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Klim ZaporojetsView profile

Research Fellow

• Natural Language Processing
• Information Extraction
• Entity Linking
• +3 more

Klim Zaporojets is a Marie Skłodowska-Curie Postdoctoral Fellow in the Department of Computer Science at Aarhus University, where he conducts research within the Data-Intensive Systems Group. His work bridges theoretical advancements and practical applications in natural language understanding. His research focuses on information extraction systems that connect textual content with structured knowledge bases. His methodology emphasizes leveraging external knowledge sources to enhance information extraction performance, particularly in document-level contexts where entities evolve over time. His work spans temporal relation extraction, entity linking, and biomedical text mining applications. The publication record reveals a strong focus on document-level information extraction with increasing emphasis on temporal aspects and knowledge integration. Recent work explores large language model applications for graph learning and calibration challenges in LLMs, showing evolution from traditional NLP tasks to cutting-edge foundation model research. His publications appear in top-tier venues including ACL, EMNLP, CIKM, and NeurIPS. His scientific recognition includes the prestigious Marie Skłodowska-Curie Postdoctoral Fellowship, supporting his research at Aarhus University. His work has produced several influential datasets including DWIE, TempEL, and BioDEX that have become benchmarks in document-level information extraction. Zaporojets maintains active collaborations with researchers at Ghent University (evidenced by his ugent.be email address) and has contributed to multiple interdisciplinary projects spanning computational linguistics, healthcare informatics, and knowledge representation. His technical contributions include open-source implementations of his research, demonstrating commitment to reproducible science.

• Video Coding for Machines
• Neural Network-Based Video Processing
• Immersive Video Coding
• +5 more

Professor Marek Domański is a distinguished faculty member at Poznań University of Technology, holding the position of Professor at the Institute of Multimedia Telecommunications within the Faculty of Computing and Telecommunications. With over four decades of academic career since completing his dissertation in 1983, he has established himself as a leading researcher in video coding and processing. His research primarily focuses on advanced video coding techniques, particularly Video Coding for Machines (VCM), neural network applications in video processing, immersive video coding, and multiview video compression. Professor Domański has made significant contributions to the field through his extensive publication record and active participation in international standardization efforts, particularly at MPEG meetings. Analysis of his recent publications (2020-2025) reveals a strong emphasis on machine-oriented video coding, with numerous contributions to MPEG standardization activities. His work demonstrates a consistent evolution from traditional video coding toward specialized techniques for machine vision applications, incorporating artificial neural networks to improve coding efficiency and processing capabilities. As an academic supervisor, Professor Domański has guided 27 doctoral students to completion, with recent dissertations focusing on cutting-edge topics in video processing and coding. His research group at PUT maintains active international collaborations, particularly with South Korean institutions like ETRI, reflecting the global relevance of his work. Professor Domański's research has practical applications in virtual reality, free-viewpoint television, and machine vision systems, with numerous technical reports indicating ongoing research projects focused on improving machine vision coding techniques. His work bridges theoretical advances with practical implementations, contributing significantly to both academic knowledge and industry applications in video technology.

• Nature-Society Relations
• Climate Change
• Political Ecology
• +8 more

Dylan M. Harris, PhD is an Assistant Professor in the Department of Geography & Environmental Studies at the University of Colorado Colorado Springs, within the College of Letters, Arts, & Sciences. His academic work bridges geography, environmental studies, and critical theory with a focus on innovative approaches to understanding socioecological challenges. Dr. Harris's research interests span Nature-Society Relations, Climate Change, Political Ecology, Storytelling, Environmental/Climate Justice, Cultural Geography, and Critical Physical Geography. His work explores how narrative frameworks shape our understanding of environmental crises and social issues, with particular attention to experimental methodologies that push disciplinary boundaries. His recent publications demonstrate a consistent scholarly output across multiple high-impact geography and environmental studies journals. His research trajectory shows increasing focus on the intersections between student debt as a socioecological issue, climate justice, and innovative storytelling approaches to environmental challenges. He has developed a distinctive voice in political ecology that emphasizes experimental and speculative approaches. University of Colorado Colorado Springs, Green Action Fund Research Seed Grant (2022) University of Colorado Colorado Springs Office of Research, Committee on Research and Creative Works Seed Grant (2021) National Science Foundation Geography and Spatial Sciences Doctoral Dissertation Research Improvement Award (2019) The Robert and Patricia Switzer Foundation Environmental Leadership Fellowship (2018) Edna Bailey Sussman Fund Environmental Fellowship (2018) Dr. Harris teaches courses including Introduction to Environmental Studies & Sustainability, World Regional Geography, Nature & Society, and Global Climate & Environmental Change. He serves in multiple university roles including Green Action Fund Faculty Advisor, Committee on Research and Creative Works Grant Reviewer, and Campus Sustainability Committee member. His community engagement extends beyond campus through work with The Chinook Center and the Honcho Campout queer music festival, reflecting his commitment to connecting academic work with community-based action.

