جست‌وجوی استاد و پژوهشگر

Eric Hochsteinمشاهده پروفایل

دانشیار

• History and philosophy of science
• Philosophy of neuroscience
• Philosophy of psychology
• +۴ مورد دیگر

Dr. Eric Hochstein is an Associate Professor in the Department of Philosophy at the University of Victoria (on leave until June 30, 2025). He holds a BA from Concordia University, an MA from the University of British Columbia, and a PhD from the University of Waterloo. His research focuses on the philosophy of science, neuroscience, psychology, mind, language, and metaphysics, with a particular interest in how contradictory scientific models contribute to explanations of complex phenomena like the mind. He also explores social and linguistic influences on scientific practice, traditional philosophy of mind questions, and the metaphysics of intentionality. Before joining UVic in 2017, Hochstein was a SSHRC Postdoctoral Fellow at Washington University in St. Louis and a Visiting Research Fellow at the University of Leeds. His work has been published in leading journals such as The British Journal for the Philosophy of Science and Synthese. He currently serves as the Graduate Coordinator for the Philosophy Department. Key research themes include model pluralism in scientific explanation, the role of social factors in shaping science, and the integration of psychological and neuroscientific theories. His scholarship challenges reductionist approaches, advocating instead for explanatory holism and interdisciplinary dialogue.

Eva Schultze-Berndtمشاهده پروفایل

استاد

• Linguistic Typology
• Language Documentation
• Australian Languages
• +۱ مورد دیگر

Prof. Eva Schultze-Berndt is Professor of Linguistics at the University of Manchester, specializing in typology and documentation of Australian languages. With 40+ months of fieldwork, her research examines Western Mirndi languages (Jaminjung, Ngaliwurru) and Northern Australian Kriol. Research Focus: Schultze-Berndt's work addresses grammatical phenomena including complex predication, verb classification, spatial language, information structure, and modality systems. Her DoBeS-funded projects document Jaminjungan languages and analyze prosodic convergence in multilingual communities. Publication Trends: Recent articles (2017-2023) explore reflexive constructions, discontinuous NPs, and information structure in Australian languages. Earlier work established foundations on secondary predication, parts of speech, and verb classification typologies. Leadership: Coordinates international documentation projects; serves on editorial boards of Sprachtypologie und Universalienforschung and Oxford Studies in Typology.

Marcus Maurerمشاهده پروفایل

استاد

• Political Communication
• Media Effects Research
• Nonverbal Communication
• +۳ مورد دیگر

Prof. Marcus Maurer is a full-time faculty member and holds the position of Professor of Communication Science at the Institute of Journalism at Johannes Gutenberg University Mainz since 2014. Previously, he was a Professor for Empirical Methods in Communication Science at Friedrich Schiller University Jena (2010-2014), and held visiting professorships at FU Berlin, LMU Munich, and the University of Zurich (2006-2010). He completed his doctorate in 2002 on 'Political Disenchantment through Media Reports' and habilitation in 2008, both at JGU Mainz, after studying Journalism, Political Science, and German Philology (1991-1997). His research focuses on political communication , media effects , nonverbal communication , and empirical methods . Notable work includes studies on televised political debates, refugee crisis reporting, and the impact of social media on political discourse. He has served as Managing Director of the Institute of Journalism (2017-2019), spokesperson of the DGPuK Methods Section (2006-2010), and since 2024 is a Member of the Executive Board of the Gutenberg Research College. 2024: Prize for Best Conference Contribution (DGPuK) 2020: Best Article Award (SCM Journal) and DGPuK Journal Article Prize (1st place) 2005: Dissertation Prize and DGPuK Article Prize (1st place) 1997: Award for Outstanding Master’s Thesis His grants and advising span collaborations with institutions like Stiftung Mercator and the Rudolf Augstein Foundation. He has led projects evaluating road safety campaigns (2010-2017) and climate journalism (2022-2023). His team includes researchers like Dr. Pablo Jost and Dr. Simon Kruschinski, focusing on digital communication, media content analysis, and automated text-mining tools (e.g., Argument Mining). Maurer’s work critically engages with the role of media in democracy, emphasizing the interplay between journalistic practices and public opinion. Recent projects analyze online misinformation, the effects of political microtargeting, and the dynamics of epistemic authority in the digital public sphere.

