Florina Piroi is a Senior Researcher at the Technische Universität Wien (TU Wien), affiliated with the Faculty of Informatics and the Department of Data Science. She holds the role of Senior Scientist in Data Science and is a Substitute Member of the Curriculum Commission for Business Informatics. Her primary research focuses on information retrieval, medical informatics, natural language processing, and patent text mining. She leads projects such as the CLEF-IP evaluation lab and contributes to initiatives like the DoSSIER and OS Trails research programs. Key research interests include longitudinal evaluation of machine learning models, reproducibility in NLP tasks, and knowledge graph applications in manufacturing. She has supervised PhD student Anindita M. Ningtyas, whose work addresses medical terminology accessibility for laypeople. Piroi collaborates on interdisciplinary projects, such as designing health datasets from medical forums and improving search systems for evolving corpora. Her notable contributions include benchmarking frameworks for IR systems, semantic translation tools for industry, and methods for analyzing electrical systems. She has published over 50 peer-reviewed articles in venues like SIGIR, CLEF, and ECIR, emphasizing practical applications in both academic and industrial contexts.
Danai Symeonidou is a Researcher (CR) at INRAE in Montpellier since 2015, working in the GAMMA team. She holds a PhD from University Paris Sud (2014) and a joint Greek-French Master's degree from the University of Crete and University Paris Sud. Her research focuses on Semantic Web technologies, key discovery in knowledge bases, rule mining, and descriptive analytics. She has conducted postdoctoral research at Telecom ParisTech and was a visiting researcher at the Insight Centre for Data Analytics in University College Cork, Ireland. Education includes a Bachelor's degree from the University of Macedonia (2009), followed by advanced studies in France. She has extensive teaching experience across multiple institutions, including courses on Discrete Mathematics, Relational Databases, UML, Algorithms, and Semantic Web topics. Her work emphasizes scalable solutions for data linking and key discovery, with contributions to RDF data analysis, knowledge base optimization, and agrifood chain modeling. She has published widely in top venues such as ISWC, K-Cap, and EKAW, focusing on theoretical foundations and practical applications of semantic web technologies.
Constantine Kotropoulos is a Professor at the Department of Informatics, School of Informatics, Aristotle University of Thessaloniki. He holds a PhD (1993) and a Diploma in Electrical Engineering (1988), both from Aristotle University. His professional journey includes roles from Lecturer (1997) to current Professor (2015–present), with extensive postdoctoral and research experience in electrical and computer engineering fields. His research focuses on Digital Signal Processing , Audio/Music/Speech Processing , Pattern Recognition , and Human-Centered Multimodal Interaction . Recent work emphasizes forensic applications (e.g., source device identification), medical diagnostics (speech pathology classification), and explainable AI (face aging, camera model identification). Key research themes include electric network frequency analysis for audio authentication, multimodal fusion for media forensics, and optimization techniques for non-negative machine learning problems. His publications span signal processing, multimedia, and healthcare technology, with a focus on practical applications of advanced algorithms. He maintains active collaborations in interdisciplinary areas such as agricultural disease detection via hyperspectral imaging and route recommendation systems leveraging image-driven data. His work often bridges theoretical computer science with real-world challenges in security, healthcare, and environmental monitoring.
Chuan Chen is a researcher at the Technical University of Munich , affiliated with the Chair of Cartography and Visual Analytics . His work focuses on the intersection of Geospatial Artificial Intelligence (GeoAI) , Explainable AI (XAI) , Causal Inference , and Visual Analytics , aiming to improve the interpretability and policy relevance of spatial modeling. Research Interests include responsible AI applications in urban contexts, population distribution modeling, and frameworks for transparent decision-making using geospatial analysis. His studies emphasize ethical AI, causal mechanisms, and spatial representation. Recent publications highlight his contributions to geospatial modeling, AI ethics narratives, and urban sustainability. He applies explainable AI to frozen ground analysis, population distribution predictability, and AI risk decoding from news data. Teaching includes courses like Image Analysis for Mapping (M.Sc., since 2022) and Mapping for a Sustainable World (M.Sc., 2023 Summer). He supervises master theses and seminars on AI ethics and global-scale visual analysis.
