جست‌وجوی استاد و پژوهشگر

Bernardo Cuenca Grauمشاهده پروفایل

استاد

• Artificial Intelligence
• Knowledge Representation and Reasoning
• Knowledge Graphs
• +۶ مورد دیگر

Bernardo Cuenca Grau is a Professor of Computer Science at the University of Oxford and a Tutorial Fellow at Keble College. His research focuses on artificial intelligence, particularly knowledge representation and reasoning, knowledge graphs, computational logic, and semantic technologies. He leads the Information Systems Group and has contributed to high-impact software tools like LogMap, MORe, and PAGOdA. His work bridges theoretical foundations with practical applications, including industry collaborations through his co-founded startup Oxford Semantic Technologies, acquired by Samsung in 2024. He has received prestigious awards such as the Royal Society University Research Fellowship (2009-2017) and the 2025 Vice-Chancellor Award for Innovation. Affiliations: University of Oxford Department of Computer Science, Keble College Professional Roles: Tutorial Fellow, Co-founder of Oxford Semantic Technologies Research interests span declarative data analysis, graph neural networks, temporal reasoning, and ontology-based systems. His recent work explores connections between graph neural networks and logic programming (e.g., Datalog). He advises PhD students on topics like knowledge graph completion and explainable AI models. Key publications include foundational work on limit Datalog, ontology-based data access, and neural network stability. His work on LogMap (ontology matching) earned the Semantic Web Science 10-Year Award (2021). He actively participates in conferences like IJCAI and AAAI, serving as General Chair for the 2020 Description Logics workshop. Awards: Vice-Chancellor Award (2025), Distinguished Paper Award (IJCAI 2017), Royal Society Fellowship (2009-2017) Grants/Funding: Royal Society Fellowship, VC Innovation Award, MPLS Commercial Impact Award Cuenca Grau co-develops tools like SemFacet (faceted search system) and MeTeoR (temporal Datalog reasoner). His research group emphasizes interdisciplinary collaboration, addressing challenges in scalable reasoning, privacy in knowledge graphs, and industrial ontology management.

• Business Processes
• Blockchain Technology
• Semantic Technologies
• +۵ مورد دیگر

Assoc. Prof. Julius Köpke is an Associate Professor at the University of Klagenfurt's Department of Informatics Systems. His research focuses on business processes, blockchain technology, and semantic interoperability, with particular emphasis on smart contracts, artifact-centric processes, and interorganizational systems. He is affiliated with the Information and Communication Systems research group and contributes to the Institute for Computer Science Systems. Research Interests: - Interorganizational business processes with a focus on blockchain and smart contracts - Application of semantic technologies for data interoperability - Artifact-centric process modeling and data provenance Key Contributions: - Developed SecBPMN2BC framework for secure blockchain-based process modeling - Authored methods for aligning global and local processes, optimizing data-flow implementations - Pioneered lightweight XML-Schema annotation techniques for data translation Recent Work: - Explored LLM-based conversational process modeling tools - Investigated blockchain channel storage for business process data - Published extensively on time-aware processes and temporal constraints Labs/Teams: - Member of the Information and Communication Systems team - Active contributor to the Department of Informatics Systems' research initiatives

• Information Systems
• Computer Science
• Process Modeling
• +۳ مورد دیگر

Josef Lubas is a PhD candidate in the Research Group Information and Communication Systems at the University of Klagenfurt , Austria. He holds a BSc and MSc and is supervised by Prof. Johann Eder. His work focuses on process modeling, temporal constraints, and legal technology applications in smart contracts. Education: BSc, MSc (details unspecified); current PhD candidate in Informatics Systems. Research Interests: Josef specializes in temporal aspects of process models , conflict resolution in workflow systems , and legal smart contracts . His work bridges theoretical computer science with practical applications in business process management and regulatory compliance. Publications (2020–2023): Focus on temporal logic applications in process scheduling, dynamic controllability, and integrating time-aware models into legal frameworks. Recent work emphasizes smart contract systems with legal enforceability. Labs/Teams: Member of Team ICS within the Information and Communication Systems group. Collaborates with Prof. Eder’s research team on temporal data modeling and process engineering.

