جست‌وجوی استاد و پژوهشگر

Adel Abusittaمشاهده پروفایل

استادیار

• Cybersecurity
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Dr. Adel Abusitta is an Assistant Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal, where he conducts research at the intersection of artificial intelligence and cybersecurity. With expertise in secure and resilient AI systems, IoT security, and malware analysis, Dr. Abusitta has established himself as a significant contributor to the field of AI-powered cybersecurity solutions. Education: PhD in Computer Engineering from Polytechnique Montréal Postdoctoral Fellow at University of Montréal Postdoctoral Fellow at McGill University Dr. Abusitta's research focuses on developing secure and trustworthy artificial intelligence systems with applications in cybersecurity. His work spans several critical areas including explainable AI for security applications, AI-powered malware analysis, intrusion detection systems, and IoT security. He has made significant contributions to the understanding of how AI can be both secured against attacks and used to enhance security systems. His research addresses the dual challenge of making AI systems resilient to adversarial manipulation while leveraging AI's capabilities to detect and prevent cyber threats in complex environments like cloud computing and IoT networks. Analysis of Dr. Abusitta's recent publications reveals a strong focus on the intersection of AI and cybersecurity, particularly in developing robust anomaly detection systems, explainable security solutions, and resilient architectures for IoT environments. His work demonstrates a consistent trajectory toward making AI systems both more secure and more useful for security applications, with increasing emphasis on practical implementations that can withstand real-world challenges. Dr. Abusitta has collaborated extensively with Defence Research and Development Canada (DRDC) on projects related to AI-powered data analytics for discerning malware intent. He has also worked with industrial partners through the Institute for Data Valorization (IVADO) to develop privacy-preserving machine learning techniques that maintain accuracy while protecting sensitive information. His research has practical applications in critical infrastructure protection and secure AI deployment.

Robert Preyمشاهده پروفایل

دانشیار

• Digital Culture
• Platform Capitalism
• Music and Cultural Industries
• +۵ مورد دیگر

Dr. Robert Prey is an Associate Professor of Digital Culture at the Oxford Internet Institute (OII) and a Research Fellow at Green Templeton College, University of Oxford. His research focuses on the intersections of technology, capitalism, and culture, particularly examining algorithmic systems, datafication, and platformization's impact on cultural industries and creative labor. He leads the ERC-funded 'PlatforMuse' project (2023-2028), investigating how streaming platforms shape musicians' creative practices globally. Previously, he held positions at the University of Groningen and completed his PhD at Simon Fraser University. His work has been supported by grants from the Academy of Korean Studies, Brazil's National Council for Scientific and Technological Development, and the European Research Council. Education: PhD from Simon Fraser University (Canada), affiliated with the Transnational Culture and Digital Technology Lab. Current teaching includes a course on Digital Ethnography. Research interests span digital economy, cultural work, music industries, and critical theory. He actively collaborates on international projects, including algorithmic mediation studies in Brazil and platformization of music in Nigeria and South Korea. Key projects include analyzing musician adaptation to online platforms, voice biometrics' identity frameworks, and global platform models. His publications address algorithmic power dynamics, datafication in music, and the political economy of digital capitalism. He maintains affiliations with academic networks and serves as a doctoral supervisor on topics like platform capitalism and digital labor.

• Geographic Information Science (GIS)
• Spatial Analysis
• Public Health
• +۵ مورد دیگر

Dr. John Wilson is a Professor at the University of Southern California (USC), holding academic positions across multiple schools including Dornsife College of Letters, Arts and Sciences; Viterbi School of Engineering; Keck School of Medicine; and USC School of Architecture. He is the founding Director of the Spatial Sciences Institute and leads interdisciplinary research in spatial analytics, GIScience, and environmental health. His work integrates Geographic Information Systems (GIS), remote sensing, and spatial modeling to address challenges in community health, sustainability, and urban resilience. Dr. Wilson holds a PhD in Geography from the University of Toronto and advanced degrees from the University of Canterbury. His research emphasizes geodesign, digital terrain modeling, and the application of spatial technologies to public health and environmental science. He directs the Wilson Map Lab, which develops tools for healthier communities and resilient landscapes using BIM, GPS, and remote sensing technologies. His publications span GIScience, environmental health, and spatial data science, with over 130 articles and book chapters. Notable works include Environmental Applications of Digital Terrain Modeling and an upcoming book on spatial data science. He serves as Editor-in-Chief of Transactions in GIS and leads multiple research initiatives, including the Southern California Environmental Health Sciences Center and the Center for Knowledge-Powered Interdisciplinary Data Science. Recent research focuses on mobility patterns, PM2.5 exposure during pregnancy, and spatial equity in healthcare access. He has secured grants for sustainability solutions and collaborates internationally, including with the Chinese Academy of Sciences in Beijing.

