جست‌وجوی استاد و پژوهشگر

• Spatial Data Science
• Artificial Intelligence (AI)
• Geographic Information Science (GIScience)
• +۷ مورد دیگر

Krzysztof Janowicz is a Professor at the University of Vienna and Head of the Department of Geography and Regional Research. Previously, he held full professorships at the University of California, Santa Barbara (UCSB) and Pennsylvania State University. He directs the Research Network Data Science and is Editor-in-Chief of the Semantic Web journal. His research focuses on Spatial Data Science, GeoAI, and knowledge graphs, emphasizing the integration of semantic and data-driven approaches. Education includes a PhD in Geoinformatics from the University of Münster and postdoctoral work at the Institute for Geoinformatics. Teaching includes courses on spatial data science, cartography, and geoinformatics, such as field trips to Scotland and North America. He leads projects like the KnowWhereGraph, a large-scale geo-knowledge graph for interdisciplinary applications. His work addresses AI sustainability, geographic diversity evaluation, and privacy in geospatial AI. He has directed UCSB’s Center for Spatial Studies and contributed to disaster risk management frameworks through ontologies like HIP.

• Natural Language Understanding
• Natural Language Processing
• Machine Learning
• +۳ مورد دیگر

Dr. Prashant Khare is a Researcher at Queen Mary University of London's School of Electronic Engineering and Computer Science. His research focuses on Natural Language Understanding, Machine Learning, and Social Data Science, with applications to organizational communication, crisis information analysis, and internet standards. He has contributed to datasets like LEDA for decision dialogue analysis and explores linguistic markers of influence in online organizations. His work bridges computational methods with real-world challenges in communication and crisis management. Key research interests include dialogue modeling, NLP for organizational contexts, and cross-lingual crisis data classification. He has analyzed social graphs of technical communities like the IETF and studied the co-spread of misinformation during global health crises. His technical contributions span RFC errata analysis, decision detection algorithms, and semantic validity assessment in linked open data. Though no formal awards are listed, his publications reflect sustained engagement with interdisciplinary challenges at the intersection of computer science and social systems. His research often involves collaboration with industry and standards bodies, as seen in his work on RFC deployment and large-organization email analysis.

• Distributed Systems
• Cloud Computing
• High-Performance Computing
• +۳ مورد دیگر

Thilo Kielmann is an Associate Professor at the Vrije Universiteit Amsterdam, holding positions in the Faculty of Science (Computer Systems department) and the Network Institute. His research focuses on distributed systems, cloud computing, and high-performance computing, with emphasis on resource management, data locality, and scalable infrastructure. He has authored 95+ research outputs and supervised 8 PhD theses. Education details are not explicitly listed, but his academic role implies advanced qualifications in computer science. His work contributes to UN Sustainable Development Goals through innovative computing solutions. Research interests include distributed file systems (e.g., MemEFS), resource disaggregation, energy-efficient scheduling (e-BaTS), and scalable VM management. His publications span conferences like HPDC and journals like Future Generation Computer Systems. No scientific awards are explicitly mentioned. He teaches four courses, including Computer Programming and Large Research Project in Computer Science. Labs/teams involvement is not detailed, but his research collaborations and conference roles (e.g., HPDC15 Chair) suggest active participation in academic networks.

Jacopo Urbaniمشاهده پروفایل

دانشیار

• Knowledge Graphs
• Data Stream Reasoning
• Semantic Web
• +۴ مورد دیگر

Jacopo Urbani is an Associate Professor at Vrije Universiteit Amsterdam, affiliated with the Faculty of Science, Computer Systems department, and the Network Institute. His research focuses on Knowledge Graphs, Stream Reasoning, and Distributed Computing. He explores scalable reasoning techniques for large-scale datasets, integrating semantic technologies with real-time data processing. His work emphasizes practical applications of logic-based systems, including existential rules, probabilistic reasoning, and trigger graphs for efficient knowledge base materialization. Recent contributions address challenges in handling dynamic data streams and enhancing the scalability of semantic web technologies. Urbani has published extensively in top venues like the Semantic Web Conference (ESWC) and the International Conference on Principles of Knowledge Representation and Reasoning (KR). Notable projects include the VLog rule engine for knowledge graphs and the Tab2Know platform for extracting structured data from scientific tables. He supervises PhD theses in areas like stream reasoning and knowledge graph embeddings. His research also involves collaborative efforts with institutions worldwide, addressing topics such as data compression, distributed computing architectures, and hybrid reasoning systems.

