جست‌وجوی استاد و پژوهشگر

• Egyptology
• Coptic Studies
• Computational Linguistics
• +۵ مورد دیگر

Eliese-Sophia Lincke is a Junior Professor at the Department of History and Cultural Studies, Freie Universität Berlin, since May 2022. Her work bridges computational methods with Egyptology, focusing on digital tools for studying ancient texts. Bachelor's and Master's in Egyptology, Humboldt-Universität zu Berlin (2007) PhD in "The Conception of Spaces in Language" (TOPOI Cluster, 2012) Research interests include: Digital Humanities : Developing machine learning models for Hieroglyphic, Demotic, and Coptic text processing Linguistic Typology : Analyzing classifier systems in Ancient Egyptian and Sign Languages Spatial Linguistics : Investigating prepositions and spatial adverbs in Egyptian-Coptic Recent publications focus on Neural Lemmatization , OCR for Coptic , and Classifier Semantics , demonstrating her commitment to computational Egyptology. Scientific awards include the Humboldt-Preis 2008 for best Master's thesis and the Prize for Good Teaching 2014 . She has co-organized workshops like "Wege zum Ägyptischen" and served as Co-Editor for Lingua Aegyptia . Her teaching contributes to the Digital Studies of Ancient Texts Master's program.

• Computational Linguistics
• Natural Language Processing
• Multilingual Models
• +۷ مورد دیگر

Malvina Nissim is a leading researcher in computational linguistics and NLP at the University of Groningen's Department of Artificial Intelligence, with a focus on multilingual modeling, bias mitigation, and human evaluation frameworks. Key Contributions : Developed CALAMITA (Italian LLM benchmark), IT5 models for Italian language processing, and ReproHum framework for NLP evaluation reproducibility Research Pillars : Multilingual reasoning consistency, perspective-based text analysis, and figurative language modeling Her work spans activation steering techniques, cross-lingual transfer learning, and the creation of specialized language resources like the EurekaRebus dataset and MAGPIE idiom corpus. She pioneered methods for gender bias measurement in BERT and developed the SocioFillmore tool for perspective visualization. Recent publications explore model uncertainty as MCQ difficulty proxy, Italian headline generation benchmarks, and multilingual multi-figurative language detection. She actively participates in teaching initiatives like the "NLP with Bracelets" workshop for Italian high school students. Scientific Awards : ACL Best Paper Award (2025) EMNLP Outstanding Reviewer (2023) EVALITA Leadership Recognition (2024) She advises PhD students in model bias analysis and has contributed to the development of the Dutch Abusive Language Corpus (DALC) and the ReproNLP reproducibility framework. Her collaborations span institutions in Italy, Netherlands, and international NLP communities.

Paul Raysonمشاهده پروفایل

استاد

• Natural Language Processing
• Corpus Linguistics
• Semantic Multilingual NLP
• +۷ مورد دیگر

Professor Paul Rayson is a Professor of Natural Language Processing in the School of Computing & Communications at Lancaster University, UK. He serves as Director of the UCREL (University Centre for Computer Corpus Research on Language) interdisciplinary research centre and is affiliated with multiple research institutes including Security Lancaster, the Lancaster Centre for Digital Humanities, and the Data Science Institute. Education: PhD in Computer Science, Lancaster University (2003) BSc (Hons) Computer Science and Mathematics, Lancaster University (1990) Professor Rayson's research focuses on semantic multilingual Natural Language Processing (NLP) in challenging linguistic environments with noisy language data, including historical texts, learner language, speech, email, and other computer-mediated communication. His work spans applications in dementia detection, mental health analysis, online child protection, cyber security, learner dictionaries, and text mining of biomedical literature, historical corpora, and financial narratives. He has developed semantic tagging tools like USAS (UCREL Semantic Analysis System) and Wmatrix for corpus analysis. Major Awards and Honors: FHEA (Fellow of the Higher Education Academy) MBCS (Member of the British Computer Society) Professor Rayson has supervised numerous PhD students in NLP and corpus linguistics, with eight current students and seven completed doctorates. He has led or co-investigated multiple major research projects including the £3.5m ESRC-funded Centre for Corpus Approaches to Social Science (CASS), the National Corpus of Contemporary Welsh, and projects related to mental health forums, financial narrative analysis, and cyber security. His research has been supported by ESRC, EPSRC, and other funding bodies. As Director of UCREL, he oversees research in corpus linguistics and NLP. He is also active in the Cyber Security Research Centre, Digital Health Group, and multiple Data Science Institute initiatives. His lab has developed several widely-used NLP tools including CLAWS for English POS tagging, USAS semantic analysis system, Wmatrix corpus analysis tool, and the Variant Detector (VARD) for historical texts.

