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Jennifer FosterView profile

Associate Professor

• Natural Language Processing
• Artificial Intelligence
• Sentiment Analysis
• +4 more

Dr. Jennifer Foster is an Associate Professor and Associate Dean for Teaching and Learning in the Faculty of Engineering and Computing at Dublin City University. She specializes in Natural Language Processing (NLP) and AI, with a focus on language parsing, sentiment analysis, and Irish language technology. She leads projects funded by Science Foundation Ireland (SFI) and other agencies, supervising 11 PhD students to completion and currently mentoring four more. Her research spans NLP applications including grammar checking, question answering, and neural language model evaluation. She teaches NLP courses for Data Science and Computing programs, as well as introductory Python programming. Foster has authored over 100 peer-reviewed publications and serves on conference program committees, including the Association for Computational Linguistics executive board (2016-2019). Recent work includes developing gaBERT, an Irish language model, and exploring machine-generated story coherence. Her contributions to resources like the Irish Universal Dependencies Treebank and the GenERRate error-generation tool highlight her commitment to advancing NLP for under-resourced languages.

• Summarization
• Text Generation
• Scientific Document Processing
• +3 more

Jessica Ouyang is an Assistant Professor of Computer Science at the University of Texas at Dallas (UTD), affiliated with the Erik Jonsson School of Engineering and Computer Science. Her research focuses on computational narrative, text generation, and scientific document processing, with applications in healthcare and social media analysis. **Education**: PhD in Computer Science (Columbia University, 2019) MS in Computer Science (Columbia University, 2015) BAS in Computer and Cognitive Science & BA in Linguistics (University of Pennsylvania, 2012) **Research Interests**: Jessica’s work bridges NLP and computational linguistics, emphasizing: Automated trauma intervention tools using machine learning Citation text generation and scientific document analysis Narrative structure modeling for healthcare and activism Her 2021 Best Paper Award at WASSA recognized work on detecting hashtag hijacking in social movements. **Key Contributions**: Over 15 peer-reviewed publications since 2019, including influential work on: Related work generation frameworks (CORWA dataset) Lightweight multimodal models for sequential data Computational analysis of medical student career choices Active in academic service, she serves as Area Chair for ACL Rolling Review and program committee member for top conferences like AAAI and EMNLP.

• Natural Language Processing
• Ethics in NLP
• Bias Detection
• +8 more

Margot Mieskes is a Researcher in Natural Language Processing with a focus on Ethics in NLP , Bias Detection , Autism Detection , and Reproducibility in Research . She has contributed to Multilingual NLP , Multimodal Analysis , and Peer Review Practices through numerous publications and workshops. Research Trends: Her work addresses ethical guidelines for NLP, bias in multilingual models, emotion detection, and the challenges of replicating human evaluations. Key Contributions: Margot co-authored the 2024 survey on autism detection in speech, 2023 studies on cross-lingual bias evaluation, and 2019 analyses of summarization metrics and OCR impacts. Workshops: She actively participates in teaching NLP workshops (2016–2023) and tutorials on ethical research (2025) and reviewing practices (2020, 2021). Collaborations: Margot has collaborated with researchers like Nadine Probol, Karën Fort, and Michael Strube on topics ranging from disfluency detection to OCR preprocessing.

Maria LiakataView profile

Professor

• Natural Language Processing
• Semantics and Discourse
• Social Media Analysis
• +7 more