Danlu Guoمشاهده پروفایل

مدرس ارشد

• Hydrology
• Environmental Engineering
• Water Quality Modelling
• +۴ مورد دیگر

Dr Danlu Guo is a Senior Lecturer at the School of Engineering, Australian National University (ANU), since December 2022. She holds a PhD in Hydrology from the University of Adelaide (2017) and has held roles including Research Associate at UNSW Sydney and the University of Melbourne, where she remains an Honorary Fellow. Her research focuses on hydrology and environmental engineering, emphasizing data-driven approaches for catchment water resources, including rainfall-runoff modelling, water quality trends, and climate change impacts. She has received prestigious awards such as the 2022 GN Alexander Medal and the 2019 MSSANZ Early Career Award. Dr Guo leads over $1M in Category 2 funding and contributes to ARC Linkage Projects. Her work bridges academic and applied sectors through roles as Guest Editor for the Journal of Hydrology , Chief Editor of the Australasia Journal of Water Resources , and Chair of MSSANZ's Water Quality Modelling SIG. Education Background: PhD in Hydrology (University of Adelaide, 2017); prior roles include Research Associate at UNSW Sydney (2016–2017) and University of Melbourne (2017–2022). Research Interests include river water quality dynamics, Bayesian modelling, large-sample hydrology, and irrigation efficiency. Her studies have revealed deteriorating water quality in the Great Barrier Reef region and recovery in the Murray-Darling Basin, as well as climate-driven shifts in streamflow and salinity. She develops frameworks for benchmarking irrigation performance using satellite and on-farm data. Grants and Projects: Lead CI for >$1M Category 2 funding; involved in ARC Linkage Projects. Current projects include improving water quality modelling via solute transport studies and enhancing irrigation benchmarking methodologies. Labs/Teams: Active in the Institute for Water Futures (ANU) and collaborates with the University of Melbourne's Infrastructure Engineering. Her research network spans hydrology, environmental engineering, and climate science communities.

• Internet of Things
• Smart Cities
• Digital Transformation
• +۷ مورد دیگر

Bocchi Yann serves as an Ordinary Professor at HES-SO Valais-Wallis' School of Management within the Economy and Services faculty. His primary appointment resides in the Computer Science Institute where he leads research in Internet of Things, Smart Cities, and Digital Transformation. His work bridges technical innovation with practical urban applications through multiple EU and Swiss-funded projects. His research focuses on IoT architecture design, context-aware systems, and human-centered smart environments. Key contributions include nomadic sensing platforms for cost-effective smart city implementation, geo-aware security protocols for cross-border data exchange, and semantic middleware for heterogeneous technology integration. His work demonstrates particular expertise in translating theoretical IoT concepts into deployable urban solutions through the SmartSantander testbed and other large-scale validations. His publication portfolio reveals consistent focus on IoT interoperability (2014-2017), evolving toward human-centric applications (2015-2016) and energy-aware systems (2020). The research trajectory shows progression from foundational protocol development toward practical smart city implementations with emphasis on data valorization and user experience. As principal investigator, he has secured significant research funding including 820,415 CHF for the EU IoT6 project and 50,000 CHF for GeoTrust from the Hasler Foundation. His collaborative approach spans academic institutions, Swiss cantons, and industry partners including Nokia Research Labs and PostAuto Schweiz AG. He directs the Management Information Technology program while teaching Systems Modeling in the BSc HES-SO in Management Information Systems. His industry partnerships demonstrate strong technology transfer capability, particularly in tourism management systems and cultural heritage applications.