• Internet Security
• Operating Systems
• Programming
• +۱۲ مورد دیگر

Dr. Xiaochun Cheng is a Senior Lecturer in the Department of Computer Science at Middlesex University, School of Science and Technology. Their research spans Internet Security, Operating Systems, and Programming, with a strong focus on cybersecurity, artificial intelligence, and IoT applications. They are actively contributing to both academic and applied research in secure systems and intelligent computing. Research Interests: Dr. Cheng's work is centered on cybersecurity, deep learning, and intelligent systems. Key areas include intrusion detection in IoT, secure communication in autonomous vehicles, medical image analysis using neural networks, and privacy-preserving data sharing in healthcare systems. Their interdisciplinary approach bridges computer science with biomedical and social applications. The recent publications reflect a strong trend toward applying deep learning and hybrid AI models to critical domains such as healthcare (e.g., diabetic retinopathy, melanoma detection), cybersecurity (e.g., malware classification, threat detection), and smart infrastructure (e.g., smart buildings, UAVs). These works often combine advanced neural architectures with real-world constraints like resource limitations and data privacy. Scientific Contributions: Dr. Cheng has contributed significantly to journals such as IEEE Transactions on Intelligent Transportation Systems, Computers & Security, PLoS ONE, and Applied Sciences. Their collaborative research spans multiple continents and disciplines, including computer science, public health, and bioinformatics. Grants and Advising: While specific grants and students are not mentioned in the provided text, Dr. Cheng's extensive publication record suggests active research supervision and project leadership. They likely mentor students in AI, cybersecurity, and software engineering, and may be involved in funded projects related to secure IoT and intelligent transportation systems. Laboratories and Teams: Dr. Cheng appears to be part of a multidisciplinary research group at Middlesex University focused on intelligent systems and cybersecurity. Their collaborations with researchers in blockchain, cloud computing, and medical AI suggest involvement in a dynamic, cross-functional research environment.

• Natural Language Processing
• Machine Translation
• Statistical Machine Translation
• +۴ مورد دیگر

Cristina España i Bonet is a Professor in the Department of Computer Science at the Polytechnic University of Catalonia (UPC), working within the Natural Language Processing group (GPLN) of the Center for Technologies and Applications of Language and Speech (TALP). She holds a Physics degree and a PhD in Cosmology from the University of Barcelona, later transitioning to Natural Language Processing and Machine Translation. Her academic journey includes teaching at both the Faculty of Physics of the University of Barcelona and currently at the Barcelona School of Informatics of UPC. Her research spans multiple areas of computational linguistics with a strong focus on Machine Translation. She has extensive experience in statistical and hybrid translation systems, document-level translation, multilingual systems, and machine learning applications in NLP. Her work often addresses real-world challenges with diverse text genres including news, patents, Wikipedia articles, and social media content. She has made significant contributions to developing translation systems that leverage context beyond the sentence level to improve coherence and quality. Cristina has been actively involved in numerous European and national research projects including OPENMT, OPENMT2, MOLTO, and TACARDI, where she has contributed both research and project coordination. Her recent work shows a growing interest in sign language translation, low-resource language processing, and the intersection of large language models with traditional machine translation paradigms. She has supervised multiple PhD and Master's students in topics related to machine translation and multilingual systems. Member of the Natural Language Processing group (GPLN) at TALP Research Center Supervisor of doctoral and master's theses in NLP and Machine Translation Lead researcher in multiple EU-funded projects on multilingual translation Developer of resources and tools for Wikipedia-based multilingual corpora Her research has evolved from statistical machine translation to incorporate neural approaches while maintaining focus on document-level context and multilingual applications. She has made significant contributions to understanding translation artifacts, developing methods for low-resource language translation, and creating resources for sign language processing. Her work bridges theoretical advances with practical applications across diverse language pairs and domains.

Larisa Leisiöمشاهده پروفایل

استاد

• Language Contacts
• Samoyedic Languages
• Non-Standard Varieties of Russian
• +۷ مورد دیگر

Larisa Leisiö is a Professor at the University of Eastern Finland's School of Humanities, specializing in Russian language with a focus on language contacts, Samoyedic languages, and non-standard varieties of Russian. Her research integrates typological and usage-based approaches, examining phenomena like code-switching, possessive noun phrases, and gender integration of Finnish loanwords in Russian. She has conducted extensive fieldwork across Siberia (Nganasans, Forest Enets, Nenets) and among European Russian-Finnish communities. Professor, University of Eastern Finland Research: Language contact, Samoyedic languages, Russian dialectology Fieldwork: Siberian indigenous communities, Finland Russians Publications: 15 most recent explore code-switching, language preservation, and morphosyntactic evolution Her work addresses both theoretical linguistic issues and practical challenges, such as Ukrainian refugee integration and Russian academic activism against war. She contributes to projects like the Language Bridge Between Ukraine and Finland while maintaining a focus on endangered language revitalization through technology.