Maria Liakata is a Professor of Natural Language Processing at Queen Mary University of London, where she serves as Deputy Centre Lead and 'Health and Wellbeing' Theme Lead for the Centre for Human-Centred Computing within the School of Electronic Engineering and Computer Science. She leads multiple research initiatives focusing on applying NLP techniques to healthcare applications, particularly mental health monitoring through social media and longitudinal user-generated content analysis. Her research interests span Natural Language Processing, Semantics and Discourse, Social Media analysis, Machine Learning, BioNLP, and NLP for Mental Health. Dr. Liakata has made significant contributions to knowledge discovery from corpora, automation of scientific experimentation, and automatic extraction of information from scientific literature. Her work has practical applications in mental health monitoring, dementia diagnosis, and rumor verification systems. Her recent publications demonstrate a strong focus on longitudinal analysis of language for mental health applications, temporal modeling of user-generated content, and healthcare AI. She has developed novel techniques for detecting changes in user representations over time, which have applications in mental health monitoring and early dementia diagnosis. Her research bridges the gap between technical NLP advancements and real-world healthcare challenges. EPSRC/UKRI Turing AI fellowship award on Creating Time Sensitive Sensors from Language & Heterogeneous User-Generated Content (2019-2025) IBM Faculty Award for work on emotion sensing from heterogeneous mobile phone data EU Project PHEME co-investigator (2014-2017) studying the spread of rumours in social media Early Career Fellowship from the Leverhulme Trust (2010-2013) on reasoning with scientific articles Dr. Liakata supervises a diverse group of PhD students working on cutting-edge NLP applications for healthcare, including mental health monitoring, dementia diagnosis, and medical imaging analysis. She leads multiple substantial research grants totaling millions of pounds from EPSRC, MRC, Wellcome Trust, and industry partners. Her current projects include 'Addressing socio-technical limitations of LLMs for medical and social computing' and 'Social media, Smartphone use and Self harm in Young People (3S-YP study)'. She leads the 'Health and Wellbeing' research theme within the Centre for Human-Centred Computing and collaborates closely with the Centre for Multimodal AI. Her interdisciplinary research team combines expertise in NLP, machine learning, clinical psychology, and healthcare informatics to develop practical AI solutions for real-world health challenges.

Nozha BoujemaaView profile

Researcher

• Multimedia Content Search
• Pattern Recognition
• Machine Learning
• +3 more

Nozha Boujemaa is a Research Director at Inria and Director of DATAIA Institute, leading projects in Data Sciences, Algorithmic Transparency, and Societal Impact. She co-founded the Digital Society Institute (ISN) and serves as a Senior Scientific Advisor for AI initiatives. Expert in Large Scale Multimedia Content Search, Pattern Recognition, and Machine Learning Developed methods for visual content enrichment, interactive retrieval, and satellite image analysis Scientific leader of Pl@ntNet (plant identification), CHORUS (multimedia search engines), VITALAS, MUSCLE, and TRENDS projects Her research spans Multimedia Retrieval , Big Data Applications , and Algorithmic Transparency , with over 150 publications. She has supervised 25+ PhD/Master's students and organized conferences like ACM Multimedia 2013 and European Big Data Value Forum 2017. Key scientific awards include: Knight of the National Order of Merit (France) She has contributed to international projects (NSF, European Commission), served on editorial boards for Multimedia Tools and Applications , and co-chaired workshops on visual digital libraries and AI ethics. Her work impacts web search, cybersecurity, biodiversity, and earth observation.

Sonia MandinView profile

Researcher

• Educational Technologies
• Learning Sciences
• Computer-Assisted Learning
• +5 more