Byron C. Wallace is a prominent researcher in Natural Language Processing with a focus on biomedical and clinical applications . His work spans model distillation, factuality evaluation, and medical text simplification. Key contributions include developing methods for tracing teacher models in distillation and creating benchmarks like FactPICO and RedHOT. Research interests include LLM interpretability , medical evidence synthesis , and cross-modal alignment in clinical NLP His recent publications analyze syntactic template repetition in LLMs, token erasure effects , and definition-augmented biomedical NER Wallace's work has advanced zero-shot summarization techniques, pharmacovigilance automation , and patient data privacy analysis in clinical models. Current projects explore chain-of-thought distillation , multilingual medical simplification , and interpretable feature extraction from EHR data. Key collaborators include researchers from institutions like Allen Institute for AI, MIT, and various biomedical NLP teams. His methodological innovations in instance attribution , data augmentation , and counterfactual reasoning have influenced modern NLP research paradigms.
Mathilde Joncheray is a Lecturer in Human Geography at Université Toulouse Jean-Jaurès, affiliated with the Interdisciplinary Laboratory for Solidarity, Societies, Territories (LISST). Her career includes positions as a high school teacher (2013-2015) and PRAG at the University of Pau and the Adour Region (2015-2020). She holds a PhD in Geography (2013) from Aix-Marseille University, with research focusing on territorial transformations in post-conflict contexts. Her research explores: Conflicts, post-conflict reconstruction, and resilience in territories Geopolitics of development in Sub-Saharan Africa (Niger, Mali, Congo, Ivory Coast) Cartography, GIS, and digital knowledge dissemination Gender disparities in scientific representation (e.g., Wikipedia projects) Her publications emphasize African territorial dynamics, conflict geography, and digital epistemology, with recent work analyzing gender bias in collaborative knowledge platforms. She leads projects like WIKIF (Wikipedia and women scientists) and AVALSUD (banana supply chains). She has contributed to international development programs including the EU-funded PIP Sugar project and advised the Congolese government on GIS-based social registries.
Professor Mizuho Iwaihara is affiliated with Waseda University's Faculty of Science and Engineering and Graduate School of Information, Production, and Systems. Her research focuses on database systems, web information retrieval, text mining, security/privacy, and social media analysis. She has led significant projects on Wikipedia edit history analysis, knowledge graph construction, and privacy-preserving frameworks. Key research areas: Database Query Processing, Web Information Systems, Text Mining, Knowledge Management, Social Media Her recent publications address semantic analysis of collaborative content, topic evolution tracking, and privacy behavior modeling. Over 85 papers with 349 citations reflect her impact in database and social media research. Scientific achievements include: Best Demo Award (2014) for WikiReviz Best Paper Award (2008) at IFIP e-Business Conference EC-Web2006 recognition Grants from Japan Society for the Promotion of Science (JSPS) span multiple projects on knowledge graph development, social content analysis, and privacy-preserving systems. She supervises numerous graduate students and leads the Data Engineering Laboratory at Waseda University.
Szymon Olewniczak serves as an Assistant lecturer and Deputy Head of Department at the Department of Computer Architecture within the Faculty of Electronics Telecommunications and Informatics at Gdańsk University of Technology. His academic career is focused on natural language processing and related computational linguistics fields. His educational background includes: Master of Engineering (mgr inż.) in Technical Informatics and Telecommunications from Gdańsk University of Technology (2019-07-12) Engineer (inż.) in Technical Informatics and Telecommunications from Gdańsk University of Technology (2018-02-02) Olewniczak's research primarily centers on natural language processing with specific expertise in entity linking, named entity recognition, and information retrieval systems. His work demonstrates a strong focus on practical applications of NLP techniques, particularly in creating systems that bridge natural language with structured knowledge bases like Wikipedia. He has developed innovative approaches to word embeddings, question answering systems, and domain-specific information retrieval. His publication record shows consistent research output from 2020 through 2025, with a notable emphasis on improving entity linking systems, developing specialized datasets, and applying neural network techniques to text analysis tasks. Recent work includes creating a gold standard multi-genre dataset for entity recognition and developing question answering systems for technical documentation. As Deputy Head of Department, Olewniczak contributes to academic administration while maintaining an active research profile. His work bridges theoretical NLP concepts with practical implementations, particularly in the information technology domain.
