جست‌وجوی استاد و پژوهشگر

• Urban Sustainability
• Climate Action
• Urban Resilience
• +۶ مورد دیگر

Professor Joao Porto de Albuquerque is a Professor in Urban Analytics at the University of Glasgow's School of Social and Political Sciences, serving as Deputy Director of the Urban Big Data Centre (UBDC). He holds affiliate roles at the Centre for Research & Development in Adult and Lifelong Learning (CR&DALL) and previously led the Institute for Global Sustainable Development at the University of Warwick. His interdisciplinary work bridges geography and computer science, focusing on urban sustainability, participatory data methods, and addressing global inequities through community-driven approaches. Education: PhD in Computer Science (University of Campinas, 2006), postdoctoral research at University of Hamburg (2006-2008), and prior academic roles at University of São Paulo and Heidelberg University. Research emphasizes participatory urban analytics, citizen science, and AI ethics in disaster resilience, funded by major grants (e.g., £5.5M+ as PI from ESRC, Gates Foundation). Research interests include urban resilience, climate adaptation, participatory GIS, and data equity in marginalized communities. Notable projects include the Waterproofing Data Project (flood resilience in Brazil), IDEAMAPS (deprivation mapping in Africa), and co-creation of Earth-observation AI systems for slum areas. Publications span over 120 peer-reviewed articles, focusing on spatial data analysis, participatory methods, and urban sustainability. Awards include the ESRC Impact Prize for societal contributions to flood resilience. Active in global collaborations, his work integrates social sciences with environmental and technical disciplines.

• Artificial Intelligence
• Recommender Systems
• Information Systems
• +۲ مورد دیگر

Dietmar Jannach is a Full Professor at the University of Klagenfurt, Austria, affiliated with the Institute for Artificial Intelligence and Cybersecurity where he leads the Research Group for Information Systems. His academic roles include membership in the university's Senate and Curricular Commissions for Liberal Arts and Information Management. His research spans: Core Areas : Artificial Intelligence, Recommender Systems, and Software Engineering. Methodological Focus : Algorithm reproducibility, fairness in AI, sequential recommendations, and hybrid learning models. Emerging Interests : Generative AI for group decision support, ethical recommender systems, and foundation model applications. Jannach's recent publications critically evaluate reproducibility challenges in AI research, advocate for calibrated recommendations to mitigate bias, and explore agentic paradigms in group recommender systems. He emphasizes real-world validation, with studies on deployment challenges and developer experiences in software processes. He actively contributes to academic governance and mentors through research groups, though specific student advisees are not listed. Contact via Dietmar.Jannach@aau.at .

• Computer Vision
• Machine Learning
• Deep Learning
• +۳ مورد دیگر

Prof. Margret Keuper is a Professor in the Department of Computer Vision and Machine Learning at the Max Planck Institute for Informatics. Her research focuses on advancing machine learning and computer vision techniques, with an emphasis on model fairness, adversarial robustness, and multimodal interactions. She leads interdisciplinary projects exploring topics such as dataset analysis, generative models, and climate action through visual narrative analysis. Research Interests: Her work bridges theoretical foundations and practical applications in domains like adversarial training, image classification robustness, and robotics perception. She explores how vision-language models can be steered to align with human biases and develops methods for data-efficient learning and interpretability. Recent Contributions: Recent work includes FAIR-TAT (model fairness via adversarial training), VSTAR (video synthesis), and TikZero (zero-shot graphics program generation). Her publications in top venues like CVPR, ICCV, and ICLR highlight contributions to both methodological innovation and real-world impact. Collaborations: Works closely with researchers across Max Planck and academic partners, focusing on projects such as sensor layout optimization, climate discourse analysis via social media imagery, and domain-aware foundation model fine-tuning.

