جست‌وجوی استاد و پژوهشگر

Luis Alberto Barron Cedenoمشاهده پروفایل

دانشیار

• Natural Language Processing
• Information Retrieval
• Machine Learning
• +۷ مورد دیگر

Luis Alberto Barron Cedeno is an Associate Professor at the Department of Interpretation and Translation, University of Bologna since 2022, where he previously served as Senior Assistant Professor from 2019-2022. He holds a PhD in Computer Science from Universitat Politècnica de València (2012) and has worked at Qatar Computing Research Institute (2014-2019) and TALP Research Center (ERCIM fellowship, 2012-2014). PhD: Universitat Politècnica de València (2012) MSc: AI (Universitat Politècnica de València, 2009) MSc: Computing Science (UNAM, 2007) BEng: Computing (UNAM, 2004) His research focuses on NLP applications for analyzing text qualities like originality (plagiarism detection) and intent (hate speech, propaganda). Recent work includes persuasion techniques in spam emails , misogyny detection using argumentation theory, and Spanish language varieties analysis. He has published over 100 papers with 20+ in top-tier conferences. Key awards include SemEval 2020 Best Task for propaganda detection and ACL 2020 Best Demo . He serves as Specialty Chief Editor for Frontiers in Artificial Intelligence (NLP) since 2023. His students include PhD candidates Arianna Muti (misogyny detection), Katerina Korre (hate speech), and Paolo Gajo (inceldom analysis). 2020: SemEval Best Task 2020: ACL Best Demo 2012: PhD International Mention 2009: Best MSc Thesis 2007: MSc Cum Laude 2004: BEng Cum Laude He organizes the annual CheckThat! lab at CLEF since 2018 and chaired CLEF 2022. His teaching includes NLP courses, computational linguistics, and game localization for translation students.

Regina Stoddenمشاهده پروفایل

پژوهشگر ارشد

• Text Simplification
• Online Participation
• Web Accessibility
• +۶ مورد دیگر

Regina Stodden is a Research Fellow at the Department of Computational Linguistics, Heinrich Heine University Düsseldorf, since January 2019. She is affiliated with the NRW Research College for Online Participation (second funding phase) and works under the supervision of Prof. Dr. Marc Ziegele. Education: B.A. in Educational Science, Text Technology, and Computational Linguistics from Bielefeld University M.A. in Information Science and Language Technology from HHU Düsseldorf Her research focuses on automatic text processing , particularly text simplification for online discussions. This includes: Enabling participation for people with limited German proficiency Reducing manual workload in text analysis Exploring accessibility in Open Data portals She has contributed to tools like TS-ANNO for corpus annotation and EASSE-DE for simplification evaluation, with recent work extending to CEFR-based language proficiency assessment . Her research intersects Natural Language Processing , Machine Learning , and Usability Studies , often addressing accessibility challenges in digital participation. Scientific awards: No explicit awards mentioned. Advising and grants: Participates in the NRW Research College for Online Participation funding program and collaborates under Prof. Dr. Laura Kallmeyer's supervision. Her work involves grants related to text simplification for online participation processes.

Sara Rezatمشاهده پروفایل

استاد

• Writing and text didactics
• Argumentative writing
• Digital education
• +۳ مورد دیگر

Prof. Dr. Sara Rezat is a full-time Professor at the Institute of German Studies and Comparative Literature (University of Paderborn), specializing in German Language Didactics . Her research focuses on writing pedagogy, text procedures, and digital/AI-supported writing instruction. PhD in German Linguistics (University of Paderborn, 2006) Diplom in Music Pedagogy (HfM Detmold, 2002) Her research integrates multilingualism and digital transformation in education, particularly exploring: Argumentative writing frameworks AI-driven adaptive feedback systems Material-supported writing instruction Metatextual procedures in text structuring Recent publications highlight trends in: Digital literacy education Automated text evaluation Transdisciplinary approaches to writing Ethical AI integration in classrooms Scientific engagement includes: Vice-chair of Symposions Deutschdidaktik e.V. (2024-2026) Member of the Faculty Council for Cultural Studies (2023-2025) Co-editor of "Praxis Deutsch" (since 2020)