Sonia Mandin is a Postdoctoral researcher in educational sciences specializing in educational technologies at the French Institute of Education (EducTice) at École Normale Supérieure de Lyon. She has been working as a Post-Doc researcher with the Eductice team since October 2015. Her professional background includes positions as a teaching assistant at DILIPEM, Grenoble-3 since 2014, and previous postdoctoral research with the LIRIS - CNRS SILEX team from 2013-2015. Her educational background is impressive and interdisciplinary. She earned her doctorate in educational sciences from LSE, Grenoble 2 in 2009 with 'Very honorable mention with congratulations from the jury.' Prior to this, she completed a DEA in educational sciences (2003), a Master's in Educational Sciences (2002), and a degree in educational sciences (2001), all from SEAD, Lille 3 with honors. Her technical foundation was established with a DUT in computer science engineering from IUT A, Lyon 1 in 1998. Dr. Mandin's research focuses on the complex process of learning from an interdisciplinary perspective, integrating insights from psychology, didactics, and computer science. Her work centers on assisting learners through appropriate digital activities by developing computational models that can be implemented in educational technology tools. A significant portion of her research has focused on summarization skills, exploring how to help students better understand texts through effective summarization techniques. She has developed expertise in Latent Semantic Analysis (LSA) and its application to educational contexts, particularly in the development of the Résum'Web system for improving students' summarization abilities. Analysis of Dr. Mandin's recent publications reveals a strong focus on adaptive learning systems, competency-based education, and the application of natural language processing to educational contexts. Her work demonstrates a consistent trajectory from foundational research on text summarization to broader applications in personalized learning environments. Key themes include learner modeling, knowledge representation through ontologies, and the development of feedback mechanisms that support student learning. Her research bridges cognitive science with practical educational technology applications, particularly in mathematics education and writing instruction. Dr. Mandin has been actively involved in several significant research projects including the e-education project 'OCINAEE' (2015-2016), the 'Cartographie des savoirs' project (2013-2015), the European 'Language Technologies for Lifelong Learning' project (2008-2011), and the ACI Ecole et Sciences Cognitives project (2003-2005). She has also served as a speaker for the Canopé Network (formerly CNDP), the National Agency for the Use of ICT in education. Her work spans multiple research teams and institutions, including collaborations with the Knowledge Media Institute at the Open University of Milton Keynes, and research positions at LIRIS - CNRS and LSE, Grenoble. This diverse institutional engagement has allowed her to develop a rich perspective on educational technology applications across different educational contexts.

Rob GaizauskasView profile

Professor

• Natural Language Processing
• Information Extraction
• Temporal and Spatial Information Processing
• +7 more

Professor Rob Gaizauskas is a faculty member at the University of Sheffield , serving as Co-Director of the UKRI Centre for Doctoral Training in Speech and Language Technologies and leading the Natural Language Processing (NLP) research group . His academic journey began with a DPhil in Cognitive and Computing Sciences from the University of Sussex (1992), preceded by degrees in Philosophy from Carleton University and a Diploma in Information Processing. Education : DPhil (University of Sussex, 1992), MA (Carleton University, 1978), BA (Carleton University, 1975) His research focuses on NLP , particularly information extraction from texts, temporal/spatial information processing , automatic image description , argument mining , and evaluation of NLP systems . He has pioneered work in multi-document summarization , dialogue analysis , and comparable corpora for machine translation. Notable grants include: UKRI Centre for Doctoral Training in Speech and Language Technologies (2019–2027, £5.5M) VisualSense (2013–2016, £310k) SENSEI Project (2013–2016, £459k) ACCURAT (2010–2012, £268k) Scientific contributions : Co-developer of the GATE framework for text engineering Led biomedical NLP projects like BioWSD and PASTA Pioneering work in temporal relation identification (TempEval)

Grigorios TsoumakasView profile

Professor

• Machine Learning
• Natural Language Processing
• Ensemble Methods
• +6 more

Grigorios Tsoumakas is a Professor of Machine Learning and Knowledge Discovery at the School of Informatics, Department of Informatics, Aristotle University of Thessaloniki. He has held academic positions at the same department since 2007, including Lecturer (2007-2013), Assistant Professor (2013-2020), Associate Professor (2020-2024), and Professor since 2024. He is also an Affiliate Researcher at Archimedes/RC Athena and academic co-founder of the spin-off company Medoid AI (founded in 2019). BSc in Informatics (1999), MSc in Artificial Intelligence (2000), and PhD in Computer Science (2005) from Aristotle University of Thessaloniki MSc in Artificial Intelligence from the University of Edinburgh (2000) His research expertise focuses on supervised learning (ensemble methods, multi-target prediction, interpretability) and natural language processing (semantic indexing, keyphrase extraction, summarization). He has published over 150 papers with more than 20,000 citations and an h-index of 53 according to Google Scholar. Honors include the ECML PKDD 10-Year Test of Time Award (2017) and the Marco Ramoni Best Paper Award at AIME 2021. He is a senior member of IEEE and ACM. Teaches undergraduate and postgraduate courses including Machine Learning, Natural Language Processing, and Object-Oriented Programming Contributed to projects like AMULET and ECARLE

