جست‌وجوی استاد و پژوهشگر

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.

• Biometrics
• Keystroke Dynamics
• Gait Recognition
• +۳ مورد دیگر

Patrick Adrianus Bours is Professor at the Department of Information Security and Communication Technology, Norwegian University of Science and Technology (NTNU). Educated at Eindhoven University of Technology (MSc 1990, PhD 1994), his career includes senior roles at Netherlands National Communication Security Agency and leadership of NTNU's Norwegian Information Security Laboratory (NISlab). Research focuses on behavioral biometrics including keystroke dynamics, gait recognition, and continuous authentication systems. Current projects address chatroom security with emphasis on detecting predatory behavior through typing patterns and stylometric analysis. Work integrates machine learning, natural language processing, and multimodal systems to enhance cybersecurity. Publications demonstrate progressive refinement of predator detection systems and biometric authentication methods. Recent work examines misinformation impacts during COVID-19 and ensemble methods for security applications. Research consistently combines theoretical security frameworks with practical implementation challenges.

Denilson Barbosaمشاهده پروفایل

استاد

• Natural Language Processing
• Information Retrieval
• Machine Learning
• +۳ مورد دیگر

Denilson Barbosa is a Professor of Computing Science at the University of Alberta's Faculty of Science. He holds a PhD and specializes in Natural Language Processing, Information Retrieval, and Machine Learning. His research focuses on knowledge extraction, entity recognition, and knowledge graph construction. Barbosa teaches courses like CMPUT361 (Information Retrieval) and CMPUT656 (Knowledge Graphs). He served as President of the Canadian Artificial Intelligence Association (CAIAC) from 2023 to 2024. His work includes developing tools like the NLP Workbench and contributing to open relation extraction, Wikipedia analysis, and low-resource language models. Education and Background: Barbosa's academic background aligns with his research interests in computational linguistics and AI applications. His teaching emphasizes practical skills in algorithms, data structures, and machine learning for text processing. Research Highlights: Barbosa's research spans semantic graphs, probabilistic language models, and defect prediction systems. He explores challenges in multilingual NLP, particularly for Indigenous and low-resource languages like Cree. His work often integrates machine learning with traditional IR methods to improve system efficiency and accuracy. Recent Contributions: Notable recent projects include improving Bengali/Hindi LLMs, evaluating QA systems via textual entailment, and developing Bayesian methods for crowdsourced truth discovery. His articles reflect his interdisciplinary approach, combining theory with real-world applications in education, software engineering, and social media analysis.

• Multimedia Indexing and Search
• Social Data Analysis
• Knowledge Discovery
• +۳ مورد دیگر

Professor Helen Huang is a faculty member in the School of Electrical Engineering and Computer Science at The University of Queensland, where she serves as the Data Science Discipline Leader. She holds a BSc from Tsinghua University's Computer Science Department and a PhD from The University of Queensland's School of ITEE (2001 and 2007, respectively). Her research focuses on multimedia indexing, social data analysis, and knowledge discovery, with over 200+ publications in top-tier venues. Dr. Huang is an Associate Editor for The VLDB Journal, ACM Transactions on Information Systems, and Pattern Recognition Journal, and a member of the VLDB Endowment Board of Trustees. Her awards include the 2016 Chris Wallace Award for breakthroughs in Computer Science, the 2014 Women in Technology Research Award, and the 2018 Excellence in Higher Degree Research Supervision Award. She leads projects in data science, AI-driven systems, and interdisciplinary applications such as Auslan learning and material science modeling. Her work spans domains like recommender systems, domain adaptation, and graph learning, with contributions to both theoretical advancements and real-world applications. Dr. Huang’s publications reflect expertise in machine learning, computer vision, and data science, addressing challenges in multimedia, social networks, and interdisciplinary collaborations. She has advised numerous students and led grants in AI, domain adaptation, and educational technologies. Her leadership roles and editorial contributions highlight her impact on the academic community.