Reza Zafaraniمشاهده پروفایل

دانشیار

• Big Data Analytics
• Data Mining
• Web Mining
• +۵ مورد دیگر

Reza Zafarani is an Associate Professor in the Department of Electrical Engineering and Computer Science at Syracuse University, where he directs the Data Lab. He holds a Ph.D. from Arizona State University. His research focuses on the intersection of data mining, machine learning, and social sciences, particularly in analyzing large-scale networks and social media data. Key areas of interest include big data analytics, social network analysis, and behavior modeling. He has authored influential works such as the textbook Social Media Mining: An Introduction (Cambridge University Press, 2014) and pioneered research in fake news detection, network robustness, and graph representation learning. Notable awards include the NSF CAREER Award (2020) and NVIDIA/Google education grants. His work spans theoretical advancements (e.g., spectral network analysis) and applied solutions (e.g., noise-enhanced machine learning). Recent research highlights include higher-order network models, adversarial graph attacks, and interpretable network representations. He advises students like Shengmin Jin and Xinyi Zhou, whose work addresses critical challenges in network science and misinformation detection. Reza Zafarani actively contributes to the academic community through tutorials (e.g., WWW/SDM conferences) and open-source datasets like CHECKED, enabling reproducible research in misinformation studies.

Michael Followsمشاهده پروفایل

استاد

• Marine Biogeochemistry
• Oceanography
• Biogeochemical Modeling
• +۳ مورد دیگر

Michael Follows is a Professor at the Department of Ecology and Evolution, Massachusetts Institute of Technology (MIT). His research focuses on understanding biogeochemical cycles of carbon and nutrients in the ocean through numerical modeling, integrating physical transport, chemical, and biological processes. He leads projects that explore phytoplankton physiology, nutrient dynamics, and climate-ocean interactions using advanced computational tools. His work bridges micro-scale cellular processes with large-scale oceanic phenomena, emphasizing ecological and biogeochemical consequences of environmental changes. Follows collaborates with international observatories and employs Lagrangian models to study plankton blooms and eddy-driven biogeochemical processes. His research also addresses methodological challenges in metatranscriptomics and microbial ecology. Key areas of investigation include phytoplankton acclimation to environmental conditions, nitrogen fixation in marine systems, and the role of microbial diversity in shaping global biogeochemical cycles. Follows' studies often involve observational data from sites like the Blanes Bay Microbial Observatory and model outputs to predict ecosystem responses to climate change. Recent work highlights the importance of macromolecular composition, metabolic trade-offs, and symbiotic relationships in marine microbial communities. Publications frequently emphasize model-based analyses of nutrient cycling, viral-host interactions, and the impact of physical oceanography on biological productivity. His research has implications for understanding past climate transitions and future ocean carbon sequestration potential. Follows maintains an active lab at MIT, contributing to both theoretical and applied marine science through interdisciplinary collaboration.

Robert Kruegerمشاهده پروفایل

استادیار

• Visualization
• Visual Analytics
• Human-Computer Interaction
• +۵ مورد دیگر

Robert Krueger is an Assistant Professor in the Department of Computer Science & Engineering at NYU Tandon School of Engineering, and a member of the Visualization Imaging and Data Analysis Center (VIDA) at NYU. Previously, he held a joint postdoctoral appointment as a Senior Research Scientist and Subgroup Lead at Harvard University's Visual Computing Group (VCG) and Laboratory of Systems Pharmacology (LSP). His research focuses on scalable visualization and visual analytics for spatial and multivariate data, particularly in biomedical and geographical applications like smart cities and cancer tissue analysis. Education: Ph.D. in Computer Science (Dr. rer. nat.), University of Stuttgart, 2017 M.S. in Computer Science and Media, Stuttgart Media University, 2012 B.S. in Media and Communication Informatics, Reutlingen University, 2008 Research Interests: Krueger specializes in integrating machine learning with interactive visual interfaces to enable human-in-the-loop analysis of large biomedical and spatial datasets. He designs tools for multiplexed imaging data exploration, spatial biology, and geospatial dynamics. His work emphasizes interdisciplinary collaboration to address challenges in smart cities, immuno-oncology, and data standardization (e.g., MITI guidelines). Organization Committees: He actively contributes to the VIM (Visualization and Image Data Management) monthly meetings and the Spatial Biology Association (SBA), advancing data interoperability and spatial biology applications. His teaching accolades include multiple Harvard Excellence in Teaching Awards. Grants and Advising: As a subgroup leader since 2021, he manages research collaborations between VCG and LSP. He has supervised 14 student trainees/researchers on projects like CIMPLEX and HTAN. His team develops open-source tools like Minerva and Scope2Screen. Labs/Teams: Affiliated with VIDA at NYU and VCG/Harvard Medical School. He leads visualization efforts in the Human Tumor Atlas Network (HTAN), funded under the NCI Cancer Moonshot Initiative.