Aaron Whiteمشاهده پروفایل

استادیار

• Architecture
• Architectural History
• Art History
• +۶ مورد دیگر

Aaron White serves as an Assistant Professor in the School of Architecture at Mississippi State University, where he contributes to both architectural education and research in architectural history. His work bridges historical scholarship with contemporary critical examinations of race, empire, and cultural identity in the built environment. White's educational background provides a strong foundation for his interdisciplinary approach: PhD in Architectural History and Theory from Columbia University MA in Architecture from Pratt Institute BA in Architecture from the University of Idaho His research focuses on the complex relations between classicism and colonization in late-sixteenth and early-seventeenth century English architecture. White examines how architectural forms and practices functioned within imperial frameworks, particularly exploring connections between built environments and racial constructions. His work on whiteness in early modern architecture represents a significant contribution to expanding architectural history to address racial formations in premodern contexts, as evidenced by his 2025 edited volume "Early Modern Architecture and Whiteness" published by Routledge. White's publication record reveals an evolving scholarly trajectory that increasingly engages with critical race theory while maintaining connections to his foundational interests in classicism and colonialism. His most recent works demonstrate sophisticated analysis of how architectural spaces participated in the construction of racial identities, particularly whiteness, in early modern England. The 2025 Routledge volume represents a major scholarly intervention that reframes architectural history through the lens of race studies, examining how premodern architecture contributed to racial hierarchies and power structures. White has presented his research extensively at major academic conferences including the Society of Architectural Historians annual meetings, Association of Collegiate Schools of Architecture conferences, and specialized forums such as the Southeast Society of Architectural Historians. His presentations demonstrate engagement with both architectural history specialists and broader scholarly communities interested in race, empire, and cultural studies. As an educator, White has developed innovative approaches to architectural history pedagogy, as evidenced by his 2025 work on integrating AI into architectural history courses. His teaching likely emphasizes critical perspectives that connect historical architectural practices to contemporary issues of race, representation, and social justice in the built environment. He is affiliated with research centers at Mississippi State University including the Fred Carl, Jr. Small Town Center and the Gulf Coast Community Design Studio, suggesting connections between his historical scholarship and community-focused architectural practice.

Martin Wynnمشاهده پروفایل

دانشیار

• Digitalisation
• Digital Transformation
• Emerging Technologies
• +۴ مورد دیگر

Martin Wynn is an Associate Professor of Information Technology at the University of Gloucestershire's School of Computing and Engineering. With 20 years of industry experience as an IT professional and senior manager at Glaxo Pharmaceuticals and HP Bulmer Drinks, he transitioned to academia with a focus on knowledge transfer partnerships and post-doctoral supervision. His research interests span digital transformation, emerging technologies, sustainability, IT strategy, and risk management. He holds a PhD in Town and Country Planning and a PGCFHE in Education. Education: BA (Hons) Geography (Durham, 1973), MA Geography (Durham, 1977), PhD Town and Country Planning (Nottingham Trent, 1981), PGCFHE Education (Gloucestershire, 2003). Research focuses on leveraging technology for sustainable development, including digitalisation in manufacturing, cybersecurity, and the interplay between technology and urban planning. Over 20 doctoral students have been supervised in areas like digitalisation, analytics, and sustainability. Publications span e-business adoption in developing countries, ERP systems in SMEs, and ICT utilization in Libyan universities. He is a PRINCE2 Practitioner and Certified Management Consultant (CMC).

Lenka Zdeborováمشاهده پروفایل

دانشیار

• Statistical Physics
• Machine Learning
• Computational Biology
• +۳ مورد دیگر

Lenka Zdeborová is an Associate Professor at EPFL, jointly affiliated with the School of Basic Sciences and School of Computer and Communication Sciences. She leads the Laboratory of Statistical Physics of Computational Systems, where her research bridges statistical physics, machine learning, and computational biology. Education: PhD in Physics, Université Paris-Cité (2012) MSc in Fundamental Physics, École Normale Supérieure (2009) BSc in Physics, École Normale Supérieure de Lyon (2007) Her work focuses on phase transitions in learning algorithms, high-dimensional statistics, and neural network theory. Current projects investigate fundamental limits of machine learning, dynamics of graph neural networks, and applications to biological systems. Recent publications explore attention mechanisms in transformers, neural network depth advantages, and Bayes-optimal learning. Methodological innovations include cavity methods for hypergraphs and analysis of high-dimensional inference problems. Supervises doctoral students researching statistical physics approaches to machine learning and optimization. Teaches graduate courses in data science and machine learning for physicists.