Giuseppe Attardiمشاهده پروفایل

استاد

• Natural Language Processing
• Machine Learning
• Web Technologies
• +۳ مورد دیگر

Giuseppe Attardi is a Professor at the Dipartimento di Informatica, Università di Pisa. His work spans Natural Language Processing (NLP), Machine Learning, and Web Technologies. He leads projects like Arianna (an Italian Web search engine) and contributes to initiatives like SerRA (University of Pisa's networking center) and GARR (Italian research network). Research interests include dependency parsing, semantic analysis, and machine learning applications in healthcare and cybersecurity. Developed tools such as ECoLisp (Common Lisp implementation), CMM (memory manager), and DeSR (dependency parser). Recipient of awards for the Arianna project, including Best of Europe by Europe Online and Beta . He teaches courses like Human Language Technologies and Natural Language Processing. Collaborates on EU-funded projects like Parseme and RIS (medical record analysis). Actively involved in academic initiatives like the MediaLab and Java Campus programs.

• Knowledge Representation and Reasoning
• Natural Language Processing
• Machine Learning
• +۳ مورد دیگر

Xiaowang Zhang is a Full Professor at the College of Intelligence and Computing, Tianjin University, China. His research spans Knowledge Graphs, Natural Language Processing, Multi-modality, and Software Engineering, with a focus on semantic reasoning, relation extraction, and software vulnerability detection. He leads a team advising international students and contributes to open-access research in venues like ACL, WWW, and ISWC. Education : PhD from Peking University (2011), Postdoc at Hasselt University (2011-2014), Visiting Associate Professor at Griffith University (2018). His research integrates Knowledge Graphs for relation extraction and rule learning, advances LLMs in few-shot learning and cross-lingual stance detection, and addresses software engineering challenges through vulnerability description analysis and code translation error detection. Recent work emphasizes temporal reasoning and explainability in AI systems. Article trends highlight interdisciplinary applications of Knowledge Graphs in NLP tasks, leveraging graph structures for QA systems, and improving software security through feature inference and multi-interest recommendation frameworks. While no explicit awards are listed, his collaborations with institutions like Griffith University and Hasselt University demonstrate global academic engagement. He advises international students and emphasizes programming skills, communication, and teamwork in future advisees. His full_description expands on 15+ years of contributions to knowledge representation, semantic networks, and code generation systems.

Teri Schamp-Bjeredeمشاهده پروفایل

پژوهشگر

• Language Didactics
• Computer-Assisted Language Learning
• EFL Writing
• +۳ مورد دیگر

Teri Schamp-Bjerede is an active doctoral candidate and researcher at Lund University's Centre for Languages and Literature within the Faculty of Humanities and Theology. She specializes in language didactics with a focus on English as a Foreign Language (EFL) writing and computer-generated feedback systems. Her research examines digital writing processes, pedagogical affordances of technology, and L2 acquisition strategies. Education: • Bachelor's in English (Blekinge Institute of Technology, 2004) • MSc in IT (University of Liverpool, 2009) Research Focus: Her work intersects digital pedagogy, linguistic analysis, and educational technology. Primary interests include: computer-assisted writing feedback, affective aspects of digital learning, sociolinguistics in online environments, and interdisciplinary methodologies merging computational linguistics with language education. Publication Trends: Schamp-Bjerede's recent articles demonstrate a strong focus on computational linguistics and digital pedagogy, particularly analyzing social media discourse, sentiment detection, and educational technology efficacy. Her work frequently employs interdisciplinary approaches combining linguistic theory with data visualization and machine learning techniques. Projects: Co-leads the interdisciplinary project Representation of war as autobiographical media: Walter MacKay Draycot, P.P.C.L.I. exploring digital remediation of historical texts. Previously developed the Walter Draycot Web Project, integrating academic standards with digital accessibility.

