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Karsten DonnayView profile

Assistant Professor

• Digital Democracy
• Political Behavior
• Computational Social Science
• +3 more

Karsten Donnay is an Assistant Professor of Political Behavior and Digital Media at the University of Zurich's Department of Political Science, affiliated with the Digital Society Initiative. Previously, he held positions at the University of Konstanz and ETH Zurich. He earned his PhD in Computational Social Science from ETH Zurich and conducted postdoctoral research at the Graduate Institute Geneva and the University of Maryland. His research focuses on digital democracy, examining how digital technologies reshape political behavior, communication, and democratic processes. Key areas include media bias, hate speech mitigation, and the impact of digitalization on political participation. He leads projects like 'Improving Public Discourse' (funded by the Swiss National Science Foundation) and 'StopHateSpeech,' and co-developed software tools for data analysis and visualization. Teaching responsibilities include courses on digital democracy, conflict in the digital age, and digital transformation. He collaborates across disciplines, serving on the executive board of the University of Zurich's Population Research Center and contributing to initiatives like the DigiVox survey panel on digitalization's societal impacts.

• Natural Language Processing
• Computational Linguistics
• Language Model Interpretability
• +7 more

Anna Rogers is a leading researcher in Natural Language Processing (NLP), known for her foundational and critical work on language model interpretability, dataset quality, and the ethics of AI systems. She has published extensively at top-tier venues including ACL, EMNLP, and NAACL, often collaborating with prominent researchers like Anna Rumshisky and Isabelle Augenstein. Her research interests center on data curation , model generalization , responsible data use , and transparency in large language models . She has conducted influential surveys on community perspectives regarding intelligence in AI and has contributed to improving peer review practices in NLP conferences. Her work on BERTology, including papers like A Primer in BERTology and Revealing the Dark Secrets of BERT , has become key reading in the field. Recent publications highlight her focus on data transparency (e.g., the ROOTS Search Tool), synthetic content detection , and temporal annotation frameworks like NarrativeTime. She also investigates the robustness of models, probing techniques, and the limitations of current benchmarks. Her work consistently emphasizes methodological rigor and ethical considerations in NLP research. She has advocated for better data practices and more thoughtful evaluation paradigms across the community. Natural Language Processing Computational Linguistics Language Model Interpretability Dataset Curation and Quality Ethics in NLP Peer Review in Academic Conferences Anna Rogers has played a key role in shaping meta-discussions in the NLP field, including peer review reform and the societal impact of language technologies. She has co-organized workshops on negative results and contributed to tutorials on reviewing and data use. Her work bridges technical depth with critical reflection on the direction of the field. She has advised or collaborated with numerous researchers, though specific students are not listed in the available data. She has not received any explicitly mentioned scientific awards in the provided text. Anna Rogers leads or contributes to several open-source initiatives and shared resources, including the DECAF framework, the ROOTS Search Tool, and various datasets such as TimeBankNT and RuSentiment. Her work often includes released code and tools to promote reproducibility and further research.

Robert FrederkingView profile

Researcher

• Machine Translation
• Computational Linguistics
• Multilingual Information Processing
• +5 more

Robert Frederking is an Associate Dean for PhD Programs and Chair of the Master of Language Technologies program at Carnegie Mellon University's Language Technologies Institute (LTI), part of the School of Computer Science (SCS). With over three decades at CMU, he holds a PhD in Computer Science , specializing in machine translation and computational linguistics . Education : PhD in Computer Science, Carnegie Mellon University Research Interests : Advancing machine translation for low-resource languages Developing speech-to-speech translation systems (Tongues, NineOneOne projects) Building named entity recognition tools for defense applications Creating translingual information retrieval frameworks Designing multilingual processing architectures Scientific Awards : Allen Newell Award for Research Excellence Leadership & Grants : Principal Investigator for NSF KDI Universal Access project Co-PI for NSF/EU Muchmore project Organizer of JGC60 Celebration Representative to NSF-funded LEAP Alliance Labs & Teams : Founding member of CMU's Language Technologies Institute Contributor to evolution of Center for Machine Translation into LTI Key member of Dolphin Communication Project Participant in AMTA leadership (2004-2008)