• Privacy
• Cybersecurity
• Human-Computer Interaction
• +۳ مورد دیگر

Florian Schaub is a Professor at the University of Michigan's School of Information, specializing in privacy, cybersecurity, and human-computer interaction. His work focuses on user-centric privacy mechanisms, including privacy policy analysis, usable security tools, and ethical implications of emerging technologies like VR and AI. He collaborates widely with researchers in computer science, social sciences, and policy domains. Key research areas include consumer privacy in digital ecosystems, security-aware design, and privacy implications of smart home technology. Schaub leads studies on data breach notifications, phishing mitigation, and privacy controls in mobile and web applications. His interdisciplinary approach bridges technical solutions with user behavior insights, aiming to improve transparency and empowerment in technology use. Publications span conferences like CHI, SOUPS, and USENIX Security, emphasizing empirical studies and system designs addressing real-world privacy challenges. He has co-authored over 130 papers and contributed to initiatives like Polisis, an NLP tool for analyzing privacy policies at scale.

Dengsheng Zhangمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Big Data
• Image Classification
• +۵ مورد دیگر

Dr. Dengsheng Zhang is a Senior Lecturer at Federation University Australia (formerly Monash University) and a Guest Professor at Xi'an University of Posts & Telecommunications, China. He holds a PhD in Computing (2002) and a GCHE (2006). His expertise spans over 25 years in artificial intelligence, big data, image processing, and music classification. He has published over 100 refereed papers (10,000+ citations) and authored the award-winning book Fundamentals of Image Data Mining (Springer, 2019). His research focuses on image classification, object detection, deep learning, and feature extraction. Dr. Zhang leads the Computational Science and Mathematics Group, contributing to projects like SIRBOT (Semantic Image Retrieval) and VFR (Visiting Friends and Relatives Travel Research). He serves as an Associate Editor for World Scientific's Transactions on Signal Processing. His teaching spans calculus, web design, computer networks, and project management. He has supervised 8 completed PhD students and actively engages in grants, including two ARC Discovery projects. His lab explores innovations in image retrieval, music classification, and machine learning applications.

Roderick McCollمشاهده پروفایل

استاد

• Biomedical Engineering
• Medical Imaging
• Magnetic Resonance Physics
• +۶ مورد دیگر

Roderick McColl, Ph.D., is a Professor of Radiology at UT Southwestern Medical Center and a member of its Medical Physics section. He provides magnetic resonance physics services to multiple imaging centers, including the Meadows Imaging Center, Rogers Imaging Center, and Clements University Hospital. Education: Bachelor’s in Electrical Engineering, University of Edinburgh Master’s in Electrical Engineering, University of Texas at Arlington Doctoral in Computer Science, University of Warwick, England Dr. McColl’s research focuses on advanced medical imaging technologies, such as multi-modality imaging workstations, echo-planar image reconstruction, functional MRI, diffusion tensor imaging, and medical image processing. His work emphasizes cross-modal generalization, imaging informatics, and data management systems for large-scale studies. His contributions include developing web-based research PACS systems for the Dallas Heart Study and DTI analysis tools for the Gulf War Neuroimaging Project. He has authored over 65 peer-reviewed articles and two book chapters, with funding from the Department of Defense, Veterans Affairs, and NIH. Scientific Awards: Fulbright Scholarship (1984) Dr. McColl has served on grant review committees for the American Heart Association, NIH, and international organizations. He actively contributes to the American College of Radiology and the American Association of Physicists in Medicine.

