جست‌وجوی استاد و پژوهشگر

Tibor Marcinekمشاهده پروفایل

استاد

• Mathematics Education
• Educational Technology
• Teacher Knowledge Development
• +۳ مورد دیگر

Tibor Marcinek is a Professor of Mathematics at Central Michigan University, affiliated with the College of Science and Technology. His research focuses on mathematics education with an emphasis on K-8 teacher knowledge development, cross-national educational comparisons, and integrating dynamic geometry systems into teaching. He holds a Ph.D. (2002) and M.Sc. (1995) from Comenius University in Bratislava, Slovakia. Education: Ph.D., Comenius University in Bratislava, Slovakia (2002) M.Sc., Comenius University in Bratislava, Slovakia (1995) Research Interests: Mathematical and technological knowledge for teaching K-8 mathematics Open-source dynamic geometry systems in primary education Cross-national comparisons of teacher competency Teaching: He teaches courses such as Mathematics for Elementary Teachers, Geometry for K-8 Teachers, and History of Elementary Mathematics. His pedagogical approach emphasizes active learning through problem-based and technology-enhanced methods, minimizing traditional lecturing in favor of collaborative activities and discussions. Key Achievements: 2023: Distinguished Teaching Award (MAA Michigan Section) 2021: Outstanding Teaching Award (CMU College of Science and Engineering) Labs/Initiatives: Develops open-source educational resources including interactive Java applets for geometric constructions and promotes OER (Open Educational Resources) adoption in mathematics education.

• Computer Vision
• Neural Networks
• Pattern Recognition
• +۳ مورد دیگر

Nikolaos Vassilas serves as Professor in the Department of Informatics and Computer Engineering at the University of West Attica, Greece, with leadership roles including Director of the Intelligent Knowledge, Image & Information Systems research Laboratory (ISLab) since 2019 and former Director of the Joint Greek-French Master Degree Program (2016-2020). His academic journey includes research positions at NCSR "Demokritos" and EPFL. His educational credentials feature a Diploma in Electrical Engineering from Aristotle University of Thessaloniki (1983), and M.S.E.E. and Ph.D. degrees from the University of Minnesota (1987, 1990). Professional affiliations include IEEE Computational Intelligence Society, Hellenic Society of Artificial Intelligence, and Greek Computer Society. Professor Vassilas' research centers on Computer Vision and Neural Networks with applications in urban analysis and remote sensing. His work integrates deep learning for building extraction from aerial/LiDAR data, semantic modeling in 3D urban environments, and neural network-based environmental prediction systems. Key methodological focuses include mean-shift algorithms, Hough transforms, and multisource spatial data fusion. Analysis of his recent publications reveals consistent specialization in computer vision techniques for urban infrastructure analysis, particularly building contour detection and 3D reconstruction using convolutional neural networks. The integration of aerial imagery with elevation data and robust line detection algorithms represents a dominant research trajectory across his 70+ publications. No scientific awards were documented in the source materials. He has coordinated two European Union co-funded research programs and participated in multiple national projects, with expertise in environmental data processing and intelligent spatial analysis systems. His leadership extends to directing research laboratories and international academic programs, demonstrating significant grant management experience. Professor Vassilas leads the Intelligent Knowledge, Image & Information Systems research Laboratory (ISLab), which focuses on advancing computer vision techniques for urban planning and environmental monitoring applications through interdisciplinary team collaboration.

Leif Harald Karlsenمشاهده پروفایل

مدرس ارشد

• Ontology Engineering
• Deductive Databases
• Qualitative Spatial Reasoning
• +۱ مورد دیگر

Leif Harald Karlsen is a Senior Lecturer at the University of Oslo's Department of Informatics, specializing in data and knowledge management. His research focuses on ontology engineering, deductive database systems, and qualitative spatial reasoning. Karlsen has developed formal frameworks for pattern-based ontology engineering and efficient representations of spatial information. His work on OTTR (Reasonable Ontology Templates) provides formal methods for ontology pattern specification and implementation. Karlsen also researches multi-scenario reasoning applications in geological subsurface evaluation.