Piek VossenView profile

Professor

• Computational Linguistics
• WordNets
• Natural Language Processing
• +2 more

Prof. Piek Vossen is Full Professor of Computational Lexicology at Vrije Universiteit Amsterdam, heading the Computational Lexicology & Terminology Lab (CLTL). A Spinoza Laureate (2013) and Knight in the Order of the Dutch Lion (2015), his research integrates computational linguistics, WordNets, and conversational AI. He co-founded the Global WordNet Association and leads projects including 'Make Robots Talk', 'Dutch FrameNet', and the Hybrid Intelligence Centre. Key research areas: Multilingual semantic networks and ontologies Cross-lingual language modeling Conversational agents and social robots Event extraction and perspective analysis Computational analysis of discourse and argumentation His recent work focuses on toxicity analysis in online discourse, medical language models, and hybrid intelligence systems that combine human and machine capabilities.

• Responsible AI
• Software Engineering
• Machine Learning
• +3 more

Mr. Boming Xia is a Research Fellow at the Responsible AI Research Centre (RAIR) and the Australian Institute for Machine Learning (AIML), University of Adelaide. He holds a position within the Faculty of Sciences, Engineering and Technology. His research focuses on advancing responsible and safe AI through a software engineering lens, particularly exploring the integration of system-level practices with machine learning approaches. His work emphasizes ethical AI development, including frameworks for risk assessment, ESG (Environmental, Social, Governance) integration, and blockchain-based accountability mechanisms. Key areas of interest include AI safety, privacy protection in generative AI, and the design of transparent software supply chains using tools like SBOM (Software Bill of Materials). Xia's contributions span empirical studies on SBOM adoption, AI system evaluation frameworks, and tools like CDCAT for cross-document entity and event coreference. His research bridges theoretical AI foundations with practical software engineering methodologies to ensure AI systems are both innovative and ethically grounded.

• Information Retrieval
• Natural Language Processing
• Dialogue Systems
• +10 more

Prof. Dr. Udo Kruschwitz is a Full Professor of Information Science at the University of Regensburg since July 2019. Previously, he held a professorship at the School of Computer Science and Electronic Engineering, University of Essex. His research bridges Information Retrieval (IR) and Natural Language Processing (NLP), focusing on adaptive search systems, dialogue modeling, gamification for annotation, and ethical issues in search technology. Key projects: COURAGE (Volkswagen Stiftung-funded virtual companion for social media safety), SENSEI (Horizon 2020 conversational analytics), and collaborative works with industry (Signal Media, Minority Rights Group). Research themes include: IR/NLP integration Conversational systems Gamified annotation platforms (Phrase Detectives) Arabic language resources Privacy-preserving search strategies His publications span query suggestion algorithms, crowdsourcing validation techniques, and hate speech detection. He has co-organized major events like Search Solutions and GamifIR workshops, and founded the Data Science @ Regensburg meetup. Scientific awards include the 2015 InnovateUK Knowledge Transfer Partnership Project of the Year. Current teaching includes Advanced Topics in IR and Natural Language Engineering modules. Serves as Senior Academic Advisor for Signal AI and mentor for numerous doctoral candidates.

Mark SteedmanView profile

Professor

• Computational musical analysis
• Computational linguistics
• Combinatory logic
• +6 more