• Artificial Intelligence
• Natural Language Processing
• Machine Learning
• +۴ مورد دیگر

Zenun Kastrati is an Associate Professor at the Department of Informatics, Linnaeus University. His research focuses on Artificial Intelligence, Natural Language Processing, Machine Learning, Semantic Web, Sentiment Analysis, and Learning Technologies. He contributes to the Data-driven Business Innovation (DBI) and Interaction Design Research Groups, leading projects like Forest 4.0, RAPID, and IGNITE. His recent work involves Explainable AI, medical imaging, and multilingual NLP. Ph.D. in Computer Science (NTNU, 2018) Master's in Computer Science (EU TEMPUS Programme) Previous Lecturer/Researcher at University of Prishtina His research spans AI applications in medical diagnostics , NLP , sentiment analysis , and semantic technologies . Key projects include Forest 4.0 (environment monitoring) and RAPID (online education in Pakistan). Publications highlight his expertise in deep learning , transformer models , and context-aware systems . Recent publications demonstrate trends in Explainable AI (XAI) for healthcare, medical imaging techniques, and multilingual NLP frameworks. Other work explores social media analytics , student feedback analysis , and pedagogical document classification . Zenun's teaching includes Fundamentals of Programming , Object-Oriented Programming , Web Applications , Data Analytics , and Adaptive Web courses at BSc and MSc levels.

Ludovic Vetea Mompelatمشاهده پروفایل

استادیار

• Linguistics
• Natural Language Processing (NLP)
• Creole Languages
• +۵ مورد دیگر

Ludovic Vetea Mompelat is an Assistant Professor at the University of Miami 's College of Arts and Sciences . His research focuses on linguistics, natural language processing (NLP), and computational analysis of creole languages such as Martinican and Haitian Creole. He specializes in integrating artificial intelligence into language education and exploring syntactic typology, ellipsis constructions, and linguistic barriers in healthcare. Research Interests Dr. Mompelat investigates: POS tagging and error analysis in creole languages AI-driven solutions for linguistic barriers in healthcare Computational approaches to ellipsis constructions and syntactic finiteness Corpus development for discourse analysis (e.g., conspiracy theories) and event sequencing Publications & Trends Recent articles highlight his work on NLP for under-resourced creole languages, contrasting classical NLP with modern LLMs, and leveraging AI to address linguistic challenges in healthcare and education. His studies often involve comparative syntax analysis across Martinican, Haitian, and French languages, alongside creating annotated corpora for machine learning applications.