• Natural Language Processing
• Machine Translation
• Statistical Machine Translation
• +۶ مورد دیگر

Cristina España-Bonet is a researcher at the Department of Computer Science (CS) in the Polytechnic University of Catalonia (UPC), where she works in the Natural Language Processing (GPLN) group. Previously, she was affiliated with the University of Barcelona (UB) in the Department of Astronomy and Meteorology (DAM), where she completed her PhD in Cosmology. Her research spans both Natural Language Processing and Cosmology , with a strong focus on Machine Translation and Multilingual Systems . Her work in NLP includes: Statistical and Hybrid Machine Translation Document-level Translation Multilingual Information Retrieval Sign Language Translation Low-resource Language Processing She has contributed to major projects such as: OPENMT MOLTO TACARDI Wikiparable Her research has produced significant resources including: Wikipedia-based comparable corpora Hybrid translation systems for patents Stopword lists for Occitan Sign language translation systems

Leila Behrensمشاهده پروفایل

دانشیار

• Semantics and Pragmatics
• Cross-linguistic and Cross-cultural Diversity
• Ambiguity
• +۱۲ مورد دیگر

Leila Behrens serves as Associate Professor in the Department of Linguistics at the University of Cologne, specializing in semantics and pragmatics with emphasis on cross-linguistic diversity. Her research examines ambiguity, evidentiality, modality, and intercultural communication phenomena across diverse languages. Education: Habilitation in Theoretical Linguistics and Computational Lexicology, Universität München (1999) PhD in General Linguistics, Universität München (1987) MA in General Linguistics, Universität München (1982) Her scholarly focus spans semantic-pragmatic interfaces and cross-cultural variation , particularly investigating irony comprehension , metadiscourse markers , and evidentiality systems . Current work analyzes stance-taking in digital discourse, while earlier research established foundational insights into lexicon-grammar interactions, genericity, and reciprocal constructions across languages. Analysis of her publication trajectory reveals sustained engagement with typological semantics , especially evidentiality-modality relationships and cross-linguistic genericity patterns. Her methodological approach consistently bridges theoretical frameworks with empirical discourse analysis, increasingly incorporating digital communication contexts since 2010. Scientific Awards: No awards documented in source materials. Professor Behrens has secured substantial research funding including DFG support for 'Lexical Typology' (1996-2000), ARC-funded cross-cultural irony research at Melbourne University (2003), and Siemens-sponsored machine translation projects (1987-1993). While student advising details aren't specified, her 35+ year research trajectory indicates extensive mentorship through principal investigator roles.

• Artificial Intelligence
• Semantic Web
• Natural Language Processing
• +۷ مورد دیگر

Philipp Cimiano is a Professor at Bielefeld University, Germany , with a prolific research record in Artificial Intelligence, Semantic Web, Natural Language Processing, Knowledge Graphs, Explainable AI, Clinical Decision Support Systems, Ontology Engineering, and Federated Learning . His work bridges theoretical AI concepts with practical applications in healthcare and robotics. Key research themes include dialogue-based XAI for user understanding, federated learning for healthcare data privacy, and LLM-driven robotics for embodied commonsense reasoning. Recent publications analyze dynamic explanatory interactions , perspectivized argumentation frameworks , and benchmarks for robot manipulation using large language models. His collaborations span institutions in Germany and Europe, with frequent co-authorship on topics like counterfactual generation , stakeholder group analysis , and lexicalization in QALD systems .