Mark Steedman is a Professor of Cognitive Science at the School of Informatics , University of Edinburgh, and an Adjunct Professor in the Department of Computer and Information Science at the University of Pennsylvania. His research bridges Artificial Intelligence , Cognitive Science , and Computational Linguistics , with a focus on Combinatory Categorial Grammar (CCG) , Prosody and Intonation , and Temporal Semantics . He has led the Institute for Language, Cognition, and Computation and contributed to interdisciplinary research at the Human Communications Research Center and Centre for Speech Technology Research . Research Interests : Steedman's work explores the intersection of formal grammar, computational models, and cognitive processes. He investigates how CCG parsing can enhance semantic inference, how prosodic features improve speech processing, and the role of temporal semantics in language understanding. His projects often integrate language models with entailment graphs for question answering and dialogue systems. Scientific Awards : Fellow of the American Association of Artificial Intelligence (1993) Fellow of the Royal Society of Edinburgh (2002) Fellow of the British Academy (2002) Member of Academia Europaea (2006) Best Paper Awards at ACL 2023 and AACL/IJCNLP 2023 Influential Paper Award (IFAAMAS 2017) Recent Trends in Publications : His recent work emphasizes language models for semantic inference , entailment graphs in multilingual settings, and incremental parsing for brain-language interfaces. Papers address challenges in hallucination , cross-lingual transfer , and prosody-text alignment .

Erdem YörükView profile

Professor

• Social Welfare and Social Policy
• Social Movements
• Political Sociology
• +2 more

Erdem Yörük is a Professor in Sociology at Koç University , with additional affiliations as Associate Member at the University of Oxford's Department of Social Policy and Intervention, and Affiliated Faculty at the Ford Institute of Human Security (University of Pittsburgh, Central European University). As Director of the Center for Computational Social Sciences at Koç University, he leads major research initiatives including the ERC-funded projects Emerging Welfare and Politus , along with the H2020 Social Comquant project. Ph.D. in Sociology from Johns Hopkins University (2012) M.A. in Sociology from Johns Hopkins University (2009) M.A. in Sociology from Boğaziçi University (2006) B.Sc. in Electrical and Electronics Engineering from Boğaziçi University (2002) His research integrates Computational Social Sciences with Political Sociology to analyze the interplay between Social Movements and Welfare Policy . Current work focuses on creating cross-national datasets ( Global Welfare Dataset (GLOW) and Global Contentious Politics Database (GLOCON) ) to explore how governments utilize social assistance as both Mobilization and Containment mechanisms in response to grassroots political activity. Major findings from his publications in journals like World Development , Governance , and Politics & Society demonstrate that Emerging Market Economies have developed distinct Populist Welfare State Regimes through interactions between Structural Pressures , Institutional Frameworks , and Political Agency . Notable among these is his 2022 book The Politics of the Welfare State in Turkey (University of Michigan Press), which presents a political explanation for Turkey's shift from employment-based social security to poverty-targeted assistance. He has organized EU-funded Training Workshops on topics including Social Media Data Research , Network Analysis with R , and Digital Trace Data applications. His methodological contributions span Random Sampling techniques for protest event coding, Multilingual Annotation protocols, and Machine Learning Integration with expert rule systems.

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.

Leander HeldringView profile

Associate Professor

• Economic Development
• Political Economy
• Economic History
• +4 more

Leander Heldring is an Associate Professor of Managerial Economics & Decision Sciences at the Kellogg School of Management, Northwestern University. He joined Kellogg in 2020 after receiving his PhD in economics from the University of Oxford. His research spans economic development, political economy, and economic history with particular focus on government's role in facilitating or stifling innovation, entrepreneurship, and growth. His research interests include: Economic Development Political Economy Economic History Government Origins and Evolution Innovation and Entrepreneurship Growth Patterns Heldring's scholarly work examines historical government formation, economic effects of historical events like the English Parliamentary Enclosures and the Dissolution of English Monasteries, and long-term impacts of colonialism in Africa. His research combines historical data with economic analysis to understand how institutions shape economic outcomes over time. He has published in top journals including American Economic Review, Quarterly Journal of Economics, and Review of Economic Studies. Heldring has received media coverage for his work in outlets such as the Economist magazine, VOXeu.org, and Forbes. His research has significant implications for understanding historical roots of modern economic development and government structures. Contact information: Email: leander.heldring@kellogg.northwestern.edu Website: http://www.leanderheldring.com/ Twitter: @LeanderHeldring