• Entity Resolution
• Knowledge Graphs
• Anomaly Detection
• +۴ مورد دیگر

Vassilis Christophides is a Researcher at INRIA Paris, France, specializing in data management and knowledge systems. His research spans entity resolution, knowledge graphs, anomaly detection, and IoT analytics, with recent focus on fairness-aware algorithms and explainable AI. He maintains active collaborations with institutions across Europe and has published extensively in top-tier venues including VLDB, ICDE, and KDD. His core research investigates: Scalable entity resolution techniques for web-scale data Knowledge graph construction and alignment methodologies Real-time anomaly detection in streaming environments Fairness and bias mitigation in data integration pipelines Edge computing optimizations for IoT analytics Recent publications demonstrate a strong trend toward responsible data science, combining foundational data management with emerging concerns in AI ethics. His work frequently develops novel methods for: (1) improving transparency in automated systems through explainable anomaly detection, (2) ensuring fairness in entity resolution workflows, and (3) optimizing resource-constrained edge environments for continuous analytics. Dr. Christophides leads research initiatives at INRIA and collaborates on European projects involving streaming data processing, knowledge representation, and distributed computing infrastructures. His team focuses on bridging theoretical frameworks with practical implementations for web-scale data challenges.

James Andzulisمشاهده پروفایل

دانشیار

• Strategy
• Sales
• Sales Management
• +۱۰ مورد دیگر

James 'Mick' Andzulis is the Chair of the Marketing Department and O Bleness Associate Professor of Marketing at Ohio University's College of Business. He also directs academics at the Ralph and Luci Schey Sales Centre. His academic career spans roles at LSU and extensive industry experience in engineering, insurance, and aviation sectors. Educated at Penn State (BS Chemical Engineering), Villanova (MBA), Temple (MS Finance), and the University of Alabama (PhD Marketing). Education: Ph.D., Marketing, University of Alabama (2014) MS, Finance, Temple University (2006) MBA, Villanova University (2001) BS, Chemical Engineering, Penn State University (1996) Research focuses on strategy, sales technology, B2B/B2C dynamics, and retail arbitration. Key contributions include work on salesperson communication strategies, frontline employee perceptions, and cultural intelligence impacts. His work appears in top journals like Journal of Service Research and Journal of Business Research . Award highlights include the Ohio University Marketing Departmental Impact Award (2019), Emerald Literati Citation (2017), and multiple conference best-paper awards. He serves on editorial boards for Journal of Marketing Theory and Practice and Journal of Global Scholars of Marketing Science . Teaching and academic leadership include immersive learning projects, accreditation education initiatives, and leadership roles in professional organizations like the National Conference in Sales Management and AMA Sales SIG. Labs/Teams: Directs Ohio University's Sales Centre academic programs and collaborates with industry partners through consulting and research projects.

• Information Retrieval
• E-Government Usability
• Accessibility for Older People
• +۴ مورد دیگر

Dr. Dan Smith is an Honorary Associate Professor at the School of Computing Sciences, University of East Anglia. He holds roles as Director of Learning and Teaching, Ethics Committee Chair, and Faculty Appeals Panel Chair. His academic background includes a BA in Geography (University of Nottingham) and a PhD in database systems for spatial/temporal data. He previously worked as an archaeologist, freelance programmer, and consultant before joining UEA in 1990. His research focuses on information retrieval, e-government usability, and accessibility for older adults. Notable projects include developing a public library impact assessment framework (East of England) and investigating postpartum smoking cessation (BabyBreathe trial). He has contributed to cloud computing policy analysis and seafood processing tracking systems. Key collaborations include work with the National Institute for Health and Care Research, Centre for Environment, Fisheries & Aquaculture Science, and Sapienza University of Rome. He is a Senior Fellow of the Higher Education Academy and affiliated with BCS, ACM, and IEEE. Teaching responsibilities include Internet Technologies, Human-Computer Interaction, and MSc Computing program leadership. Recent media coverage highlights his work on public library impacts, reaching over 6 platforms and Mendeley readership.