• Computer Science
• Medical Multimedia
• Video Retrieval
• +۲ مورد دیگر

Bernd Münzer is a researcher at the Institute of Information Technology at Alpen-Adria-Universität Klagenfurt. His work focuses on medical multimedia, video retrieval systems, and human-computer interaction, particularly in endoscopic and laparoscopic video analysis. He contributes to projects involving deep learning for content identification, interactive exploration tools, and medical data visualization. Medical video analysis and retrieval Human-computer interaction in multimedia systems Endoscopic imaging and surgical skill assessment Dynamic content descriptors for video processing Collaborative video search frameworks Temporal analysis of clinical multimedia data His research includes developing tools like ECAT for endoscopic annotation, diveXplore for interactive exploration, and datasets such as Cataract-101 for surgical analysis. Projects emphasize medical multimedia applications, efficient video encoding, and augmented interfaces for clinical workflows.

• Futures Research
• Political Science
• Public Policy
• +۳ مورد دیگر

Mikkel Knudsen is a Researcher and Doctoral Candidate at the Faculty of Social Sciences, Business and Economics, and Law (FSEJ Common) at the University of Turku. He holds a Master’s degree in Political Science from the University of Copenhagen (2010). His current research focuses on the temporality of policymaking and the application of futures studies in political contexts. Knudsen is affiliated with the Finland Futures Research Centre, where he serves as a Project Researcher. His work bridges political science with futures research, examining topics like Industry 4.0 technologies, digital transformation trends, and scenario-building for emerging technologies such as 6G networks. He has contributed to interdisciplinary projects analyzing global technology landscapes using tools like Google Trends and longitudinal data analysis. His research interests span futures studies, public policy analysis, and the societal implications of technological change. He has published widely on topics including future generations in policy frameworks, digital twin applications in manufacturing, and plausible scenarios for future mobile networks. Knudsen actively engages in academic peer review, serving as a reviewer for journals like Futures & Foresight Science and American Sociological Review . Knudsen’s work has been cited in multiple disciplines, with notable contributions to understanding gaps between technological visions and industrial realities. He has also participated in public discourse, including a recent podcast for the Åland Islands Peace Research Institute’s Kastelholm Talks 2024, highlighting his role as a bridge between academic research and societal engagement.

• Real-Time Systems
• Database Systems
• Distributed Systems
• +۱۰ مورد دیگر

Ming Xiong is a researcher affiliated with Bell Labs , focusing on real-time systems, temporal consistency, and data freshness in embedded environments. His work spans concurrency control protocols, deferrable scheduling algorithms, and wireless communication systems. Key Research Areas: Real-time databases, XML data integration, location management in mobile networks, IoT semantic communication, and wireless channel modeling. Collaborations: Frequent co-authorship with Song Han, Deji Chen, Kam-yiu Lam, Krithi Ramamritham, and Wenfei Fan. His recent publications (2023-2025) emphasize semantic communication for IoT and wireless systems, temporal consistency in cyber-physical systems, and environmental data analysis via remote sensing. While no explicit awards or educational background are listed, his contributions to IEEE journals and conferences highlight expertise in real-time transaction processing and distributed systems.

Lise PINAULTمشاهده پروفایل

پژوهشگر

• Climate Change
• Ecological Indicators
• Carbon Storage
• +۳ مورد دیگر

Lise PINAULT is a Researcher at the Chrono-environnement research unit (UMR 6249 CNRS) within the University of Franche-Comté. Her work focuses on climate change, ecological indicators, carbon storage, and peatland ecology. As a postdoctoral researcher since 2021 under supervisors Daniel Gilbert and Elsa Martin, she developed a national database for French peatlands to prioritize restoration sites, integrating ecological data with socio-economic factors like land tenure and costs. Her research bridges environmental science with policy, emphasizing carbon neutrality and sustainable land management. Education : PhD defended in April 2025 at the University of Franche-Comté. Prior academic work includes studies on socio-ecological systems and river dynamics at the Rohrschollen Island (Rhine River). Research Interests : Combining ecological data with socio-economic analysis to inform environmental policy. Specializes in peatland restoration, GHG mitigation, and the role of historical data in conservation strategies. Uses computational frameworks to model human-nature interactions across temporal and spatial scales. Key Contributions : - Developed a national peatland database integrating ecological and socio-economic metrics - Advanced methodologies for assessing restoration feasibility and costs - Explored the dynamics of human-river interactions and socio-ecological systems Labs/Teams : Core member of the DYNABIO team at Chrono-environnement, collaborating with interdisciplinary groups on environmental policy and ecosystem services.