Dongmei Chenمشاهده پروفایل

استاد

• Geomatics
• Environmental Science
• GIS Applications
• +۴ مورد دیگر

Dr. Dongmei Chen is a Professor in the Department of Geography and Planning at Queen's University, affiliated with the Faculty of Arts and Science. She holds cross appointments in the School of Environmental Studies and the Beaty Water Research Centre. Her research focuses on understanding human-environment interactions through GIS and remote sensing, with specialties in land use modeling, climate change impacts, and spatial data analysis. Education: PhD in Geography (2001, San Diego State University/UCSB); M.Sc. in GIS/Remote Sensing (Chinese Academy of Sciences); B.Sc. in Geography (Peking University). Pre-Queen's career included work as a GIS product specialist at ESRI. Research interests include geomatics, environmental science, and applying machine learning to remote sensing challenges. Recent work addresses flood susceptibility modeling, urban sprawl analysis, and spatial-temporal disease risk. Her interdisciplinary approach bridges geospatial technologies with environmental and social science. Active in research centers like LaGISA, she explores topics like air pollution monitoring and spatial data privacy. Grants and advising are integral to her role, though specific details are not detailed here. Collaborations span global contexts, including Brazil, Thailand, and China.

Yalong Yangمشاهده پروفایل

استادیار

• Immersive Analytics
• Virtual Reality
• Data Visualization
• +۳ مورد دیگر

Yalong Yang is an Assistant Professor at the School of Interactive Computing at Georgia Institute of Technology. His research focuses on immersive analytics, virtual reality (VR), and augmented reality (AR) interfaces, with a particular emphasis on spatial interaction, hybrid user interfaces, and data visualization techniques. He explores how embodied interactions and immersive environments enhance understanding in domains like education, sports analytics, and collaborative decision-making. Key research themes include hybrid immersive systems (combining VR/AR with physical devices), asymmetric collaboration in mixed environments, and AI-driven tools for programming education. His work spans both theoretical frameworks and applied systems, such as SPHERE for scalable personalized feedback in coding classrooms and VizGroup for collaborative learning analytics. Yang’s recent publications highlight trends in spatial hybrid interfaces, navigation in immersive environments, and the integration of generative AI in educational technologies. His projects often involve evaluating interaction techniques (e.g., label placement in AR) and comparing performance across desktop and VR platforms. Notable contributions include the SportsXR initiative for immersive analytics in sports, and systems like CompositingVis for creating complex visualizations in 3D spaces. His work addresses challenges in situated analytics, wearable technologies for outdoor activities, and audience analysis in VR exhibitions.

Thomas Le Barbanchonمشاهده پروفایل

استاد

• Labor Economics
• Public Finance
• Econometrics
• +۵ مورد دیگر

Thomas Le Barbanchon is a Full Professor of Economics at Bocconi University since 2025 and holds the Rodolfo Debenedetti Chair in Labor Economics. He received his PhD from Ecole Polytechnique (CREST-ENSAE) in 2012 and has been affiliated with institutions like CEPR, CREST, J-PAL, LEAP, BIDSA, IGIER, IZA, and IFS. His research focuses on labor economics, particularly job search mechanisms, unemployment insurance effects, gender disparities, and labor market policy evaluation. Educational background: PhD in Economics (Ecole Polytechnique), MSc in Economics (Universitat Pompeu Fabra), Diplôme d'ingénieur statisticien-économiste (ENSAE), and Diplôme d'ingénieur (Ecole Polytechnique) Research highlights include: Quantifying the impact of unemployment insurance reforms in France Analyzing gender differences in job search behavior Studying the effectiveness of hiring credits during economic crises Investigating how traditional AI improves job matching Examining migrant-native job search segregation patterns Scientific contributions appear in top journals like American Economic Journal: Applied Economics , Quarterly Journal of Economics , and Review of Economic Studies . Awards include two ERC grants (2017 & 2024) and the Bocconi Impact Award (2022). He mentors PhD students in economics and labor policy, currently serves as Director of IGIER research center, and maintains active editorial roles at Review of Economic Studies and Journal of the European Economic Association .