• Digital Humanities
• Spatial Humanities
• Artificial Intelligence
• +۷ مورد دیگر

Professor Patricia Murrieta-Flores is a faculty member at Lancaster University's School of Global Affairs and Co-Director of the Digital Humanities Centre. Her research focuses on the intersection of Digital Humanities, Artificial Intelligence, and Spatial Humanities to study Latin American colonial history, particularly 16th–18th century New Spain. She employs GIS, NLP, Computer Vision, and Machine Learning to analyze epidemics, economic systems, and indigenous spatial epistemologies. Research Grants : TAP/ESRC: Digging into Early Colonial Mexico AHRC/NEH: Unlocking the Colonial Archive ESRC: The Fleets of New Spain (2024–) Scientific Awards : Fellow, Royal Historical Society Fellow, Centre for Apocalyptic and Postapocalyptic Studies (Heidelberg) PhD Supervision : Katherine Bellamy Edward Moore Collaborative Networks : Cross-institutional projects with University of Lisbon, LLILAS Benson, and others Interdisciplinary teams combining Computer Science, History, and Archaeology

Raquel Amaroمشاهده پروفایل

استادیار

• Computational Linguistics
• Lexical Semantics
• Lexicography
• +۳ مورد دیگر

Raquel Amaro serves as tenured Assistant Professor at NOVA University of Lisbon's School of Social Sciences and Humanities and Researcher at the Linguistics Research Centre (CLUNL) since 2015. She coordinates the Horizon Europe iRead4Skills project and has led 7 of 25+ research initiatives in corpus linguistics, computational lexical semantics, lexicography, and language technologies. Education: PhD in Computational Linguistics, University of Lisbon (2010) Master in Linguistics, University of Lisbon (2002) Her research pioneers computational approaches to lexical semantics and grammatical modeling, with emphasis on cross-linguistic resource development (Portuguese/Italian/Slovak) and educational applications. Current work bridges computational linguistics with health literacy and heritage language preservation through COST Actions and the Heritage Language Consortium. Recent publications demonstrate methodological innovation in semantic alignment frameworks, pedagogical lexicography tools, and multilingual grammatical resources, reflecting her dual focus on theoretical linguistics and practical language technology deployment. She actively supervises PhD/MA candidates while teaching computational linguistics across degree levels. Her professional footprint spans project leadership (7 coordinated), international collaborations (Macao, Mozambique, Czech Republic), and service on journal/conference committees. As CLUNL Board Director since 2017, she shapes institutional research strategy while maintaining industry engagement through roles like Lionbridge Computational Linguist.

Chelsea Maria Johnمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Artificial Intelligence
• High-Performance Computing
• +۵ مورد دیگر

Chelsea Maria John is a Researcher at the Accelerating Devices Lab within the NOVAS division of the Jülich Supercomputing Centre (JSC) at Forschungszentrum Jülich. Her work focuses on high-performance computing and artificial intelligence, specializing in efficient machine learning model training, hardware accelerator benchmarking, and optimization strategies for communication and computation. Her research spans: Natural Language Processing and Large Language Models (LLMs) Scientific Machine Learning with Neural Operators High-Performance Computing system optimization Benchmarking frameworks for emerging AI hardware European open-source AI initiatives like OpenGPT-X Analysis of her 15 publications (2021-2025) reveals pioneering work in training LLMs on HPC systems, development of benchmarking suites (JUPITER, CARAML), and European LLM projects (Teuken series). Her research bridges AI and computational science, notably applying Fourier Neural Operators to fluid dynamics simulations. As part of the Accelerating Devices Lab, she contributes to advancing AI acceleration through hardware-software co-design, focusing on communication efficiency and computational optimization for next-generation scientific computing workloads.