Garrett Hopperمشاهده پروفایل

استادیار

• Aquatic Ecology
• Biodiversity-Ecosystem Function
• Conservation Biology
• +۳ مورد دیگر

Dr. Garrett Hopper is an Assistant Professor in Aquatic Ecology at the School of Renewable Natural Resources, Louisiana State University. His research focuses on community ecology, biodiversity-ecosystem function, and conservation of freshwater ecosystems, particularly in mussel and fish assemblages. He holds a Ph.D. in Biology from Kansas State University, with postdoctoral research at the University of Alabama. Key research themes include identifying processes driving species diversity, habitat associations, and global change impacts on freshwater systems. His lab operates out of LSU’s School of Renewable Natural Resources and investigates how biodiversity influences nutrient cycling and ecosystem functions through aggregated filter feeders like mussels. Recent publications emphasize mussel growth dynamics, host-fish co-occurrences, biodiversity-ecosystem function relationships, and trait-based conservation strategies. His work spans experimental field studies and large-scale database analyses, contributing to both theoretical and applied freshwater ecology. Teaching includes courses on Ichthyology, Fish Biology, and Freshwater Mussel Ecology. He actively collaborates with regional and national institutions on conservation initiatives and maintains a robust publication record in high-impact journals like Biological Reviews , Functional Ecology , and Scientific Data .

Craig A Abelمشاهده پروفایل

استاد مدعو

• Entomology
• Agricultural Genomics
• Crop Genetics
• +۳ مورد دیگر

Dr. Craig A. Abel is an Adjunct Professor of Entomology at Iowa State University and a Supervisory Research Entomologist with the USDA-ARS Corn Insects and Crop Genetics Research Unit. He oversees research on maize, soybean, barley, and legume crops, focusing on ecological pest management, comparative genomics, and disease resistance signaling. Education Ph.D., Entomology, Iowa State University, 1998 M.S., Entomology, Iowa State University, 1993 B.S., Animal Science, Iowa State University, 1987 His research explores host plant resistance in maize to pests like European corn borer and western bean cutworm, Bt-corn risk assessment , and interactions between mycotoxigenic fungi and pests. Recent work includes using machine learning for pest classification, evaluating transgenic maize resistance, and refining agricultural action thresholds through field studies. Dr. Abel's 116 publications span insect resistance mechanisms , genetic mapping , and mycotoxin contamination in crops. He supervises a USDA-ARS team focused on sustainable crop production and contributes to databases like MaizeGDB and SoyBase.

Lianhua Chiمشاهده پروفایل

مدرس

• Big Data Analytics
• Artificial Intelligence in Healthcare
• Machine Learning
• +۷ مورد دیگر