Karin Stolpeمشاهده پروفایل

عضو هیئت علمی

• Science Education
• Technology Education
• AI Literacy in Education
• +۳ مورد دیگر

Karin Stolpe is a Senior Associate Professor at Linköping University's Department of Behavioural Sciences and Learning (IBL), affiliated with the Division of Learning, Aesthetics, Natural Science (LEN). Her work focuses on science and technology education, particularly addressing AI integration in classrooms, teacher professional development, and cognitive aspects of programming instruction. Her research explores topics like AI ethics in education, multimodal learning strategies, and the role of metaphors in teaching abstract concepts. Current projects include investigating AI literacy for educators and analyzing spatial gestures in programming lectures. She contributes to the Technology and Science Education Research (TESER) unit, emphasizing evidence-based teaching methods. Recent publications highlight her work on technology teachers' pedagogical content knowledge, ethical challenges posed by AI tools in STEM classrooms, and visual programming's role in interdisciplinary learning. Her articles often bridge cognitive semiotics with educational practice, offering frameworks for modernizing curricula and enhancing teacher preparedness for technological advancements.

• Multiagent Systems
• Agent Architecture
• Agent-based Simulation
• +۷ مورد دیگر

Julian Padget is a Reader (equivalent to Associate Professor) in the Department of Computer Science at the University of Bath, with extensive affiliations across multiple research centers including the EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa), Water Innovation and Research Centre (WIRC), UKRI CDT in Accountable, Responsible and Transparent AI, Centre for Therapeutic Innovation, and Institute for Digital Security and Behaviour (IDSB). His work bridges computer science with energy systems, healthcare, and digital governance through interdisciplinary collaborations. Padget's research centers on multiagent systems , agent architecture , norm representation and reasoning , and fusing symbolic and statistical AI , with significant contributions to distributed ledgers, policy modeling, and narrative models. His fingerprint analysis reveals dominant connections to multi-agent systems (100%), web services (72%), and normative frameworks (48%), reflecting his focus on creating ethically aligned autonomous systems for complex socio-technical environments. Recent work demonstrates increasing integration of AI with energy infrastructure and biomedical applications. Analysis of his 15 most recent publications shows a clear trajectory toward operationalizing AI ethics, particularly in bias management and trust frameworks, while maintaining strong foundations in multiagent coordination. His energy sector research increasingly focuses on digital spine architectures for data sharing, and biomedical collaborations explore molecular imaging techniques for cancer research. The consistent thread across domains is the development of governance frameworks for autonomous systems. Padget actively supervises doctoral students with 23 supervised works documented and serves as Principal Investigator on major grants including EPSRC-funded energy network projects (2025-2026) and Innovate UK collaborations with the BBFC. His policy impact is evidenced by parliamentary testimony in March 2025 that generated coverage across 16 news outlets. Current projects emphasize AI for agile energy networks, value-aware agent architectures, and statutory compliance frameworks for online media. His laboratory ecosystem spans the IAAPS Innovation Bridge and Institute for Digital Security and Behaviour, focusing on translating theoretical agent frameworks into practical applications for energy systems, digital governance, and health interventions. The Water Innovation and Research Centre provides critical infrastructure for his energy-related simulations, while therapeutic innovation collaborations enable biomedical applications of his norm-representation frameworks.

• Robotics
• Computer Vision
• Human-Robot Interaction
• +۲ مورد دیگر

Yik Lung Pang is a researcher at the School of Electronic Engineering and Computer Science, Queen Mary University of London, based in the Peter Landin building (Room CS 440). His work bridges robotics, computer vision, and machine learning to advance human-robot collaboration in real-world environments. His research specializes in human-robot interaction with a focus on handover behaviors, 3D scene reconstruction, and object pose estimation. Key contributions include: Developing LaVA-Man for visual action representation learning in robot manipulation Creating stereo-based hand-object reconstruction systems for safe human-to-robot handovers Pioneering incremental 6D pose estimation techniques for dynamic object tracking Integrating audio-visual modalities to enhance object classification in collaborative tasks His methodology consistently emphasizes safety, adaptability to unseen environments, and real-time performance. From 2021-2025, Pang's publication trajectory reveals an escalating focus on multimodal perception (combining vision, audio, and depth data) and robustness in unstructured settings. His work addresses critical gaps in human-robot teaming, particularly for domestic and industrial applications involving unknown containers and complex handovers. No scientific awards, student supervision, or laboratory affiliations were documented in the provided sources.