• Learning Management Systems
• Information and Communication Technologies for Education
• Hybrid Learning
• +۴ مورد دیگر

Bergey Jean-Luc is a Research Professor at the University of Lorraine, specifically affiliated with Inspé (Institut National Supérieur du Professorat et de l'Éducation) at the Metz-Montigny-lès-Metz site. He is a member of the CREM research center (Centre de recherche sur les médiations) and specializes in Language Sciences as indicated by his CNU section 7 affiliation. His research focuses on the intersection of technology and education, with particular expertise in: Learning Management Systems (LMS) and their optimization for language learning Information and Communication Technologies for Education (ICT) Hybrid and blended learning models Generative AI applications in educational contexts Educational assessment methodologies in digital environments Professor Bergey's recent publications from 2023-2025 reveal a strong emphasis on understanding how AI technologies are being adopted in educational settings, particularly examining both teacher and student perspectives in the Grand Est region of France. His work critically examines the balance between measuring performance versus competence in AI-enhanced learning environments and explores the transformative potential of hybrid learning models on traditional educational structures. He has been actively involved in organizing and participating in webinars through GT-NUM IA2GE, focusing specifically on the application of generative AI in educational assessment. His research bridges theoretical insights with practical implementation in classroom settings across the Nancy-Metz academy. Professor Bergey maintains an active research profile with numerous publications on educational technology, with a special focus on language learning systems and digital assessment methodologies. His email for professional correspondence is jean-luc.bergey@univ-lorraine.fr.

Xiaoyan Liمشاهده پروفایل

مدرس ارشد

• Question Answering
• Cross-lingual Question Answering
• Information Retrieval
• +۴ مورد دیگر

Xiaoyan Li serves as a Senior Lecturer in the Department of Computer Science at Princeton University, where she focuses on teaching and mentoring undergraduate students through junior independent work supervision each semester. Her academic credentials include: Ph.D. in Computer Science, University of Massachusetts Amherst (2006) M.S. in Computer Science, University of Massachusetts Amherst (2006) M.S. in Management Information Systems, Tsinghua University (1996) B.S. in Management Information Systems, Tsinghua University (1992) Dr. Li's research centers on Question Answering systems and Information Retrieval , with pioneering work in novelty detection using sentence-level patterns and cross-lingual applications. Her expertise spans Machine Learning techniques for data mining, relevance modeling, and query expansion, particularly in multilingual contexts. She has made significant contributions to syntactic feature analysis in Chinese question answering and time-based language models for dynamic information needs. Her publication history (2001-2008) reveals a concentrated focus on novelty detection and robust relevance models, with prominent outputs in ACM SIGIR, CIKM, and TREC proceedings. The research trajectory shows evolution from syntactic analysis (early 2000s) to adaptive passage retrieval techniques (late 2000s), consistently addressing core challenges in information access through pattern-based and machine learning approaches. At Princeton, Dr. Li teaches foundational and advanced courses including Machine Learning and Data Science (COS IW02&03), Introduction to Computer Systems (COS217), and Artificial Intelligence (COS402). Previously at Mount Holyoke College, she developed curriculum for Object-Oriented Programming, Data Structures, and Intelligent Information Retrieval courses, demonstrating extensive pedagogical range across computer science disciplines.

• Sculpture
• Environmental Art
• Video Art
• +۶ مورد دیگر

Stephanie Smith is a Lecturer in the Sculpture & Environmental Art department at The Glasgow School of Art . Her practice spans sculpture, installation, video art, and interdisciplinary projects often exploring the intersection of art, nature, and digital spaces. She frequently collaborates with Eddie Stewart on large-scale installations and conceptual works. Her research interests include environmental art , conceptual frameworks , and digital exhibitions . Recent projects like The Unseen Masterpiece (2020) and SMITH/STEWART PRESENT TENSE (2024) highlight her focus on site-specific installations and virtual art spaces . Publications such as Grey Gardens (2016) and Sprache / Language (2016) reflect her engagement with art-architecture dialogues and multilingual exhibitions . Smith’s collaborative exhibitions include Re-hang (2017) at Gray’s School of Art and Sharing a View: Contemporary Art from Glasgow (2020/21) in China, where her works Handheld and Round were presented across multiple institutions like Tsinghua University and Guangzhou Academy of Fine Arts.