Shilad Sen is a Professor and Chair of Computer Science at Macalester College in St. Paul, Minnesota, with a concurrent position as Principal Scientist at Microsoft. His academic appointment is within the Mathematics, Statistics, and Computer Science (MSCS) Department at Macalester College. Professor Sen's research focuses on member-maintained websites that empower Internet users to contribute valuable information, with particular emphasis on tagging systems, recommender systems, and combinations of the two. His work draws upon the fields of Human-Computer Interaction (HCI), data-mining, psychology, and computer systems design. He has made significant contributions to understanding geographic barriers in Wikipedia content and developing systems that help users better contribute to online communities. His research trajectory shows a consistent focus on understanding how people interact with information systems and how to design better systems that support community knowledge building. His work spans both theoretical contributions to understanding online communities and practical system development, including projects like Cartograph, Localness, WikiBrain, and Macademia. His recent work at Microsoft focuses on developing AI systems for products like Microsoft Outlook. Professor Sen teaches a wide range of computer science courses including Object-Oriented Programming and Data Structures, Internet Programming, and Collective Intelligence. His research has been published in top-tier venues including CHI, with his 2015 paper 'Barriers to the Localness of Volunteered Geographic Information' being particularly influential in understanding geographic inequalities in Wikipedia content. BA in Mathematics from Northwestern University (1999) BM in Saxophone Performance from Northwestern University (1999) PhD in Computer Science from University of Minnesota (2009) Before his academic career, Sen worked at Sourcelight Technologies building movie recommenders for companies like Blockbuster Video and Comcast, and also had positions at Google, IBM Research, Thomson Reuters R&D, and Target Corporation. Outside of academia, he is an avid jazz saxophonist and squash player.
Nicolas Heist is a Researcher at the University of Mannheim's Data and Web Science Group. His work focuses on Semantic Web Technologies, Knowledge Graphs, Linked Data, and their applications in data mining and social media analysis. He has contributed to projects such as CaLiGraph, a knowledge graph derived from Wikipedia categories and list pages, and has organized exercises for Data Mining I and II courses since 2018. He actively participates in academic conferences, serving as a Program Committee (PC) member for multiple International Semantic Web Conferences and Extended Semantic Web Conferences between 2020 and 2023. His research emphasizes the intersection of knowledge representation and practical applications, including improving interaction with knowledge graphs via embeddings and analyzing social media trends like vegan communities on Instagram. Heist has received several recognitions, including the Outstanding Reviewer Award at ESWC 2022 and a challenge win at SemREC 2021. He supervises student projects exploring topics like knowledge graph development for tax regulations and bot development for Wikipedia maintenance.
Suzanne Mills is an Associate Professor in the School of Labour Studies at McMaster University, where she adopts a spatial lens to study identity, work, and labour unions. Her research examines multiple dimensions of work and organizing in northern and underdeveloped regions, with a particular focus on resource extraction industries and the experiences of marginalized workers. Bachelor of Science (with great distinction) Wildlife Biology, McGill University Master of Science Conservation Biology, University of Alberta PhD Human Geography, University of Saskatchewan SSHRC Postdoctoral Fellow, Queen's University Mills' research spans several interconnected areas including gender and northern resource development, Indigenous peoples' work and union experiences, and LGBTQ+ worker experiences. She examines how colonial and gender relations structure employment in mining, forestry, and hydro-development, and has increasingly focused on queer and trans workers in deindustrializing cities. Her community-engaged approach involves partnerships with Indigenous communities, LGBTQ+ organizations, worker centers, and trade unions. Recently, she has explored post-COVID migration to resource peripheries through the lenses of technological transformations in work, uneven development, and struggles for social reproduction. Her scholarly output demonstrates a clear evolution from studying northern resource development and Indigenous employment toward increasingly intersectional analyses incorporating gender, sexuality, and colonial relations. Recent publications focus heavily on LGBTQ+ worker experiences, particularly examining discrimination, mental health, and labor market dynamics, while maintaining connections to her earlier work on spatial dimensions of work and resource extraction industries. This trajectory reflects growing scholarly attention to the complex interplay between identity, geography, and labor markets. Mills has demonstrated significant impact through media coverage of her research, including features in McMaster's Faculty of Social Sciences on topics like "Queer and trans workers disproportionately represented in precarious work" and "Survey reveals huge gaps in LGBTQ+ support in Hamilton." Her work has been referenced in policy sources, Wikipedia, and picked up by multiple news outlets, indicating real-world relevance and application of her research findings. Mills practices community-engaged research methodology, working directly with affected communities and organizations rather than conducting research on them. This approach is evident in her numerous reports and policy-relevant publications developed in partnership with Indigenous communities, LGBTQ+ organizations, and worker centers. Her teaching portfolio includes courses such as Work and the Environment, Advanced Labour Studies Theory, and Geographies of the North American Political Economy, reflecting the interdisciplinary nature of her scholarship.