Ritika Tiwariمشاهده پروفایل

مدرس ارشد

• Public Health
• Health Policy
• Health Economics
• +۳ مورد دیگر

Dr Ritika Tiwari is a Senior Lecturer in Public Health at the York St John University London Campus. She holds over 14 years of experience in public health across South Asia, Africa, and Europe, with prior affiliations to India’s National Health Mission, South Africa’s Stellenbosch University, and the UK’s University of Greenwich. At York St John, she serves as Semester Lead for the MSc Public Health program, leading modules on Health Economics and Public Health for an Ageing Population. Her research focuses on Human Resources for Health (HRH), emphasizing equitable health workforce distribution and universal health coverage. Key areas include geo-spatial inequities in healthcare access, workforce planning models, and policy interventions. Her work has contributed to South Africa’s 2030 HRH Strategy and analyses of dentist shortages, nephrologist deficits, and health workforce trends in India and South Africa. Publications span journals, policy reports (e.g., South African Health Reforms, 2022), and media features on oral health crises and health worker shortages. Dr Tiwari’s academic contributions bridge policy, education, and practice, aiming to strengthen health systems through evidence-based strategies.

• Oncology
• Digital Pathology
• Machine Learning in Healthcare
• +۳ مورد دیگر

Yalai Bai is a Research Scientist and Technical Director of Tissue Distribution and Analysis Service in the Pathology Department at Yale School of Medicine. She holds a PhD and MD from Peking University Health Science Center (1996 and 1990, respectively). Her research focuses on quantitative biomarker analysis, tumor immunology, and machine learning applications in pathology. Key projects include developing automated algorithms for tumor-infiltrating lymphocyte (TIL) scoring and standardizing Ki67 and HER2 expression measurements. She collaborates internationally on clinical trials, such as the EORTC 10994/BIG 1-00 breast cancer trial, and contributes to translational studies on cancer metastasis and therapeutic response prediction. Education : PhD in Pathology, Peking University Health Science Center (1996) MD, Peking University Health Science Center (1990) Labs/Teams : Rimm Lab (specializing in quantitative pathology and computational oncology) Tissue Procurement & Distribution team (supporting large-scale clinical studies) Her work bridges clinical pathology and computational methods, addressing challenges in reproducibility and standardization. Recent studies highlight spatial tumor-immune microenvironment analysis and AI-driven biomarker validation across breast, head & neck, and gynecologic cancers. Contributions also include optimizing pre-analytic variables for antigen stability and advancing open-source tools for TIL quantification in triple-negative breast cancer.

Tameka Samuels-Jonesمشاهده پروفایل

استادیار

• Environmental Policy
• Global South Development
• Regulatory Law
• +۴ مورد دیگر

Dr. Tameka Samuels-Jones is an Assistant Professor at York University's School of Administrative Studies and Co-Director of the Centre for Research on Latin America & the Caribbean (CERLAC). Her work focuses on environmental policy, regulatory law, and the impacts of Canadian extractivism in Latin America and the Caribbean. She holds a PhD in Criminology & Law from the University of Florida. Research interests include AI ethics in the Global South, Black Indigenous legal frameworks in the Caribbean, and environmental crime analysis. Her studies critically examine colonial legacies in environmental governance and advocate for inclusive policymaking in resource-rich regions. Notable publications address bauxite mining in Jamaica, carbon emissions at Canadian universities, and geospatial patterns of environmental harm in US territories. Dr. Samuels-Jones has been recognized with the Robbins-Ollivier Award for Equity Excellence from the Canada Research Chairs Program. Her interdisciplinary approach bridges criminology, sociology, and legal studies to address systemic inequities in global environmental policies. She co-leads CERLAC initiatives promoting Caribbean studies and sustainable development advocacy.