Gerd Kortemeyerمشاهده پروفایل

دانشیار

• Physics Education
• Educational Technology
• Learning Analytics
• +۳ مورد دیگر

Gerd Kortemeyer is an Associate Professor in the Department of Physics & Astronomy at Michigan State University, holding a joint appointment as Associate Professor of Physics Education in Lyman Briggs College. His research focuses on technology-enhanced physics education, particularly developing tools for online learning, assessment systems, learning analytics, and educational data mining in post-secondary environments. Education: M.Sc. in Theoretical Nuclear Physics, Universität Hannover, 1993 Ph.D. in Theoretical Nuclear Physics, Michigan State University, 1997 His research investigates data from online learning venues including MOOCs, flipped classrooms, and hybrid environments, with emphasis on transaction records from formative assessments to understand student learning patterns. Current work explores AI applications in educational technology, virtual reality physics instruction, and learning management systems. Analysis of his 15 most recent publications (2023-2025) reveals dominant trends in artificial intelligence for educational assessment (grading systems, virtual assistants), multilingual/multimodal learning tools, and empirical studies of hybrid learning outcomes. Key subfields include physics concept inventories, cheat detection in online homework, and accessibility-enhancing technologies. No scientific awards were mentioned in the provided materials. Information about advised students and research grants was not specified in the source text. Dr. Kortemeyer directed MSU's Laboratory for Instructional Technology in Education (1997-2011) and is a principal developer of the LON-CAPA open-source learning content management system, widely used for physics education assessment and content delivery.

Irina Nikishinaمشاهده پروفایل

پژوهشگر

• Semantics
• Argument Mining
• Taxonomy Enrichment
• +۳ مورد دیگر

Irina Nikishina is a postdoctoral researcher at the University of Hamburg's Department of Informatics, working in the Language Technology Group under Prof. Chris Biemann. As a researcher in computational linguistics and natural language processing, she contributes to projects like ACQuA-2.0, focusing on semantics, argument mining, taxonomies, and knowledge graphs. PhD in Computational and Data Science and Engineering (2022), Skolkovo Institute of Science and Technology Bachelor's and Master's degrees from National Research University Higher School of Economics (NRU HSE) Her research spans taxonomy enrichment, comparative question answering systems, and biomedical concept representation. She organizes shared tasks like RUSSE’2020 and RuArg-2022, and co-founded the RusNLP semantic search engine for Russian NLP conferences. She chairs the Network Analysis track at the International Conference on Analysis of Images, Social Networks and Texts (AIST) and has served as secretary for AIST 2020 and 2021. Recent publications focus on large language models' performance in lexical semantics, multilingual comparative argumentation systems, and knowledge graph integration for QA tasks. Her work includes developing tools like TaxFree for candidate-free taxonomy enrichment and exploring cross-modal approaches for taxonomic graph expansion.

