برای مسیر پژوهشیتان، استاد راهنما، استاد دانشگاه و پژوهشگر مناسب را پیدا کنید و با آنها ارتباط بگیرید.
نمایش ۳۱۶-۳۱۹ از ۳۱۹ استاد راهنما
اطلاعات پروفایلها از صفحات عمومی دانشگاهها گرفته شده و ممکن است بهروز نباشد.
Estefanía Talavera Martínez is an Assistant Professor specializing in Datamanagement & Biometrics , with research spanning artificial intelligence, computer vision, and health informatics. Her work addresses surveillance, emotion recognition, and egocentric data analysis.
استادیار
Shenghui Wang is an Assistant Professor in Human Media Interaction with a focus on hybrid human-AI systems. Affiliated with OCLC Research Europe since 2012, his work bridges artificial intelligence, virtual reality, and cultural heritage digitization. Research Interests: Ontology modeling, eye-tracking integration, multimodal conversational agents, and FAIR metadata principles for cultural data Key Activities: Organized HHAI 2025 and ISWC 2025 conferences; presented at ICT Open 2024 and Hybrid Intelligence Consortium meetings Current Work: Developing social VR frameworks for collaborative art exploration and evaluating RAG-based chatbots in healthcare contexts His recent publications emphasize Human-Computer Interaction in educational and cultural settings, with specific attention to: Personalized learning systems Virtual heritage applications Ontology-driven VR environments Author disambiguation algorithms Wang's research contributes to UN Sustainable Development Goals through innovative applications in education, cultural preservation, and accessible AI systems.
استادیار
Koray Karaca is an Assistant Professor in Philosophy , specializing in the intersection of Artificial Intelligence , Machine Learning , and Philosophy of Science . His work critically examines epistemic and ethical dimensions of AI, with a focus on Knowledge Representation and Reasoning , Human-AI Interaction , and Experimental Methodology in high-energy physics. Research interests span Artificial Intelligence , Autonomous Agent Systems , and Scientific Modeling . His studies analyze diagrammatic representations in collaborative particle physics experiments, inductive risk in ML modeling, and robustness in experimental results. Recent publications explore experimental robustness , Higgs mechanism epistemology , and ethical frameworks for AI . His work combines Physics , Machine Learning , and Philosophical Analysis , addressing challenges in theory-ladenness , data acquisition , and interdisciplinary collaboration . Karaca’s contributions include developing design thinking frameworks for AI systems and evaluating scientific unification across physics domains. His studies on binary classification models highlight the societal implications of technical decisions in machine learning.
دانشیار
Vijay Mago is Chair and Associate Professor of Computer Science at Lakehead University, Canada, and Associate Professor at York University's School of Health Policy and Management since 2015. He holds a Ph.D. in Computer Science from Panjab University, India (2010). Education: Ph.D. in Computer Science, Panjab University, India (2010) His research integrates artificial intelligence, machine learning, and natural language processing to address complex societal challenges including homelessness, obesity, and crime through health informatics, medical decision support, and Bayesian intelligence. Current work emphasizes modeling complex health systems and social networks using big data analytics. Recent publications reveal strong interdisciplinary trends applying AI to public health crises (notably COVID-19 modeling) and political/social media analysis, with consistent focus on ethical considerations, system resilience, and narrative shaping in digital environments. Dr. Mago serves as Associate Editor for IEEE Access and BMC Medical Informatics and Decision Making, demonstrating significant editorial contributions to his fields. He previously contributed to the Modeling of Complex Social Systems Program at Simon Fraser University's IRMACS Centre starting in 2011, establishing foundational work for his current research trajectory.