Kalina Bontchevaمشاهده پروفایل

پژوهشگر

• NLP for social media
• semantic search
• GATE infrastructure
• +۸ مورد دیگر

Kalina Bontcheva is a Senior Researcher in the Natural Language Processing Group within the Department of Computer Science at the University of Sheffield. She holds an EPSRC Career Acceleration Fellowship (working part-time since October 2015) focused on personalized summarization of social media content. Her research spans multiple EU-funded projects including PHEME (computing veracity of social media), TrendMiner, DecarboNet, and uComp, with significant contributions to the GATE (General Architecture for Text Engineering) open-source NLP infrastructure since 1999. Dr. Bontcheva's research interests focus on the intersection of natural language processing and social media analysis. Her work encompasses NLP for social media, semantic search, information extraction from social platforms, crowdsourcing of NLP corpora, collaborative text annotation, semantic technologies, and text mining and analytics. She has particular expertise in developing methods for personalized, abstractive multi-document summarization across different social media platforms, addressing the challenges of noisy, jargon-filled and dynamic content. Her interdisciplinary approach combines machine learning, semantic technologies, and social dimension analysis to create systems that adapt to individual users' information seeking goals. Analysis of her recent publications reveals a strong focus on social media processing challenges, with emphasis on Twitter analysis, temporal expression recognition, and handling noisy text. Her work consistently addresses the unique characteristics of social media content and develops specialized techniques for information extraction, sentiment analysis, and user geolocation within these platforms. The GATE framework serves as the foundation for much of her tool development, demonstrating her commitment to creating reusable, open-source NLP infrastructure. Her most significant award is the EPSRC Career Acceleration Fellowship, which supports her work on personalized social media summarization. This prestigious fellowship includes a substantial budget of £560k and involves collaborations with industry partners including The Press Association, British Telecom, and Fizzback. Dr. Bontcheva has led numerous major research projects throughout her career. She was Principal Investigator on three EU-funded projects (MUSING, TAO, and ServiceFinder) between 2006-2009, coordinating the TAO consortium with seven partner institutions. She currently leads the PHEME EU project and serves as PI for TrendMiner and DecarboNet European projects, while also contributing as Co-I on the uComp project. Her project portfolio demonstrates consistent success in securing competitive research funding across multiple domains within NLP and semantic technologies. She works within the Natural Language Processing Group at the University of Sheffield, which has been central to the development of the GATE infrastructure. Her work connects with various initiatives including the GATE Cloud platform and the TextVRE project for e-humanities textual studies. She has established collaborations with organizations including the Press Association, British Telecom, Oxford Internet Institute, and Sheffield's Department of Journalism to ensure her research addresses real-world needs across different user communities.

• Natural Language Processing
• Information Extraction
• Deep Learning
• +۱۰ مورد دیگر

Thien Nguyen is an Associate Professor in the Department of Computer Science at the University of Oregon, within the College of Arts and Sciences. His research focuses on natural language processing, information extraction, and deep learning, with an emphasis on multilingual and large-scale language models. Ph.D., Computer Science, New York University M.S., Computer Science, New York University B.S., Computer Science, Hanoi University of Science and Technology His research explores how computers can understand human language to perform cognitive tasks, particularly by distilling structured information from massive multilingual text. He is a pioneer in applying deep learning to information extraction and has developed influential models and datasets such as CulturaX , Vistral , and Okapi . His lab designs learning algorithms for NLP tasks including event detection, machine translation, and chatbots. The recent work centers on large language models, cross-lingual transfer, and continual learning. His 15 most recent publications reflect a strong trend in multilingual NLP , large language models , event and relation extraction , and active and continual learning . These works span dataset creation, model development, and evaluation frameworks, often leveraging transformer architectures and reinforcement learning. The research is highly interdisciplinary, combining data mining, machine learning, and linguistic analysis. NSF CAREER Award (2023) Best Demo Paper Award, EACL 2021 Outstanding Demo Paper Award, EACL 2021 IBM Ph.D. Fellowship (2016) Dean's Dissertation Fellowship, NYU Harold Grad Prize, NYU Dr. Nguyen advises multiple Ph.D. and M.S. students and has secured significant research funding from the NSF, IARPA, and Adobe Research. His lab, UO-NLP, is actively developing tools like Trankit and FourIE . He teaches courses in data structures, machine learning, and NLP, and serves on the program and senior committees of top-tier conferences such as ACL, EMNLP, and NeurIPS. He is deeply involved in advancing multilingual NLP and democratizing access to language technologies across diverse languages.

Ehsan Doostmohammadiمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Natural Language Processing (NLP)
• Language Models
• +۵ مورد دیگر

Ehsan Doostmohammadi is a Researcher at the Artificial Intelligence and Integrated Computing Systems (AIICS) department of Linköping University . His work focuses on Natural Language Processing (NLP) and Language Model Optimization , with particular interest in Retrieval-Augmented Models , Multimodal Learning , and Low-Resource Language Processing for Persian and Swedish. Research Interests : Retrieval-Augmented Language Models Swedish Language Processing Persian Language Technology Medical Text Analysis Cross-lingual Transfer Learning Publications : 15 recent articles spanning 2018–2025 Key themes: AI , NLP , Language Model Efficiency

• Digital Responsibility
• Natural Language Processing
• Machine Learning
• +۳ مورد دیگر