Nicoletta Piredduمشاهده پروفایل

استاد

• Comparative Literature
• Cultural Studies
• Cosmopolitanism
• +۷ مورد دیگر

Nicoletta Pireddu is a Professor in the Department of Italian at Georgetown University's College of Arts & Sciences. She currently serves as the Inaugural Director of the Georgetown Humanities Initiative and remains an active member of the Global and Comparative Literature Program Steering Committee after directing it until Academic Year 2023-24. Her distinguished career spans over two decades at Georgetown, where she previously served as Interim Chair of the Italian Department and Director of Graduate Studies in Italian. Italian laurea from Università degli Studi di Verona Dottorato di ricerca in English and American Literatures from Università di Venezia "Ca' Foscari" M.A. and Ph.D. in Comparative Literature from UCLA Professor Pireddu's research centers on European literary and cultural relations from the 19th century to present, with particular focus on Italian, French, and British domains. Her work explores national and transnational identities, borders and migration, literary and critical theories, cosmopolitanism, Mediterranean and island studies, and the intersection of anthropology and literature. She has pioneered scholarship on early science-fiction and translation studies, examining how literature engages with scientific concepts and cultural exchanges. Her extensive publication record includes over eighty articles in leading journals such as Comparative Literature, Romanic Review, and Journal of European Studies, along with numerous book-length publications. Her recent work shows a strong emphasis on cultural cosmopolitanism, as evidenced by her René Wellek Prize-winning edited volume Migrating Minds: Theories and Practices of Cultural Cosmopolitanism (2022) and the subsequent scholarly journal she co-founded bearing the same name. René Wellek Prize (2023) for Best Edited Essay Collection Condé Nast Award for excellence in research, teaching, service and leadership (2023) Cawley Career Champion Award (2024) American Association for Italian Studies book award (2003) Dean's Award for Excellence in Teaching (2005) Professor Pireddu has secured significant research funding from prestigious institutions including the National Endowment for the Humanities, the Howard Foundation at Brown University, and the Italian Foreign Ministry. She has mentored numerous students through innovative seminars exploring topics like European consciousness, food and fashion in "made in Italy," the avant-garde in literature and arts, and the representation of mafia in literature and film. As the inaugural Director of the Georgetown Humanities Initiative, she has fostered interdisciplinary collaboration across campus, championing the Medical Humanities Program and organizing the 2019 American Comparative Literature Association annual conference at Georgetown. Her current work centers on the Ignatius Seminar on Borders, continuing her longstanding engagement with Mediterranean Crossings and transnational cultural flows.

• Machine Learning
• Probabilistic Modeling
• Neural Networks
• +۴ مورد دیگر

Carl Allen is a Laplace Junior Chair in Machine Learning at École Normale Supérieure, Paris, working in the research group of Stéphane Mallat, Giulio Biroli and Garbiele Peyré. Previously, he was a postdoctoral fellow at ETH Zurich and completed his PhD in Machine Learning in 2021 at the University of Edinburgh under the supervision of Professors Tim Hospedales and Iain Murray. His educational background includes a BSc in Mathematics & Chemistry from the University of Southampton, an MSc in Mathematics and the Foundations of Computer Science (MFoCS) from the University of Oxford, and MScs in Artificial Intelligence and Data Science from the University of Edinburgh. Before transitioning to AI/ML research, he spent several years in Project Finance. Allen's research focuses on mathematically understanding mechanisms behind successful machine learning methods, particularly neural networks. He investigates how machine learning models exploit aspects of data distribution from a probabilistic perspective. His current topics include explaining how VAEs disentangle independent factors of data, identifying mathematical models behind self-supervised learning, and deriving probabilistic interpretations of softmax classification. His PhD work investigated neural representations of discrete objects and their relationships, with a main result explaining how word embeddings can seemingly be added and subtracted (e.g., queen ≈ king - man + woman), which received Best Paper (honorable mention) at ICML 2019. His research spans theoretical foundations of machine learning, with particular emphasis on representation learning, disentanglement, and probabilistic modeling of neural networks. His work connects mathematical principles with practical machine learning applications, aiming to develop more interpretable and reliable algorithms. Allen has received notable recognition including a Best Paper honorable mention at ICML 2019 and a research grant from the Hasler Foundation. He has delivered invited talks at prestigious institutions including Harvard Center of Mathematical Sciences & Applications and Astra-Zeneca. His collaborative work spans multiple institutions, including a notable internship at Samsung AI Centre, Cambridge, where he worked at the intersection of representation learning and logical reasoning. His research has significant implications for developing more interpretable, reliable, and theoretically grounded machine learning systems.