• Computational Neuroscience
• Machine Learning
• Artificial Intelligence
• +۵ مورد دیگر

Rui Ponte Costa is an Associate Professor at the University of Oxford's Department of Physiology, Anatomy & Genetics (DPAG). He leads the Neural & Machine Learning group, focusing on computational models of learning in the brain by integrating AI principles. His research emphasizes cortical circuits, neuromodulation, and subcortical regions to understand credit assignment mechanisms. He holds a PhD in Computational Neuroscience and Machine Learning from the University of Edinburgh and has held postdoctoral positions at the University of Oxford, University of Bern, and McGill University. His group's work bridges theoretical and experimental neuroscience, collaborating with institutions like MILA and Google DeepMind. Education: Bachelor's in Computer Science, University of Coimbra (Portugal) PhD in Computational Neuroscience, University of Edinburgh (UK) Research Interests: Neural mechanisms of learning and plasticity Machine learning inspired by biological systems Cerebro-cerebellar interactions Neuromodulatory systems' role in reinforcement learning Collaborators include Christopher Summerfield, Timothy Behrens, and Yarin Gal. His lab's work has been published in Nature Communications , Cell Reports , and top machine learning venues. He co-organizes the Oxford NeuroTheory Forum and has pioneered models explaining cortical dynamics in task acquisition and consolidation. Advising and Grants: No specific grants listed, but active in collaborative research networks. Advising focuses on PhD students in computational neuroscience and AI. Labs/Teams: Neural & Machine Learning Group at DPAG, part of Oxford's broader neuroscience and AI ecosystem.

Oluremi B. Ayokoمشاهده پروفایل

دانشیار

• Conflict Management
• Emotions
• Leadership
• +۸ مورد دیگر

Associate Professor Remi Ayoko (Oluremi B. Ayoko) is a Senior Fellow of the Higher Education Academy working in the Management Discipline at the UQ Business School, University of Queensland. With expertise in conflict management, emotions, leadership, and workplace physical environments, she leads the Next Generation of Workspaces Research Network and chairs the UQ Cultural Inclusion Council. PhD in Management from University of Queensland Senior Fellow - Higher Education Academy Her research explores how physical workspaces influence employee wellbeing, productivity, and organizational outcomes; conflict dynamics in diverse teams; and leadership practices in hybrid work environments. Current projects examine the intersection of AI surveillance, cybersecurity behaviors, and workspace design. Recent publications investigate territoriality in organizational change (2024), diversity-inclusion linkages (2023), open-plan office communication (2023), and noise reactions in modern workspaces (2023). Her work spans organizational behavior , leadership studies , and workplace ergonomics . Scientific contributions include: Australian Research Council Discovery Grant Co-editor of Handbook of Conflict Management Research and Organizational Behaviour and the Physical Environment of Work Editor-in-Chief of Journal of Management and Organization (2019-2021) Current editorial board member for International Journal of Conflict Management and Strategic Change Professional service includes convening research networks, chairing diversity councils, and presenting workplace environment insights through international media channels. She actively contributes to academic societies including the Academy of Management and Australian and New Zealand Academy of Management.

Mustafa Hajijمشاهده پروفایل

استادیار

• Topological Deep Learning
• Graph Neural Networks
• Computational Topology
• +۲ مورد دیگر

Mustafa Hajij is an Assistant Professor in the Data Science program at the University of San Francisco. He holds a PhD in Mathematics from Louisiana State University, an MS in Computer Science, and completed postdoctoral training at University of South Florida and Ohio State University. Previously, he served as Assistant Professor at Santa Clara University and as an AI Research Scientist at KLA Corporation. His research develops foundational frameworks for topological deep learning, including cell complex neural networks and geometric learning architectures that operate beyond graph domains. He leads the NSF-funded project 'A Unifying Deep Learning Framework Using Cell Complex Neural Networks' (DMS-2134231, $547,626). Recent publications establish new paradigms for topological representation learning, including combinatorial complexes and simplicial networks, with applications in computational biology, 3D vision, and drug discovery. He organized the ICML Topological Deep Learning Challenges and develops open-source tools like TopoX for topological learning.