• Leadership
• Organizational Behavior
• Educational Technologies
• +۴ مورد دیگر

Andrea North-Samardzic is an Honorary Associate Professor in the Faculty of Arts and Education at Deakin University, concurrently holding a Senior Lecturer position in the Department of Management at Deakin Business School. She earned her PhD in Organization & Management from the University of New South Wales (UNSW). Her research focuses on leadership dynamics, educational technologies, biometrics ethics, and organizational strategy, with notable projects involving government agencies like India’s Ministry of Human Development and industry partners such as the Reece Group. Her teaching expertise spans leadership, management, and organizational behavior, including designing innovative HRM simulations and online pedagogy strategies. She directs the Master of Business Administration (MBA) program and provides executive education to corporations and government delegations. Notable research contributions include studies on gender equity in academia, interorganizational collaboration, and biometric technology ethics. Andrea has secured significant research funding for projects addressing humanitarian leadership, cultural sector impacts, and educational technology applications. Her work bridges academic rigor with practical industry engagement, emphasizing ethical considerations in emerging technologies and leadership practices.

• Image and Video Processing
• Multimedia Analysis
• Computer Vision
• +۵ مورد دیگر

Prof. Tan Yap Peng is a Professor and Chair of the School of Electrical & Electronic Engineering at Nanyang Technological University (NTU), Singapore. He holds the President's Chair in Electrical and Electronic Engineering and serves as Associate Vice President (Lifelong Learning – Postgraduate Programmes by Coursework). His research focuses on multimedia analysis, computer vision, machine learning, and data analytics. He earned his B.S. from National Taiwan University and M.A./Ph.D. from Princeton University. He has led major initiatives including the INFINITUS Infocomm Research Centre and contributed to IEEE technical committees. His over 200 publications span image/video processing, neural network robustness, and cross-modal systems. Awards include IEEE Fellow status. Education: B.S. Electrical Engineering (NTU), M.A./Ph.D. (Princeton) Research interests emphasize interactive digital media, content-based analysis, and AI-driven solutions for visual and signal processing. His work addresses challenges in adversarial attacks, video generation, and low-light image enhancement. He has held editorial roles at IEEE Transactions and EURASIP journals. Conference leadership includes chairs for ICME and ICIP. His contributions bridge academia and industry through collaborative research networks.

Young Leeمشاهده پروفایل

مدرس ارشد

• Edge Computing
• Blockchain Technology
• Fog Computing
• +۳ مورد دیگر

Young Lee is a Senior Lecturer in Computing at Macquarie University, affiliated with the School of Computing and three research centers: Data Horizons Research Centre, Future Communications Research Centre, and Smart Green Cities Research Centre. His research focuses on edge computing, blockchain technology, fog computing, and resource scheduling in distributed systems, with a strong emphasis on applications in IoT, healthcare, and sustainability. He has led or contributed to over 150 research outputs since 2005, including influential works on edge-based video analytics, blockchain frameworks, and cloud-edge resource optimization. Dr. Lee's projects include 'Extreme-Scale Computing for Big Data Analytics' (2016–present) and 'Synergising the Power of the Cloud with the Power of the Crowd' (2016–present), demonstrating expertise in scalable computing and cloud-crowd integration. His work bridges theoretical advancements in scheduling algorithms with practical implementations in energy-efficient data centers and mobile edge environments. Research interests span edge computing architectures, blockchain oracles, and fog caching strategies, with recent contributions to carbon-conscious travel systems and malware detection frameworks. His interdisciplinary approach addresses challenges in resource allocation, network security, and distributed system efficiency.

• Spatial Planning
• Digitalization in Urban Governance
• Collaborative Planning
• +۹ مورد دیگر

Dr. Yanliu Lin is an Associate Professor in Spatial Planning and Digitalization at Utrecht University's Department of Human Geography and Spatial Planning. His research focuses on digital planning technologies, urban governance, and collaborative planning processes, particularly in China and the Netherlands. He leads an ERC-funded team exploring social media's role in collaborative planning and co-leads an AI-driven Digital Twin Platform project with partners from TU Eindhoven and Wageningen University. Key research areas include: Planning Support Systems and Smart Urban Governance Social Media's Impact on Public Participation Digital Twin Applications for Sustainable Development Migration and Urban Integration Ethical Dimensions of AI in Urban Planning His 60+ publications appear in top journals like Computers, Environment and Urban Systems and Urban Studies . He edited two books on smart governance and co-organized major conferences like the 2025 CUPUM workshop on Digital Planning. Awards include an ERC Starting Grant (2021-2026) for collaborative planning research. Professional Contributions: Serves on editorial boards for Planning Practice & Research and Urban Governance , reviews for 40+ ISI journals, and advises the Swiss National Science Foundation.