Ravi Gokaniمشاهده پروفایل

استادیار

• Religion and Social Welfare
• Community-Based Research
• International Social Work
• +۷ مورد دیگر

Dr. Ravi Gokani is an Assistant Professor in the Department of Social Work at Lakehead University , Thunder Bay, Canada. His research focuses on the intersection of religion and social welfare , community-based research , and international social work , with particular attention to evangelical faith-based organizations, homelessness, and policy impacts like the Ontario Basic Income Pilot. Dr. Gokani holds a Ph.D. in Social Work (2018) , an M.A. in Community Psychology (2012) , and a B.A. in Philosophy and Social Psychology (2007) . He has received the Lakehead University Contribution to Teaching Award (2022) and teaches courses such as Introduction to Social Welfare . His research includes SSHRC-funded projects on faith and service provision in evangelical organizations and homelessness migration using machine learning. He collaborates with scholars in Health Sciences, Computer Science, and History. Scientific Awards Lakehead University Contribution to Teaching Award, 2022 Dr. Gokani has supervised graduate students on topics including religious beliefs and childhood trauma , Truth and Reconciliation Commission implementation , and substance use treatment in faith-based agencies . His work spans qualitative and quantitative methodologies, addressing social justice and systemic equity.

Jacopo Urbaniمشاهده پروفایل

دانشیار

• Knowledge Graphs
• Data Stream Reasoning
• Semantic Web
• +۴ مورد دیگر

Jacopo Urbani is an Associate Professor at Vrije Universiteit Amsterdam, affiliated with the Faculty of Science, Computer Systems department, and the Network Institute. His research focuses on Knowledge Graphs, Stream Reasoning, and Distributed Computing. He explores scalable reasoning techniques for large-scale datasets, integrating semantic technologies with real-time data processing. His work emphasizes practical applications of logic-based systems, including existential rules, probabilistic reasoning, and trigger graphs for efficient knowledge base materialization. Recent contributions address challenges in handling dynamic data streams and enhancing the scalability of semantic web technologies. Urbani has published extensively in top venues like the Semantic Web Conference (ESWC) and the International Conference on Principles of Knowledge Representation and Reasoning (KR). Notable projects include the VLog rule engine for knowledge graphs and the Tab2Know platform for extracting structured data from scientific tables. He supervises PhD theses in areas like stream reasoning and knowledge graph embeddings. His research also involves collaborative efforts with institutions worldwide, addressing topics such as data compression, distributed computing architectures, and hybrid reasoning systems.

Kostiantyn Kucherمشاهده پروفایل

دانشیار

• Information Visualization
• Visual Analytics
• Text Mining
• +۵ مورد دیگر

Kostiantyn Kucher is an Associate Professor/Senior Lecturer at Linköping University's Department of Science and Technology, specializing in Information Visualization and Visual Analytics. He holds a PhD from Linnaeus University (2019) and MSc/BSc from Odessa National Polytechnic University (2012/2010). His research focuses on text visualization, sentiment analysis, network visualization, and explainable AI, with applications in climate adaptation and human-AI collaboration. He co-leads the iVis group and organizes GD 2025 conference. Awards include EuroVis Early Career (2025) and multiple Best Reviewer distinctions. Research : Explores text visualization (Text Visualization Browser), stance analysis (StaViCTA), and VA+Embeddings for AI transparency. Active in EU-funded projects like AI4REALNET and InfraVis. Recent work includes climate data visualization (EuroVis 2025) and trust in industrial AI interfaces. Awards : Early Career Award (EuroVis 2025) Best Reviewer (EuroVis 2025, 2023) Best Poster (EuroVis 2018) Grants & Projects : Leads InfraVis (Swedish national visualization infrastructure) and collaborates on AI4REALNET (critical infrastructure networks) and Testbed Air Mobility (UAV systems). Labs/Teams : iVis group at Linköping, focusing on visual analytics and human-Automation teaming. Active in ELLIIT Focus Period on Visualization-Empowered AI.

Yves Vanlandewijckمشاهده پروفایل

استاد مهمان

• Rehabilitation Science
• Paralympic Sports Classification
• Adaptive Sports
• +۵ مورد دیگر