• Language Acquisition
• Cognitive Science
• Computational Modeling
• +۷ مورد دیگر

Emmanuel Dupoux is a Professor at École des Hautes Études en Sciences Sociales (EHESS), affiliated with the School of Advanced Studies in Social Sciences and the Laboratory of Cognitive Science and Psycholinguistics (LSCP). His work bridges cognitive science, computational linguistics, and machine learning to study infant language acquisition and social cognition. Co-creator and director of EHESS Cognitive Science Master program Former LSCP laboratory director (1998-2009) Current research focuses on textless speech modeling and ecological audio analysis Research areas include: Modeling early language acquisition mechanisms using Bayesian models and HMM Investigating phonological 'deafness' and critical age plasticity Studying social cognition development through infant-toddler experiments His technical contributions span speech processing toolkits like Shennong, emergent communication frameworks (STOP dataset), and innovative approaches to self-supervised speech modeling. Recent publications demonstrate breakthroughs in: Topography-inspired CNN designs for better memory efficiency Prosody-aware generative spoken language models (pGSLM) Textless emotion conversion systems He actively explores how machine learning can reverse-engineer infant language learning processes from ecological audio data, with applications in neurodegenerative disease diagnostics. Key collaborations include: INRIA's Cognitive Machine Learning (CoML) team Facebook AI Research (FAIR) partnerships VoxPopuli multilingual speech corpus development

Jacopo Staianoمشاهده پروفایل

استادیار

• Natural Language Processing
• Artificial Intelligence
• Social Network Analysis
• +۷ مورد دیگر

Jacopo Staiano is a Senior Assistant Professor (RTDb) at the Department of Economics & Management, University of Trento (Italy). His academic journey includes previous positions as Head of Research at reciTAL.ai, research affiliate at Data-Pop Alliance, senior data scientist at Fortia Financial Solutions, and post-doctoral researcher at LIP6, UPMC - Sorbonne Universités and Fondazione Bruno Kessler. Staiano received his BSc in Computer Engineering from the University of Pisa (2003), an MA in Sonic Arts from Queen's University of Belfast (2005), and an MSc in Human Language Technologies and Interfaces from the University of Trento (2010). He completed his PhD under Prof. Nicu Sebe at the Department of Information Engineering and Computer Science, University of Trento. His academic visits include the Intelligent Systems Lab at University of Amsterdam, Ambient Intelligence Research Lab at Stanford University, Human Dynamics Lab at MIT Media Lab, and Telefonica I+D. Staiano's research spans multiple domains with a strong focus on Natural Language Processing and Human-Computer Interaction. His work ranges from modeling human behavior when interacting with technology to analyzing social network structures and virality dynamics. His recent publications demonstrate a significant shift toward large language models, with applications in sustainability reporting, medical diagnostics, financial analysis, and bias detection. His work shows sophisticated integration of technical AI capabilities with social science perspectives. Staiano has received several prestigious awards throughout his career, including an Honorable Mention at ACM DIS 2012, Best Paper Award at ACM UbiComp 2014, the UMUAI James Chen Award 2016, and most recently the Ten Year Technical Impact Award from ACM ICMI 2024. These awards reflect the sustained impact and quality of his research across multiple domains. His research has been supported by collaborations with major institutions including MIT Media Lab, Stanford University, and Telefonica I+D, as well as industry partnerships. His work on projects like DepecheMood for emotion analysis and SALSA for multimodal group behavior analysis has established him as a significant contributor to affective computing and social signal processing. Staiano maintains active connections with multiple research communities, particularly in the areas of computational social science, natural language processing, and affective computing. His work bridges technical AI development with real-world applications in finance, healthcare, and social good initiatives.