Lianhua Chi is a Lecturer in the Department of Computer Science and Information Technology at La Trobe University, Melbourne, Australia, since February 2018. He holds a dual PhD in Machine Learning and Data Mining from the University of Technology Sydney (Australia) and Huazhong University of Science and Technology (China). Before joining academia, he worked as a Postdoctoral Researcher at IBM Research Australia on Watson Education and Health, and as a Data Specialist at the University of New South Wales (UNSW). His research focuses on big data analytics, particularly in healthcare applications, AI-driven Autism Screening, and hashing techniques for real-time data processing. Chi has received notable awards including the 'Young Global Changer' title from G20/T20 Germany, 'Top 200 Young Researchers Globally' by the Heidelberg Laureate Forum, and the IBM External Honors award. Education: PhD in Machine Learning and Data Mining (2015), University of Technology Sydney & Huazhong University of Science and Technology Previous roles: Postdoc at IBM Research Australia, Visiting Researcher at UTS Research Interests: Chi’s work emphasizes adaptive hashing algorithms, graph stream classification, geolocation prediction in social media, and time series analysis. He applies these techniques to healthcare challenges such as AI-based Autism Screening and medical imaging diagnostics. His methodologies prioritize scalability and real-time adaptability. Awards & Grants: Best Paper Award (PAKDD13) Romberg Grant (Heidelberg Laureate Forum, 2016) Innovation Connection Grant (NostraData, 2022–2023) Advising & Collaborations: Chi has collaborated with Harvard Medical School’s Gehlenborg Lab and led projects on healthcare AI and cybersecurity. His work integrates advanced hashing techniques with clinical data to improve diagnostic accuracy and patient care efficiency. Labs/Teams: Active in interdisciplinary teams focusing on AI ethics, healthcare analytics, and big data security at La Trobe University.

• Temporal Databases
• Query Languages
• Embedded Control Systems
• +۴ مورد دیگر

David Toman is an Assistant (later Associate) Professor in the Department of Computer Science at the University of Waterloo, part of the Faculty of Mathematics. His research focuses on temporal databases, query languages, embedded control systems, semi-structured data (XML), finite model theory, and programming language implementation. He holds a PhD from Kansas State University (1996) and an MS (MGr.) from Masaryk University (1992). Toman has held roles including Visiting Professor at BRICS, Aarhus University, and postdoctoral fellowships at the University of Toronto. His work includes over 40 refereed publications and contributions to projects funded by CITO, CFI, and NSERC. Awards include the NSERC/NATO Postdoctoral Fellowship and multiple summer school fellowships. Education: PhD in Computer Science, Kansas State University (1996) MS (MGr.) in Computer Science, Masaryk University (1992) Research Interests: Temporal databases and query languages Query processing in embedded control systems XML and semi-structured data management Finite model theory and formal methods Programming language implementation Grants & Awards: CITO Project: Text Indexing for Data Warehouses (CDN$143,000) CFI/OIT: Software Technology for Embedded Control Programs (CDN$705,000) NSERC Individual Research Grant (CDN$84,000) Key Contributions: Developed temporal extensions of SQL and query optimization techniques Contributed to description logics and duplicate elimination in databases Published widely in venues like ACM TODS, IEEE TKDE, and EDBT

Leocadio Blanco Bercialمشاهده پروفایل

استادیار

• Zooplankton Ecology
• Molecular Phylogenetics
• Biodiversity
• +۳ مورد دیگر

Dr. Leocadio Blanco Bercial is an Assistant Professor at Arizona State University (ASU), affiliated with the School of Ocean Futures and the School of Life Sciences. He is also a Senior Global Futures Scientist at the Bermuda Institute of Ocean Sciences (BIOS), now integrated into ASU. His research focuses on zooplankton ecology, integrating molecular and morphological tools to study diversity, population connectivity, and evolutionary processes in marine systems. Education: PhD in Biology (University of Oviedo, Spain, 2009), M.S. in Biology (2002), and B.S. in Biology (2000), all from the University of Oviedo. Research Interests: Plankton community diversity, population connectivity in marine organisms, phylogenetic relationships within Copepoda, and integrating diversity measurements into ocean biogeochemical models. His work emphasizes understanding how diversity is maintained in open ocean ecosystems and its implications for climate change. Key Projects: Includes studies on zooplankton mediation in particle formation, the VAMPIRE autonomous profiling vehicle, and the BIOSSCOPE project examining plankton ecology in the Sargasso Sea. Courses taught include Ocean Futures, Ecology, and special topics in marine sciences. Lab Affiliation: Zooplankton Ecology Lab, focusing on molecular and classical ecological approaches to study marine plankton diversity and dynamics. Collaborative efforts include global initiatives on copepod phylogeny and population genomics.