Yves Vanlandewijck serves as a Visiting Professor in Rehabilitation Science at the Swedish School of Sport and Health Sciences (GIH), affiliated with the Department of Physiology, Nutrition and Biomechanics, Section for Laboratories. His research spans multiple continents with significant work in Suriname examining musculoskeletal disorders across diverse ethnic populations, and extensive contributions to Paralympic sports science. Vanlandewijck's research interests focus on rehabilitation science with particular expertise in Paralympic sports classification systems, biomechanics of athletes with disabilities, and trunk strength assessment. His work bridges clinical rehabilitation and elite sports performance, with special attention to athletes with intellectual impairment. He has pioneered evidence-based approaches to sports classification that consider both impairment types and their impact on specific sport performance. His publication record shows consistent output with recent emphasis on cognitive-motor dual-task performance in athletes with intellectual disabilities, biomechanical assessment methods for wheelchair sports, and cross-cultural studies of musculoskeletal disorders. His work frequently employs mixed-method approaches combining quantitative biomechanical analysis with qualitative insights into athlete experiences. Vanlandewijck has supervised numerous doctoral candidates and collaborators including Roi Charles Pineda, Nancy Ho-A-Tham, and Debbie Van Biesen. His research has received support from multiple international collaborations, particularly with KU Leuven in Belgium and various Paralympic sport organizations. He leads laboratory-based research examining trunk control mechanisms in adaptive sports and has developed novel assessment protocols for sit-skiing and wheelchair sports. His work on classification systems has directly influenced Paralympic sport governance and evidence-based practice in adaptive athletics.

Sandra Küblerمشاهده پروفایل

استاد

• Machine Learning of Natural Language
• Parsing Morphologically Rich Languages
• Dependency Parsing
• +۵ مورد دیگر

Sandra Kübler is a Professor in the Department of Linguistics at Indiana University, part of the College of Arts and Sciences. Her research focuses on computational linguistics, machine learning applications in natural language processing, and parsing of morphologically rich languages. She has led projects such as the NSF-funded SATC initiative on unsubstantiated information analysis and contributed to initiatives like the TLT workshops and SPMRL conferences. Her work spans dependency parsing, abusive language detection, and cross-lingual NLP challenges. She advises numerous PhD and Master’s students, many of whom have gone on to academic and industry roles. Her contributions include developing tools like the IUCL system for stance detection and collaborating on corpora for languages like Old Occitan and Xibe. Education details are not explicitly stated in the provided texts, but her extensive academic career and publications indicate advanced training in computational linguistics. Her research interests emphasize leveraging machine learning for linguistic analysis, particularly in under-resourced languages and social media text processing. Projects include the development of the TüBa-D/Z treebank and contributions to parser evaluation frameworks. She has organized major workshops such as the SIGMORPHON and TLT conferences, reflecting her leadership in the field. In advising, she has guided over 20 students to completion, many securing academic positions (e.g., University of British Columbia, Rose-Hulman Institute) or industry roles (e.g., JP Morgan Chase, Microsoft). Her lab activities involve collaborations with institutions like Bosch and IntraFind. Current research includes multilingual coreference resolution and fusion of hard/soft data for information reliability assessment.

• Computational Social Science
• Social Inequality
• Machine Learning
• +۳ مورد دیگر

Joseph Kenny is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo's School of Engineering and Applied Sciences. He also serves as Associate Director of the AI and Society Institute for Artificial Intelligence and Data Science. PhD in Societal Computing, Carnegie Mellon University (2016) MS in Societal Computing, Carnegie Mellon University (2012) BS in Computer Science, Carnegie Mellon University (2010) His research bridges computational methods with social equity , focusing on stereotype dynamics, algorithmic bias in child welfare systems, and Twitter-based social behavior analysis. Current projects include machine learning models to predict Chafee service allocation, neighborhood change prediction frameworks, and tools for analyzing social identity in online discourse. Recent publications span interdisciplinary topics like partisan exposure patterns , geospatial disparities in disaster response , and computational models of gender inequality . He leads the Computation and Equity Lab (cubelab) , which emphasizes values such as meaningful work addressing social inequality, respect for lived experiences, and balanced work-life integration. Scientific contributions include: UB Exceptional Scholar—Young Investigator Award (2021) Pioneering methods for Twitter bio analysis and misinformation detection Developing explainable GeoAI tools for urban equity Creating frameworks for fair predictive modeling in child welfare Advancing computational approaches to stereotype dynamics Students working with him engage in projects combining computer science with social justice, with recent advisees placing at institutions like Michigan (PhD), Amazon, and Meta.