Daniel Mosseمشاهده پروفایل

استاد

• Computer Architecture
• Computer Systems
• Cyber-Physical Systems
• +۸ مورد دیگر

Dr. Daniel Mosse is a Professor in the Department of Computer Science at the University of Pittsburgh. He holds a PhD from the University of Maryland, College Park, and has been a faculty member since 1993. His research focuses on distributed systems, real-time systems, power management, security, and fault tolerance, bridging operating systems and networking research. He has held leadership roles, including Chair of the Department of Computer Science since 2009 and Visiting Professorships in Brazil. His work spans grants totaling millions, addressing energy-efficient computing, secure infrastructure, and embedded systems. Education: PhD (1993), MS (1990), and BS (1985) in Mathematics and Computer Science. Research interests include distributed real-time systems, multicore systems, embedded systems, and wireless networks. Notable awards include the 2007 Provost's Innovation in Education Award and the 2006 Bellet Teaching Award. Key grants include NSF-funded projects on energy-efficient data centers, secure emergency management systems, and power-aware scheduling. He advises numerous students and teaches courses on operating systems and distributed systems. His contributions to real-time systems, fault tolerance, and energy management have been recognized through over 150 publications and international collaborations.

Karen Butler-Purryمشاهده پروفایل

استاد

• Power System Automation
• Smart Grid Security
• Distribution Automation
• +۴ مورد دیگر

Karen Butler-Purry is a Professor of Electrical & Computer Engineering at Texas A&M University, holding the Raytheon Company Professorship. She is affiliated with the Power System Automation Laboratory and the College of Engineering. Her research focuses on intelligent systems for power distribution automation, fault diagnosis, and renewable energy integration. She completed her B.S. at Southern University (1985), M.S. at UT Austin (1987), and Ph.D. at Howard University (1994). Her work emphasizes cyber-physical systems, smart grid security, and microgrid resilience. Recent research includes AI-driven grid restoration, cybersecurity frameworks for distribution systems, and self-healing shipboard power systems. She has pioneered methods for transformer lifespan prediction and unbalanced load management in distributed networks. Publications span over three decades, with notable contributions to IEEE journals and conferences. Her educational initiatives include the Texas A&M System AGEP Alliance and LSAMP programs, advancing underrepresented minority participation in STEM academia. She leads interdisciplinary projects at the intersection of power systems, machine learning, and equity-focused academic workforce development. Labs/Teams: Principal Investigator in the Power System Automation Laboratory, collaborating with industry partners like Raytheon. Active in curriculum development for digital systems education through initiatives like the Enrichment Experiences in Engineering (E³) program.

• Machine Learning
• Climate Science
• Energy Systems
• +۳ مورد دیگر

Sancho Salcedo Sanz is a Full Professor at the Universidad de Alcalá, affiliated with the Signal Theory and Communications Department and the GHEODE Research Group. His work focuses on applying machine learning and optimization techniques to energy systems, climate science, and environmental modeling. He holds PhDs from Universidad Complutense de Madrid (2019) and Universidad Carlos III de Madrid (2002). Key research interests include deep learning for energy price prediction, spatio-temporal climate analysis, and hybrid models for renewable energy forecasting. His GHEODE group develops optimization algorithms for network design and distributed systems. Recent publications highlight advancements in extreme weather prediction, smart grid optimization, and explainable AI for environmental monitoring. He has pioneered methodologies like Autoencoder-based flow analogues for heatwave reconstruction and multi-method ensembles for energy demand modeling. Labs/Teams: Leader of the GHEODE Group, specializing in modern heuristics and network design. Collaborates extensively on interdisciplinary projects combining AI with environmental and engineering applications.