Marie-Christine ROUSSETView profile

Professor

• Knowledge Representation
• Information Integration
• Ontology-based data access
• +7 more

Marie-Christine ROUSSET is a Professor of Computer Science at the University of Grenoble Alpes (UGA) in France, where she is a member of the LIG (Laboratoire d'Informatique de Grenoble) in the SLIDE group. Previously affiliated with Paris-Saclay (LRI), she has established herself as a leading researcher in Knowledge Representation and Information Integration. She holds the distinguished position of Senior member of the Institut Universitaire de France (IUF) (2011-2016, renewed for 2016-2021) and serves as co-responsible for the chair Explainable and Responsible AI within MIAI Grenoble Alpes. Her research focuses on ontology-based data access, logic-based mediation between distributed data sources, query rewriting using views, data linkage, and distributed reasoning for the Semantic Web. She skillfully combines artificial intelligence and database techniques to address complex information integration challenges, with applications spanning biomedical informatics, educational technology, and trustworthy AI. Her work demonstrates consistent innovation from foundational research to practical implementations, as evidenced by her co-authorship of the book 'Web Data Management' published by Cambridge University Press. Professor ROUSSET's recent publications (2019-2022) reveal a growing emphasis on data privacy, RDF graph anonymization, and interactive ontology engineering, while maintaining her strong contributions to semantic web technologies and knowledge representation. Her research shows increasing attention to trustworthy AI concerns, aligning with her leadership roles in relevant projects. Scientific Recognition Senior member of Institut Universitaire de France (IUF) (2011-2016, renewed for 2016-2021) Junior member of Institut Universitaire de France (IUF) from 1997 to 2002 Chevalier de l'Ordre National du Merite (July 11, 2011) EurAI Fellow (nominated ECCAI Fellow in 2005) Best Paper Award at AAAI'96 for 'Verification of Knowledge Bases based on Containment Checking' Professor ROUSSET maintains an active role in the scientific community through editorial work and organizational leadership. She serves on the Editorial Board of Communications of the ACM (CACM) and has held significant roles including PC chair of EGC 2019, Workshops co-Chair of WWW 2018, and Area Chair of IJCAI 2017. Her consistent service on program committees of major international conferences demonstrates her standing in the field. Her laboratory, the SLIDE group within LIG, focuses on semantic web technologies, knowledge representation, and data integration. The group maintains strong connections with the international research community and participates in collaborative projects addressing cutting-edge challenges in artificial intelligence and data management, with particular emphasis on trustworthy and explainable AI systems.

Ange Adrienne Nyamen TatoView profile

Assistant Professor

• Artificial Intelligence in Education
• Generative AI for Education
• Machine Learning Algorithms
• +7 more

Ange Adrienne Nyamen Tato serves as an Assistant Professor in the Department of Teaching and Learning Studies at Laval University's Faculty of Education. Her academic journey spans multiple institutions across Canada and Morocco, with a strong interdisciplinary background combining computer science, artificial intelligence, and educational theory. PhD in Computer Science (Artificial Intelligence) from University of Quebec at Montreal (UQAM), 2020 Master's degree in Computer Science from University of Quebec at Montreal (UQAM), 2015 Engineering degree in Information Systems from Mohammedia School of Engineers in Morocco, 2014 DEUST in Mathematics, Computer Science and Physics from Hassan II University, Morocco, 2011 Professor Tato's research focuses on the intersection of artificial intelligence and education, with particular expertise in generative AI applications for educational contexts, machine learning algorithms, intelligent tutoring systems, educational data mining, and serious game design. Her work addresses critical challenges in educational technology including transparency, assessment practices, and engagement issues that have limited the adoption of AI-powered learning tools. She is particularly interested in the ethical implications, environmental impact, and potential biases of AI in educational settings. Her recent publications demonstrate a consistent focus on developing sophisticated models for user behavior prediction, adaptive learning systems, and integrating pedagogical knowledge into AI frameworks. The research spans multiple domains including logical reasoning development, socio-moral reasoning, piloting training, and general educational applications of deep learning and knowledge tracing techniques. Professor Tato has secured significant research funding, including a $192,500 NSERC Discovery Grant for her project 'Optimizing Generative Artificial Intelligence for Education: Towards a Holistic Approach Integrating Teachers and Learners.' This five-year project aims to develop pedagogically aware large language models (PA-LLMs) that better serve educational purposes by integrating educational theories, human learning factors, and bias correction mechanisms. Principal Investigator for NSERC Discovery Grant ($192,500 over 5 years) PC Member for ICCE 2023 and 2024 conferences PC Member for EDM 2024 conference PC Member for AIED 2024 conference Professor Tato teaches graduate courses including TEN-7028 Games and Learning and TEN-7030 Digital Intelligence in Education: Opportunities and Challenges. She is currently accepting Master's students interested in AI applied to education. Her previous professional experience includes work as an Artificial Intelligence Specialist at Beam Me Up Augmented Intelligence (2018-2022) and a postdoctoral fellowship in Deep Learning applied to aeronautics in partnership with Bombardier and CAE (2020-2022).