• Society and Technology Interrelationships
• Information and Communication Technologies
• Voting Systems
• +۹ مورد دیگر

Amir-hassan Ghaseminejad-tafreshi is a faculty member at Capilano University within the Faculty of Business and Professional Studies, School of Business. He holds a PhD from Simon Fraser University's Faculty of Communication, Art and Technology (2019), an M.Sc. in Electrical Engineering in Computer Hardware from Sharif University of Technology (1989), and a B.Sc. in Electronic Engineering from the same institution (1986). His educational background spans engineering, technology, and communication studies, reflecting his interdisciplinary approach to research and teaching. He has taught courses in operations management, statistics for business, business decision making, database administration and design, business management, information management, and various technology-related subjects. Ghaseminejad's research focuses on the intersection of society and technology, with particular emphasis on how advanced information and communication technologies influence collective decision making, voting systems, and citizen engagement in democracies. His work also extends to modeling the criminal justice system, computational criminology, data science, and the philosophy of science and technology. He employs interdisciplinary mixed methodology research, combining statistical analysis and mathematical process modeling with qualitative understanding of social phenomena. His publications demonstrate a clear trajectory of research that bridges technical data analysis with social science applications, particularly in criminal justice system modeling and democratic processes. The publications show increasing sophistication in handling complex social systems through quantitative methods while maintaining a critical perspective on technology's societal impacts. Graduate Fellowship (PhD) Award, 2013 Graduate Fellowship (PhD) Award, 2010 Ghaseminejad has been actively involved in multiple research centers including the Institute for Canadian Urban Research Studies (ICURS) at SFU, where he develops statistical and process models of British Columbia's criminal justice system; the Interdisciplinary Research in the Mathematical and Computational Sciences (IRMACS); and the Center for Policy Research on Science and Technology (CPROST). His teaching philosophy is learner-centered, motivational, inclusive, and participatory, informed by ability-based pedagogy and active participation learning models.

• Knowledge Representation
• Description Logics
• Computational Logic
• +۳ مورد دیگر

Magdalena Ortiz is a Full Professor and Head of the Knowledge-Based Systems Research Unit at TU Wien, specializing in Knowledge Representation and Reasoning with a focus on Description Logics (DLs). Her work emphasizes integrating DLs with database systems, particularly in query languages and reasoning algorithms. She leads research in semantic technologies, ontology-mediated query answering, and formal methods for data validation (e.g., SHACL). Research interests include expressive query languages, computational complexity of DL reasoning, and applications in graph databases and cloud security. She has extensive experience in EU-funded projects (e.g., FRESH, KtoAPP) and serves editorial roles in AI conferences/journals. Her teaching includes advanced courses on Description Logics, Logic, and Ontology Engineering. Notable contributions include advancements in SHACL validation, Datalog rewritings for ontology-mediated queries, and reasoning with closed predicates. She advises multiple PhD students and collaborates internationally on topics like temporal equilibrium logic and OBDA systems.

Laura Tateosianمشاهده پروفایل

استاد آموزشی

• Geospatial Analytics
• Environmental Modeling
• Remote Sensing
• +۳ مورد دیگر

Laura Tateosian is an Assoc Teaching Professor at the Center for Geospatial Analytics, North Carolina State University, within the College of Natural Resources. She specializes in geospatial-temporal data visualization and computational methods for environmental analysis. Her research focuses on innovative data representation, including eye-tracking studies for geospatial interaction, open-source database management, and coastal terrain visualization. She has developed graduate courses in geospatial algorithms and programming. Her research interests span geospatial analytics, environmental modeling, and the application of computational methods to address societal challenges such as plant disease pandemics and urban park usage. She has contributed to projects like the Plant Aid Database (PAdb) for predicting disease spread and collaborated with Wake County on geospatial solutions for public infrastructure. Grants : PIPP Phase I ($1M NSF grant): Predictive tools for plant disease pandemics Geo-IDEAs: Wake County geospatial application development Laboratory for Analytic Sciences projects on sensemaking and narrative processing Laura has extensive experience in interdisciplinary projects, including fire management systems for the National Park Service and terrain evolution visualization for climate change studies. Her work bridges computational science with real-world applications in agriculture, ecology, and urban planning.