Chris Eliasmithمشاهده پروفایل

استاد

• Theoretical Neuroscience
• Computational Neuroscience
• Neuromorphics
• +۶ مورد دیگر

Chris Eliasmith is a Professor jointly appointed in the Systems Design Engineering and Philosophy departments at the University of Waterloo, with a cross-appointment to Computer Science. He is the Founding Director of the Centre for Theoretical Neuroscience and holds the Canada Research Chair in Theoretical Neuroscience. His research focuses on mathematical modeling of neural systems, including the Neural Engineering Framework (NEF) and Semantic Pointer Architecture (SPA), which underpin the world’s largest functional brain simulation, Spaun. He leads the Computational Neuroscience Research Group (CNRG), advancing neuromorphic computing, spiking neural networks, and cognitive modeling. Education: PhD in Neuroscience & Psychology (2000), Washington University in St. Louis MA in Philosophy (1995), University of Waterloo BASc in Systems Design Engineering (1994), University of Waterloo Research: His work integrates theoretical neuroscience with practical applications in robotics, AI, and neuromorphic hardware. Key contributions include the NEF, Spaun, and innovations like the Legendre Memory Unit (LMU) and Spatial Semantic Pointers (SSPs). His lab explores adaptive neural systems, decision-making models, and biologically plausible machine learning algorithms. Teaching: Recent courses include SYDE 556 (Simulating Neurobiological Systems), SYDE 750 (Topics in Systems Modelling), and PHIL 356 (Intelligence in Machines, Humans, and Other Animals). Awards: 2015 NSERC Polanyi Prize Labs & Projects: The CNRG develops tools like Nengo for simulating large-scale neural systems and collaborates on neuromorphic hardware platforms such as Loihi. Current projects span neural robotics, cognitive architectures, and biologically inspired AI systems.

• Semantic Web
• Linked Data
• Ontology Engineering
• +۷ مورد دیگر

Dr. Stefan Schlobach is an Associate Professor at the Faculty of Science, Vrije Universiteit Amsterdam, affiliated with the Artificial Intelligence department, Network Institute, and Knowledge Representation and Reasoning group. His research focuses on Semantic Web, Linked Data, Ontology Engineering, and Hybrid Intelligence systems. He has published over 116 peer-reviewed works and supervised 6 PhD theses. Recent projects include robotic knowledge acquisition (ORKA ontology), explainable AI for security systems, and knowledge engineering for virtual heritage applications. He co-developed the LOTUS search framework for big linked data and contributed to the CoPla ontology for agriculture. His work bridges theoretical foundations (e.g., argumentation systems) with applied domains (e.g., cyber-physical systems, cultural heritage digitization). Research Interests: Semantic Web Technologies Knowledge Graphs & Ontology Engineering Hybrid Intelligence (Human-AI Collaboration) Robotic Perception Systems Explainable AI Entity Linking & Identity Resolution Key Contributions: Developed LOTUS adaptive search system (2016 prize-winning work) Created ORKA ontology for robotics knowledge acquisition Pioneered perceived-entity linking methodologies Advocated knowledge engineering principles for hybrid systems Teaching: Leads courses in Artificial Intelligence, Knowledge Representation, and Semantic Technologies at both undergraduate and graduate levels.

Andreas Larssonمشاهده پروفایل

پژوهشگر

• Educational Development
• Technology Education
• Educational Science
• +۳ مورد دیگر