• Facial Expression Analysis
• Machine Learning
• Image Processing
• +۴ مورد دیگر

Academic Overview Kristin Surpuhi Benli currently serves as an Assistant Professor in the Department of Software Engineering at Uskudar University's College of Engineering. With a research focus spanning facial expression analysis, machine learning applications, and data mining in medical contexts, her work bridges computational methods with interdisciplinary applications. Education Undergraduate Degree: Computer Engineering, Işık University (2005) Master Degree: Computer Engineering, Işık University (2007) Doctorate: Computer Engineering, Işık University (2013) Research Interests Her research spans multiple dimensions of computational science: Developing anatomically-informed facial expression recognition systems Applying machine learning to medical prognosis through blood test analysis Investigating programming self-efficacy in computer science education Exploring AI adoption in neuroscience and clinical decision-making Implementing image processing techniques for brain tumor detection Academic Contributions Dr. Benli has contributed to diverse research areas through her publications, including: Classification algorithms in stroke mortality prediction BERT-based stance detection in social media analysis Neuroscience applications of artificial intelligence Anatomical modeling for facial expression recognition Biometric data analysis through nearest neighbor methods Administrative Roles Deputy Head of Research Center (YAZAMER), since 2025 Member of Quality Commission (Faculty level), since 2023 Board Member of Faculty Administrative Council, since 2020 Deputy Head of Software Engineering Department, since 2019 She also maintains active student advisory roles and participates in various academic commissions.

Veronique Hosteمشاهده پروفایل

استاد

• Computational Linguistics
• Natural Language Processing
• Machine Learning
• +۷ مورد دیگر

Veronique Hoste is a Full Professor of Computational Linguistics at Ghent University's Faculty of Arts and Philosophy , where she serves as Department Head of the Department of Translation, Interpreting and Communication and Director of the LT3 Language and Translation Technology Team . Her work bridges machine learning with natural language processing, focusing on semantics, discourse modeling, and practical applications in emotion detection, irony recognition, and customer service dialogue analysis. PhD in Computational Linguistics from University of Antwerp (2005) 2023-2024: Francqui Chair at Université Libre de Bruxelles 2024: Elected to Royal Flemish Academy of Belgium (KVAB) Research Interests: Specializes in machine learning approaches to coreference resolution, sentiment analysis, and multimodal emotion detection. Leads projects like FlandersAI (empathy in conversational agents), METRICS (emotion trajectories in service dialogues), and SENTiVENT (financial event extraction). Develops high-quality datasets (e.g., EmotioNL , ENCORE ) for broader NLP community use. Recent Publications span Dutch social media irony detection, Classical Chinese poetry sentiment analysis, and multimodal emotion datasets. Collaborates on interdisciplinary initiatives like NewsDNA (news recommendation) and SentEMO (commercial sentiment analysis). Scientific Awards Francqui Chair (2023-2024) KVAB Membership (2024) Outreach includes co-founding AlfaSent (LT3 spin-off for customer feedback analysis) and authoring the first Dutch-language NLP book Taaltechnologie Ontrafeld (2024). Coordinates AI education initiatives like the AI at School project.

Stuart Middletonمشاهده پروفایل

دانشیار

• Natural Language Processing
• Information Extraction
• Human-in-the-loop NLP
• +۱۷ مورد دیگر

Dr Stuart Middleton is an Associate Professor at the University of Southampton, affiliated with the School of Electronics and Computer Science within the Faculty of Engineering and Physical Sciences. He is a member of the Agents, Interaction and Complexity research group, the Centre for Machine Intelligence, and the Centre for Democratic Futures. His research focuses on Natural Language Processing (NLP), particularly information extraction and human-in-the-loop NLP, with applications in law enforcement, defence, mental health, and environmental science. His research interests include Natural Language Processing , Information Extraction , Human-in-the-loop NLP , Active Learning , Adversarial Training , Rationale-based Learning , and Argument Mining . He specializes in scenarios with limited or fragmented data, developing methods for few/zero-shot learning, graph-based models, and multimodal analysis. His work spans domains such as mental health, digital ethics (e.g., sharenting), defence, and climate science. The recent publications highlight a strong trend in applying NLP to societal challenges, including mental health monitoring through social media, ethical AI, multimodal argumentation in political debates, and climate data analysis. His work combines technical innovation in prompt engineering, summarization, and graph-based modeling with real-world impact. AI for defence: readiness, resilience and mental health (2024) Extraction and summarization of suicidal ideation evidence (2024) Sharenting and social media properties (2024) Implementing responsible innovation (2024) ConversationMoC: mood change detection (2024) Dr Middleton is actively involved in PhD supervision and academic leadership as Deputy Director of the UKRI MINDS Centre for Doctoral Training. He supervises multiple PhD students working on NLP and AI projects. He has secured research funding from ESRC and EPSRC for projects such as ProTecThem2.0 , SafeSpacesNLP , and GloSAT . He leads the Natural Language Processing modules COMP3225 (UG) and COMP6253 (PG) and mentors students in NLP research. He is a Fellow of The Alan Turing Institute and a member of the EPSRC peer review college, contributing to national research strategy and evaluation. His research is conducted within interdisciplinary teams, including collaborations with criminologists, social scientists, and environmental researchers. He is part of the Agents, Interaction and Complexity group and contributes to the Centre for Machine Intelligence and Centre for Democratic Futures , focusing on AI systems that interact meaningfully with humans and society.