Thomas Arnold is a Postdoctoral researcher at Technische Universität Darmstadt, specializing in Digital Responsibility, Natural Language Processing, and Machine Learning. His work focuses on developing automated tools for measuring corporate digital responsibility activities and detecting machine-generated text across multiple domains and languages. He actively participates in initiatives like Semeval tasks and has contributed to frameworks like M4 and M4gt-bench for evaluating black-box text generation systems. His research spans advanced motif analysis in text-induced networks, hierarchical data summarization, and privacy-preserving text rewriting (DP-rewrite). Notable projects include QUEST, an educational tool leveraging engaging storytelling for interactive quizzes, and EmpiriST, a robust tokenization and POS-tagging system for diverse text genres. Publications highlight trends in ethical AI, corporate strategy evaluation, and cross-domain NLP challenges. Recent work emphasizes transparency in AI systems and the intersection of digital ethics with corporate governance. He is affiliated with TU Darmstadt's Department of Computer Science (implied through research focus) and maintains professional profiles on LinkedIn. No specific awards or grants are listed in the provided data.

Aleksi Sahalaمشاهده پروفایل

پژوهشگر

• Languages
• History and Archaeology
• Computer and Information Sciences
• +۲ مورد دیگر

Aleksi Sahala is a Postdoctoral Researcher at the University of Helsinki's Department of Digital Humanities, affiliated with the Language Technology Centre of Excellence in Ancient Near Eastern Empires (ANEE). His work bridges computational linguistics and ancient language studies, focusing on Akkadian, Sumerian, and Egyptian scripts. Research Interests: Developing neural models for lemmatization and POS-tagging of ancient languages Analyzing phonotactic patterns in Sumerian Exploring semantic domains in Akkadian texts Digital humanities approaches to cuneiform corpora Recent research outputs demonstrate technical expertise in natural language processing applied to historical scripts, including contributions to workshops on machine learning for ancient languages and computational analysis of Neo-Assyrian texts.

Anne O'Keeffeمشاهده پروفایل

استاد

• Corpus Linguistics
• Applied Linguistics
• Pragmatics
• +۴ مورد دیگر

Professor Anne O'Keeffe is a distinguished academic specializing in Applied Linguistics at Mary Immaculate College, University of Limerick. As Director of the Inter-Varietal Applied Corpus Studies (IVACS) Research Centre, she leads projects analyzing online workplace discourse through multimodal corpus methods. Her work bridges corpus linguistics with second language acquisition, focusing on pattern recognition and data-driven learning. Current affiliation: University of Limerick Director: IVACS Research Centre PhD supervision: 14 current students Research interests span Corpus Linguistics , Pragmatics , and Discourse Analysis , with particular focus on Learner Corpora and Media Discourse . She pioneered the Limerick Corpus of Irish English and explores digital communication patterns post-COVID-19. Recent publications examine virtual workplace discourse (2024), data-driven learning design (2023), and pos tag sequences in L2 acquisition (2024). These works demonstrate intersections between usage-based theory and pedagogical innovation . Scientific recognition includes the Government of Ireland International Scholarship (2015). Her supervision extends to PhD candidates analyzing learner grammar , corpus applications , and virtual communication patterns .

Jakob Prangeمشاهده پروفایل

پژوهشگر

• Computational Linguistics
• Natural Language Processing
• Formal Semantics
• +۱۲ مورد دیگر

Jakob Prange is a Researcher (Akademischer Rat auf Zeit) at the Chair for Natural Language Understanding / Digital Humanities within the Faculty of Applied Computer Science at the University of Augsburg. He holds a Ph.D. in Computer Science with a concentration in Cognitive Science from Georgetown University, where his dissertation focused on neuro-symbolic models for syntactic and semantic representations. Education: Ph.D. in Computer Science (Cognitive Science), Georgetown University B.Sc. in Computational Linguistics, Saarland University His research lies at the intersection of computational linguistics and theoretical linguistics, emphasizing formal and distributional semantics, meaning representation, deep learning, and neuro-symbolic integration. He prioritizes model efficiency and explainability, often combining neural models with structured linguistic representations. His recent work includes projects on cross-lingual QA in migration contexts and Bayesian modeling of L2 preposition learning. His publications span top venues such as ACL, NAACL, TACL, and COLING, with a focus on semantic parsing, supersense tagging, UCCA, neuro-symbolic modeling, and robust NLP for German. He has contributed to multilingual annotation frameworks and low-resource language modeling. Scientific Awards: No awards explicitly mentioned. He has supervised M.Sc. student Steffen Kleinle on a QA project and contributes to teaching at the University of Augsburg, including Python for language processing and NLP tutorials. He is part of the HLT@Augsburg research group led by Prof. Annemarie Friedrich, focusing on natural language understanding and digital humanities.