Andreas Larsson is a Postdoc researcher at Linköping University's Department of Behavioural Sciences and Learning (IBL), within the Division of Learning, Aesthetics, and Natural Science (LEN). His work focuses on educational development, particularly in science and technology education, and he actively contributes to the Swedish National Centre for Science and Technology Education (NATDID). His research emphasizes bridging educational research with practical teaching methods, including the integration of technology, programming pedagogy, and the role of spatial metaphors in instruction. Education: While specific academic degrees are not detailed in the provided texts, Larsson's role as a Postdoc indicates advanced qualifications in educational sciences or related fields. Research Interests: Larsson specializes in technology education, programming pedagogy, and the use of gestures and metaphors in teaching. He explores how spatial constructs and linguistic metaphors aid abstract concept comprehension, particularly in programming and STEM education. His work also addresses curriculum continuity and material resources in Swedish vocational training programs. Articles Overview: Larsson’s recent publications (2022–2025) focus on metaphor analysis in programming education, gesture-based teaching strategies, and the material foundations of effective technology education. His research highlights the interplay between embodied cognition and instructional design. Awards: No scientific awards are explicitly mentioned in the provided texts. Advising & Grants: While specific grants are not listed, Larsson collaborates with NATDID to translate research into practical educational tools. His involvement in conferences like the WERA Task Force Global Research in Extended Education (2025) underscores his contribution to educational policy and outreach. Labs/Teams: Active in LEN and NATDID, he contributes to projects on AI literacy in teacher education and the greening of working life (GROWL). His work intersects with interdisciplinary initiatives exploring digital tools in education and workplace dynamics.

Manling Liمشاهده پروفایل

استادیار

• Multimodal Learning
• Computer Vision
• Natural Language Processing
• +۶ مورد دیگر

Manling Li is an Assistant Professor of Computer Science at Northwestern University. Their research focuses on multimodal learning, vision-language models, and embodied agents. They explore challenges in spatial reasoning, knowledge hallucination in LLMs, and event understanding. Their work often bridges AI, computer vision, and natural language processing to advance autonomous agent capabilities and video-language understanding. Research interests prominently feature multimodal benchmarking (e.g., EmbodiedBench), video-language analysis (Hourvideo), and mental health applications via self-play systems like MentalArena. They investigate foundational issues like knowledge overshadowing in LLMs and develop techniques for 3D layout optimization (LayoutVLM). No scientific awards are explicitly listed in the provided information. No listed advisees or grants are currently available. Their contributions emphasize cross-disciplinary collaboration between computational models and real-world tasks, such as assembly instruction grounding and long-form video comprehension. Labs or team affiliations are not explicitly detailed in the provided information, though their work suggests involvement in AI/ML research groups focused on embodied intelligence and multimedia systems.

Wen Huaمشاهده پروفایل

پژوهشگر ارشد

• Data Science
• Machine Learning
• Data Mining
• +۵ مورد دیگر

Dr. Wen Hua is an Honorary Senior Research Fellow at the University of Queensland's School of Electrical Engineering & Computer Science. His research focuses on Data Science, Machine Learning, and Knowledge Graphs, with significant contributions to privacy-preserving techniques, neural network architectures, and trajectory analysis. He has co-authored over 80 peer-reviewed publications, including influential works on entity linking, meta-learning, and spatiotemporal data privacy. His work bridges theoretical advancements with practical applications in areas like recommendation systems, sentiment analysis, and information resilience. Key research interests include: Machine Learning and Deep Learning Privacy-Preserving Data Publishing Knowledge Graph Construction Text Mining and Natural Language Processing Spatiotemporal Trajectory Analysis Information Retrieval Systems Recent publications highlight trends in: Neural architectures for meta-learning and transformer-based systems Efficient algorithms for relation extraction and entity disambiguation Temporal and spatial data anonymization techniques Integration of knowledge graphs with text corpus analysis

Jane Hunterمشاهده پروفایل

استاد

• Semantic Web
• Data Integration
• eScience
• +۳ مورد دیگر

Jane Hunter is an Honorary Professor in the School of Electrical Engineering and Computer Science at the University of Queensland. Her research focuses on semantic web technologies, data integration, and eScience, with significant contributions to ontology development, digital libraries, and environmental informatics. She leads projects such as OzTrack for animal tracking data and the 3D Water Atlas for groundwater visualization. Her work emphasizes interdisciplinary collaboration, leveraging semantic web principles to enhance data interoperability and decision-making in fields ranging from environmental science to healthcare. Her research interests include semantic annotation systems for cultural heritage, citizen science data management, and evidence-based policy frameworks using global indicators. Notable contributions include developing the Open Annotation Collaboration model and pioneering tools like MatSeek for materials scientists. She has collaborated internationally on initiatives such as the Health-e-Waterways project and the SKELETOME skeletal dysplasia knowledge platform. Jane has authored over 150 publications across journals like Hydrogeology Journal , Journal of Biomedical Informatics , and Ecological Informatics , reflecting her expertise in applying computational methods to complex scientific challenges. Her work bridges technical innovation with societal impact, addressing issues from biodiversity tracking to urban sustainability.