Chris Biemannمشاهده پروفایل

استاد

• Natural Language Processing
• Unsupervised Learning
• Semantic Modelling
• +۷ مورد دیگر

Prof. Chris Biemann is a Professor for Language Technology at the Department of Informatics, University of Hamburg (MIN Faculty). He leads the Language Technology Group, focusing on unsupervised methods, lexical semantics, and NLP applications including speech processing. His work emphasizes open science principles, releasing publications and software in open access/source formats. Education: Dr. rer. nat. and Computer Science Diploma from University of Leipzig. Professional Experience: Co-founded Powerset (acquired by Microsoft for Bing), TU Darmstadt (2011-2016), and currently heads Hamburg's Language Technology group since 2016. Active in ERC Synergy Grant CultCryo (2023) and develops tools like the D-WISE suite for discourse analysis. Research interests span computational linguistics, multimodal analysis, and ethical AI applications. Notable projects include hate speech detection systems, comparative question answering frameworks (CAM), and cross-modal benchmarks (GIMMICK). Recent work emphasizes large vision-language models' multilingual capabilities and human-AI collaboration tools. Awards: None explicitly listed, but group members have received accolades like GSCL master's thesis awards. Grants include EU-funded projects in computational sociology. Supervised students: Not listed in provided texts. Labs/Teams: Language Technology Group (LT) and D-WISE project collaboration network. Tools developed: Discourse Analysis Tool Suite, Golden Retriever (multimodal search), and CAM comparative analysis system.

Lucas Geeseمشاهده پروفایل

پژوهشگر ارشد

• Climate Change Policy
• Public Opinion Analysis
• Political Trust Dynamics
• +۳ مورد دیگر

Lucas Geese is a Research Fellow at the School of Environmental Sciences, University of East Anglia (UEA), affiliated with the Tyndall Centre for Climate Change Research and ClimateUEA. His work bridges climate policy, political behavior, and deliberative democracy, with a focus on public opinion dynamics and institutional responses to environmental challenges. Key research themes include climate change mitigation strategies, immigration policy impacts on political trust, and the efficacy of participatory governance mechanisms. Notable contributions include analyzing the effectiveness of National Citizens’ Climate Assemblies and investigating how mainstream parties’ immigration stances influence voter behavior and far-right appeal. His research employs mixed-methods approaches, including text-as-data analysis of legislative discourse and systematic reviews of climate communication frameworks. Geese collaborates with institutions like Green Alliance and contributes to policy-oriented discussions on climate action during electoral cycles. His work frequently emphasizes the interplay between political institutions, public perception, and environmental governance, with a focus on equitable policy design and cross-sectoral integration. His affiliations include leading roles in interdisciplinary climate research networks, addressing both academic and practical dimensions of sustainability transitions. Recent outputs highlight methodological innovations in survey design for climate question classification and critical analyses of low-carbon policy implementation barriers.

• Computational Social Science
• Natural Language Processing
• Social Network Analysis
• +۳ مورد دیگر

Roshni Chakraborty is an Assistant Professor at the Institute of Computer Science, University of Tartu, Estonia, where she leads research in the Computational Social Science Group. Her work bridges natural language processing, social network analysis, and machine learning to address challenges in social media analytics, disaster response, and misinformation detection. Research Interests: Her expertise spans: Computational Social Science : Analyzing social dynamics via digital footprints. Disaster Informatics : Developing NLP tools for crisis-related tweet summarization (e.g., ATSumm, IKDSumm). Political & Media Analysis : Detecting biases in community-driven fact-checking and news stance. Network Science : Advancing signed network modeling (SigGAN) and cross-network alignment (HCNA). Publication Trends: Recent articles (2022-2025) focus on generative AI for fact-checking, disaster tweet summarization benchmarks, and political bias analysis. Her work emphasizes practical NLP solutions for social good, leveraging transformer models, adversarial learning, and ontology-driven approaches. Academic Activities: She actively recruits PhD students and research interns for projects in social computing. Her group collaborates on datasets like BD2TSumm and Adsumm, fostering open research in crisis informatics.