• Educational Technology
• Digital Competence in Education
• Digital Transformation in Higher Education
• +۷ مورد دیگر

Linda Castañeda is a Professor of Educational Technology in the Department of Didactics and School Organization at the Faculty of Education, University of Murcia, Spain. Born in Bogotá, Colombia, and based in Murcia, she holds a PhD in Educational Technology from the University of the Balearic Islands. She is a leading figure in digital transformation in higher education, coordinating major European projects such as CUTIE and DALI, and directing strategic research contracts with the European Union's Joint Research Center. Her research focuses on educational technology, digital leadership, AI in education, and digital literacy. She has conducted international research stays at prestigious institutions including the Open University (UK), University of Oxford, UC Berkeley, and UJI. She is actively involved in editorial roles for top journals such as the European Journal of Educational Technology in Higher Education , Journal of New Approaches in Educational Research , and Educational Technology Research & Development . Linda leads the development of open educational resources, such as the course Strategic Leadership for Digital Transformation in Universities , adapted for the Spanish context. Her recent work emphasizes integrating AI into pedagogical practices, rethinking student roles, and fostering critical engagement with technology. She is deeply committed to ethical, people-centered, and pedagogically grounded digital transformation in education. She has contributed to national and European frameworks, including the University Digital Teaching Competence Framework (MCDDU) and the UNIDIGITAL accreditation project. Her publications reflect a strong focus on institutional change, teacher development, data literacy, and open, collaborative knowledge creation. Member, Editorial Board – European Journal of Educational Technology in Higher Education Member, Editorial Board – Journal of New Approaches in Educational Research Member, Development Editorial Committee – Educational Technology Research & Development (ETR&D) Member, GITE – Interuniversity Journal of Research in Educational Technology Linda mentors students through innovative teaching methods involving AI-enhanced reflection, role-based learning, and collaborative blogging. She emphasizes metacognition, feedback integration, and digital fluency. Her projects involve cross-institutional collaboration across 35 Spanish universities and European partners, demonstrating her leadership in shaping the future of digital education. She maintains an active blog, Educational Mushware , where she reflects on ideas over tools—'MUSHWARE' being the conceptual and creative layer beyond hardware and software. Her vision is for education to be transformed not by technology alone, but by thoughtful, human-centered innovation.

Amelia Thorpeمشاهده پروفایل

استاد

• Urban governance
• Socio-legal studies
• Cities
• +۸ مورد دیگر

Professor Amelia Thorpe of the University of New South Wales School of Law specializes in planning, property and environmental law with a focus on mobility and urban governance. Her sociolegal approach integrates professional experience in public interest environmental law and planning, including acting as Commissioner in the Land and Environment Court of NSW and membership on the Independent Liquor and Gaming Authority. BEnvDes & BArch (Hons), University of Western Australia BPolSt (Hons), Murdoch University BA (Jurisprudence), Oxford LLM, Harvard Law School PhD, Australian National University Her research explores urban governance through projects like Owning the Street: The Everyday Life of Property (MIT Press, 2020) and current $2M+ in competitive funding including: Australian Research Council Linkage Project (2025-2028): Aboriginal-led pathways James Martin Institute Policy Challenge Grant (2023-2024): Data-driven mobility Reliable Affordable Clean Energy CRC (2020): EV infrastructure She has held visiting appointments at UC Berkeley, McGill, and Paris IAS. Her 12 PhD supervisees include: Matthew Idiculla (constitutional law) Amarnath Boopalam Manjunath (street vendors) Alice Palithorpe (climate displacement) Major awards include: Australian Legal Research Awards (2022) Legal Innovation Index winner (2016) Vice-Chancellor’s Teaching Excellence (2014)

• Occupational Safety and Health
• Construction Management
• Project Management
• +۷ مورد دیگر

Professor Patrick Manu is a faculty member at the University of the West of England (UWE Bristol), holding the position of Professor of Innovative Construction and Project Management within the School of Architecture and Environment. He specializes in construction management, project management, quantity surveying, and occupational safety and health. His research focuses on occupational health and safety, sustainable construction, digital construction technologies, and BIM integration. He has secured funding from EPSRC, DFID, and other institutions for projects like developing web-based safety tools and exploring immersive technologies for safety training. Patrick holds a PhD in Construction Project Management from the University of Wolverhampton, a BSc (First Class Honours) from Kwame Nkrumah University of Science and Technology, and a PGCert in Academic Practice from City University London. He is a Chartered Member of the Chartered Institute of Building and a Fellow of the UK Higher Education Academy. His research interests include BIM applications, Industry 4.0 technologies, circular economy in construction, and AI-driven safety solutions. He has published extensively on topics such as safety risk analysis, UAV applications, and pandemic-era construction safety. He serves as a reviewer for EPSRC, Newton Fund, and leading journals like Safety Science, and chairs committees for organizations like the International Construction Measurement Standards (ICMS). Patrick has held academic positions at institutions including The University of Manchester and KNUST, and his industry experience includes roles in quantity surveying and developing digital tools for construction cost estimation. He leads collaborative projects involving academia and industry partners, emphasizing practical solutions for construction challenges.