Matthieu Labeauمشاهده پروفایل

مدرس ارشد

• Natural Language Processing
• Machine Learning
• Representation Learning
• +۲ مورد دیگر

Matthieu Labeau is a Senior Lecturer at Télécom Paris, affiliated with the Department of Image, Data, Signal (IDS). He joined the institution in 2019 after completing his PhD at the University of Paris-Saclay and a postdoctoral position at the University of Edinburgh. His research primarily centers on Natural Language Processing (NLP), with specialized interests in representation learning, language modeling, and conversational AI. His work spans: Core NLP : Contextual word representations, semantic alignment, and polysemy analysis. Machine Learning : Hierarchical classification, graph prediction, and few-shot learning techniques. Applications : Emotion recognition in dialogues, persuasiveness decoding, and educational NLP tools. Labeau leads research in the Signal, Statistics and Learning (S2A) team at the Information Processing and Communication Laboratory (LTCI). His recent publications demonstrate a strong focus on improving language model interpretability and efficiency, with innovations in tokenization effects and multimodal fusion. Though no awards or grants are mentioned, his consistent output in top-tier venues (e.g., NeurIPS, ACL, AAAI) highlights significant scholarly contributions. He actively collaborates on tools like EZCAT for conversation annotation and mentors researchers in NLP projects. Current work explores LLM capabilities in persuasion assessment and optimal transport methods for graph-based learning.

Johnatan E. Bonillaمشاهده پروفایل

پژوهشگر

• Corpus Linguistics
• Computational Linguistics
• Sociolinguistics
• +۳ مورد دیگر

Dr. Johnatan E. Bonilla is a Researcher at Humboldt-Universität zu Berlin's Institut für Romanistik, affiliated with Project A09 (register and dialect variation in Canarian Spanish) and the MGK Integrated Graduate School. His work focuses on corpus linguistics, computational linguistics, and the intersection of sociolinguistics with natural language processing. He holds a PhD in Linguistics from Ghent University and a Master's from the Instituto Caro y Cuervo (Colombia). Key projects include digitizing the Linguistic and Ethnographic Atlas of Colombia (ALEC), developing the New Linguistic Atlas of Colombia (NALAC), and creating the morphosyntactic treebank UD Spanish-COSER for spoken Spanish. He has contributed to gamified approaches for corpus annotation via projects like Juegos del Español. His recent publications explore spoken Spanish POS tagging, geographic influences on linguistic variation, and dialectal corpus development through GWAPs. Bonilla actively contributes to open-source repositories on GitHub (e.g., COSER-PoS.v1/v2) and collaborates with initiatives like Universal Dependencies.

Nan Niuمشاهده پروفایل

دانشیار

• Requirements Engineering
• Machine Learning
• Software Engineering
• +۵ مورد دیگر

Dr. Nan Niu is an Associate Professor in the Department of Electrical Engineering and Computer Science (EECS) at the University of Cincinnati. He specializes in requirements engineering, software traceability, and model-driven approaches. His work focuses on machine learning applications, continuous deployment, and testing scientific software. Dr. Niu holds a Ph.D. in Computer Science from the University of Toronto (2010, supervised by Steve Easterbrook), an M.Sc. from University of Alberta (2006), and a B.Eng. from Beijing Institute of Technology (2004). Research interests include software engineering challenges in AI/ML systems, automated refactoring, and environment-driven requirements engineering. His research is funded by agencies like NSF, NSA, and industry partners like P&G. Recent publications address topics like POS tagging in code, GUI reuse via vision-language models, and privacy concerns in mobile apps. Teaching: Software Engineering (EECE3093C), Requirements Engineering (CS5127/6027), and Large-Scale Software Engineering (CS5128/6028) Labs/Teams: Active in requirements traceability and scientific software testing Awarded over 15 honors including NSF CAREER Award (2014-2019), Best Paper Awards at RE (2016,2018,2021), and teaching excellence recognition.