Siddhartha Dattaمشاهده پروفایل

پژوهشگر ارشد

• Distributed Machine Learning
• Model Adaptation
• Cybersecurity
• +۴ مورد دیگر

Siddhartha Datta is a Researcher at the University of Oxford's Department of Computer Science, specializing in distributed machine learning and adaptive systems. His research develops end-to-end solutions for model training, security, and deployment. Key research areas include: Adaptive learning algorithms for dynamic environments Defense mechanisms against adversarial attacks Human-centered AI interfaces and tools Cross-reality systems blending digital/physical spaces Efficient model compression techniques Current projects investigate prompt engineering for generative models, online learning under data drift, and 3D object detection refinement. His work combines theoretical frameworks with practical implementations, resulting in tools like GreaseTerminator for digital sovereignty and DeepObfusCode for source protection. Datta has collaborated with Google and Cornell University during his doctoral studies. His open-source contributions include neurocogpy (ECoG processing) and Polysemy Word Tagging Tool, demonstrating commitment to accessible research tools.

• Higher Education Pedagogy
• Networked Learning
• Postdigital Education
• +۵ مورد دیگر

Dr. Dewa Wardak is a Senior Lecturer in Business Educational Development at the University of Sydney Business School. She holds a PhD from the University of Sydney and has affiliations with organizations like HERDSA and the Australasian Society for Computers in Learning in Tertiary Education. Her research focuses on higher education pedagogy, networked learning, and object-based learning. She leads initiatives in curriculum development and sustainable leadership education, emphasizing SDG-driven approaches. Notable awards include the 2024 Dr. John Yu Fellowship and multiple teaching awards. Her work spans co-design of educational programs, leveraging technology and collaborative practices. Recent projects include partnerships with museums to enhance leadership education and scaling educational innovations during the pandemic. She advises on undergraduate research through ACUR and mentors faculty via Share Sessions professional development programs. Key grants include a Medical Research Future Fund grant ($799k) for adolescent health research and a student transition support grant. Her research outputs emphasize networked learning, curriculum innovation, and ethics in postdigital education. She actively participates in conferences like ASCILITE and Networked Learning Conference, contributing to transformative educational practices.

Achim Rettingerمشاهده پروفایل

استاد

• Machine Learning
• Knowledge Representation
• Natural Language Processing
• +۴ مورد دیگر

Achim Rettinger is a full professor at Trier University, leading the research group krAil (Knowledge Representation Learning). He specializes in machine learning, natural language understanding, and human-centered AI. His work focuses on expressive knowledge representations and their applications in semantic technologies. Education: Studied Computer Science at Universität Koblenz (Germany), University of Georgia (USA), and University of Alberta (Canada). PhD in machine learning at TU Munich/Siemens AG, followed by habilitation at KIT (2016). Served as interim professor at Karlsruhe Institute of Technology (2018/19). Research interests include knowledge graphs, cross-lingual semantic annotation, and data-driven analysis in political and medical domains. Notable contributions include the X-LiSA framework and work on semantic web technologies. Awards include best paper and challenge awards at ISWC and ESWC conferences. Leadership roles include senior PC member at ISWC, track chair at ESWC, and membership in AI for Good Foundation. Active in EU projects, DFG grants, and large-scale collaborative initiatives. Key projects: BreXearch (cross-lingual Brexit analysis), xLiMe System (semantic search), and medical decision support systems for liver surgery. Collaborates with interdisciplinary teams on cognition-guided surgery and data integration. Publications span top venues like ISWC, NeurIPS, ICLR, and CVPR, with a focus on semantic web, machine learning, and applied AI solutions.