Yi Zhuمشاهده پروفایل

استاد

• Industrial Organization
• Quantitative Marketing
• Advertising
• +۷ مورد دیگر

Yi Zhu is a Professor of Marketing and holder of the Margaret J. Holden and Dorothy A. Werlich Endowed Professor at the Carlson School of Management, University of Minnesota . His work bridges Industrial Organization , Quantitative Marketing , and Chinese Economy with a focus on digital advertising, platform economics, and consumer search behavior. Education PhD in Business Administration, University of Southern California (2013) MA in Economics, University of British Columbia (2004) MA in Management, Shanghai Academy of Social Sciences (2002) BE in Industry Engineering, Shanghai University of Electric Power (1998) His research applies Industrial Organization to Marketing , examining online auctions , advertising mechanisms , media slant , and Chinese economic dynamics . Recently, he has explored two-sided platforms and surge pricing effects on consumer complaints. Publications span Marketing Science , Management Science , and Journal of Marketing Research , with work highlighted in Harvard Business Review and Forbes . His advertising research includes auction design, TV-to-online search interactions, and budget-constrained advertiser behavior. Scientific Awards Winner of John D.C. Little Award (2015) Winner of Don Morrison Long Term Impact Award (2023) 3M Nontenured Faculty Grant (2013-2016) Marketing Science Institute (MSI) Scholar (2022, 2023) Holds the Carlson School Outstanding Teaching Award (2022) and serves as Associate Editor for Marketing Science . Teaching includes Marketing Analytics for MBAs and Marketing Strategy for undergraduates, with consistently high instructor ratings. Referees for top journals like Management Science and Information Systems Research .

Dan Steinbergمشاهده پروفایل

عضو هیئت علمی

• Probabilistic Machine Learning
• Variational Inference
• Bayesian Deep Learning
• +۷ مورد دیگر

Dan Steinberg is a senior research scientist and team leader of the Decisions & Statistical Learning team at CSIRO Data61 in Canberra, Australia. His expertise lies in probabilistic machine learning, variational inference, Bayesian deep learning, causal inference, and their application to domains spanning synthetic biology, geospatial analytics, and algorithmic fairness. Education PhD in Computer Vision / Machine Learning (2013) – University of Sydney, Australian Centre for Field Robotics Bachelor of Engineering (Mechatronics, First-Class Honours) – University of Sydney (2008) Bachelor of Commerce (Finance) – University of Sydney (2008) Research Interests Steinberg’s core research agenda revolves around building scalable probabilistic models that can learn efficiently from limited or noisy data and provide principled uncertainty estimates. Key themes include: Variational Inference & Bayesian Deep Learning: developing lightweight yet powerful algorithms for approximate posterior inference in complex models (e.g., Aboleth, Revrand). Active Learning & Experimental Design: creating methods that decide which experiments or measurements will maximise information gain, with recent focus on in-silico protein engineering via Variational Search Distributions (VSD). Causal Inference: leveraging machine-learning tools to perform robust observational causal studies for evidence-based policy, including work on youth well-being and academic outcomes. Algorithmic Fairness: translating normative notions of equity into quantifiable objectives for regression-based decision systems. Large-scale Spatial Analytics: Landshark—an open-source TensorFlow toolkit for supervised learning on massive geospatial raster datasets. Notable Software & Tools Aboleth: A minimal-overhead TensorFlow framework for Bayesian deep learning. Landshark: Command-line tools for large-scale spatial inference. Revrand: Scalable Bayesian generalised linear models with non-conjugate likelihoods. libcluster: Extensible C++ library for hierarchical Bayesian clustering. Scientific Awards Oral Presentation Award – ICML 2025 Workshop on Scaling up Intervention Models (SIMS) Oral Presentation Award – NeurIPS 2024 Workshop on Bayesian Decision-making and Uncertainty (BDU) Oral Presentation Award – NeurIPS 2023 Workshop on Adaptive Experimental Design and Active Learning Spotlight Paper Award – NeurIPS 2014 (Extended and Unscented Gaussian Processes) Research Team & Collaborations As Team Leader – Decisions & Statistical Learning at CSIRO Data61, Steinberg directs a multi-disciplinary group that partners with government agencies (e.g., Jobs and Skills Australia, Australian Institute of Health and Welfare) and industry to deploy machine-learning solutions at scale. He has previously held roles as Principal Researcher at Gradient Institute (2019-2023), Senior Research Engineer at CSIRO Data61 (2016-2019), Researcher at NICTA (2013-2016), and Research Associate at the University of Sydney (2012-2013).