Jon Beasley-Murray is an Associate Professor of Spanish at the University of British Columbia (UBC), affiliated with the Department of French, Hispanic and Italian Studies within the Faculty of Arts. He holds a Ph.D. from Duke University. His research focuses on Latin American cultural, literary, and political history, with particular attention to the Latin American left, social movements, and colonial maritime networks. Beasley-Murray’s work integrates continental philosophy (Deleuze, Bourdieu) and Italian social theory (Antonio Negri) into analyses of globalization, cultural studies, and Marxist theory. His publications include the influential Posthegemony (2010) and co-edited volumes on Latin America’s left turns and new Latin Americanism. Recent work explores narcoliterature, pandemic narratives, and ecocritical studies of Andean landscapes. He advocates interdisciplinary approaches and open-access scholarship, such as using Wikipedia in teaching. Teaching responsibilities include courses on Spanish and Latin American studies at UBC. While no specific grants or advising records are detailed, his academic profile reflects sustained engagement with political theory, cultural critique, and Latin America’s socio-historical transformations. No lab affiliations or teams are explicitly mentioned in the provided texts.
Philippe Langlais is a Full Professor at the University of Montreal's Department of Computer Science and Operational Research (DIRO), specializing in Natural Language Processing (NLP). He holds affiliations with research units like the Applied Research Laboratory in Computational Linguistics (RALI) and the Centre de Recherche Interuniversitaire sur les Humanités Numériques (CRIHN). His academic journey includes a PhD from the University of Avignon (1995) and postdoctoral work at IDIAP in Switzerland and KTH in Sweden. Education: PhD in Computer Science, Université d'Avignon (1995) Research Interests: Machine translation, machine learning, analogical learning, computer-assisted translation, morphology acquisition, and NLP applications in judicial and medical contexts. Projects: Principal investigator for initiatives like 'BUMP: Better Understanding of Model’s Performance' and collaborator on large-scale projects such as UNIQUE (Neuroscience & AI) and CRIHN. His work involves developing NLP tools for aviation safety reports, legal texts, and healthcare diagnostics. Awards/Grants: Secured funding from CRSNG, FRQSC, MITACS, and industry partners. Recent grants include 'Revue3.0' (2024-2032) and 'Union Neurosciences et Intelligence Artificielle Québec (UNIQUE)' (2022-2029). Labs/Teams: Leads RALI and contributes to CRIHN, focusing on interdisciplinary applications of NLP in humanities and computational linguistics.
Satoshi Sekine is a Research Professor in the Computer Science Department at New York University (NYU), affiliated with the Proteus Project. His roles include Research Associate Professor since 2007, with prior positions as Assistant Research Professor and Research Scientist at NYU since 1994. He holds a Ph.D. in Computer Science from NYU (1998), an M.Sc. from the University of Manchester Institute of Science and Technology (1992), and a B.Sc. from Tokyo Institute of Technology (1987). His research focuses on Natural Language Processing (NLP), including information extraction, syntactic analysis, and knowledge discovery from corpora. Key projects include On-Demand Information Extraction (ODIE), Extended Named Entity (ENE) systems, and Web People Search (WePS) tasks. He has organized major conferences like HLT-NAACL 2006 and contributed to initiatives such as the IREX evaluation project. Publications span topics like neural entity classification, dependency parsing, and cross-lingual NLP. He has supervised PhD students Kiyoshi Sudo and Yusuke Shinyama, and led collaborations with companies like Fujitsu, NEC, and NHK. Grants include NSF funding for projects like On-Demand Information Extraction ($2M, 2003-2008). He serves as a program chair for ACL and ANLP conferences, reviews for top journals, and advises PhD committees. His work integrates linguistic theories with practical NLP applications, emphasizing evaluation-driven research and cross-lingual systems.
Sandro Pedrazzini is an Adjunct Professor in Software Engineering and the Head of the Bachelor's Program in Computer Engineering at the Department of Innovative Technologies (DTI) of SUPSI. He holds an M.Sc. in Computer Science from ETH Zurich and a Ph.D. in Natural Sciences from the University of Basel. His research focuses on Software Engineering methodologies, Programming Languages, Natural Language Processing, and Information Retrieval. He has extensive experience in both academia and industry, co-founding companies like Canoo AG and Karakun AG. His teaching responsibilities include courses on computer graphics, programming paradigms, and software engineering practices. Research Interests: Software Engineering: Agile methodologies, continuous integration, and project-based learning Natural Language Processing: Term extraction, morphological analysis, and e-learning tools Web Technologies: 3D interfaces, enterprise systems, and middleware architectures Publications reflect a blend of theoretical and applied research, with contributions to enterprise search systems, semantic analysis, and educational technologies. His work emphasizes practical applications of academic research in real-world contexts. Professional Experience: Co-founder of Canoo AG (2000) and Karakun AG (2018) Head of Computer Science Bachelor Program since 2012 Supervisor for multiple academic projects and courses Labs/Teams: Active in SUPSI’s DTI department, leading projects like 3D MMA (3D interface design) and TicinoTurismo II (web-based tourism platform).
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