHealth design, cultural translation, and Ghanaian digital infrastructure Recent book chapters in Routledge and Palgrave on social justice, multimodal analysis, and pandemic communication Teaching: Technical communication, science writing, digital rhetoric, and technology-society intersections Contact: Email: agbozog@uncw.edu