Mihai DascăluView profile

Professor

• Natural Language Processing
• Artificial Intelligence
• Machine Learning
• +4 more

Mihai Dascălu is a faculty member at the Faculty of Automatic Control and Computers , University Politehnica of Bucharest , with additional affiliation at the Academy of Romanian Scientists . His work spans Natural Language Processing , Intelligent Tutoring Systems , and Learning Analytics , focusing on automated comprehension modeling, text summarization, and psychomotor training systems. Research Interests : Reading comprehension, cohesion network analysis, large language models (ChatGPT), automated assessment, dialogism in education, and psychomotor skill development. Key Contributions : Development of the ReaderBench framework for collaborative learning analysis, validation studies integrating AI with educational psychology, and datasets for large-N educational research. Publications : 62 items (2008–2024), including 15 recent works on multitask scoring, domain adaptation, and AI-driven educational tools. Collaborations : Frequent co-authorship with Dragos Corlatescu, Laurentiu Neagu, Stefan Ruseti, and Robert Botarleanu across institutions like Arizona State University, Mines ParisTech, and Romanian Academy.

Lina Ochoa VenegasView profile

Assistant Professor

• Software Engineering
• Cloud Computing
• Software Architecture
• +3 more

Lina Ochoa Venegas is an Assistant Professor in the Department of Software Engineering and Technology at Eindhoven University of Technology (TU/e), affiliated with the EAISI High Tech Systems initiative. Her research focuses on software architecture, API design, software evolution, and dependency analysis, with a particular emphasis on improving software quality, maintainability, and developer productivity. She holds a Ph.D. in Computer Science and has taught courses such as Programming, Programming for Applied Physics, and Software Evolution. Her work bridges theoretical advancements and practical applications in software engineering, including studies on breaking changes, architecture recovery, and educational technology for young learners. Her research interests span software architecture communication, API security, multi-lingual system dependencies, and the impact of breaking changes in open-source ecosystems. Notable contributions include the BreakBot tool for analyzing breaking changes and systematic reviews on harmful API uses and repair techniques. Awards: Best Teacher Award (Bachelor Data Science 2024), VERSEN PhD Award (2024). Grants & Projects: Supervision of 12 academic works and contributions to datasets on software evolution challenges. Labs & Teams: Active in TU/e’s EAISI initiative, collaborating on high-tech systems research.

Jan Milan DeriuView profile

Researcher

• Natural Language Processing
• Artificial Intelligence
• Machine Learning
• +3 more

Jan Milan Deriu is affiliated with the ZHAW School of Engineering, where he is part of the Centre for Artificial Intelligence. He holds the role of Researcher and has been actively involved in multiple research projects, serving as Project Leader and Deputy Project Leader in areas such as dialogue systems evaluation, speech translation, and misinformation analysis. His work spans academic publications in top conferences and journals, focusing on AI-driven solutions in natural language processing and related fields. His research interests are centered around Natural Language Processing (NLP), including dialogue systems, text generation, and sentiment analysis; Artificial Intelligence evaluation methodologies; Speech technology, particularly dialect recognition and speech-to-text systems; Analysis of organized misinformation in social networks; Machine learning applications for data-centric AI development. Deriu has led or co-led several significant projects, including: Unified Model for Evaluation of Text Generation Systems (UniVal) – Deputy Project Leader (ongoing) Holistic Analysis of Organised Misinformation Activity in Social Networks – Project Leader (ongoing) End-to-End Low-Resource Speech Translation for Swiss German Dialects – Deputy Project Leader (completed) Pre-Study on Generation of Hockey News – Deputy Project Leader (completed) Call-E – Virtual Call Agent – Team Member (completed) DeepText: Intelligent Text Analysis with Deep Learning – Deputy Project Leader (completed) He collaborates extensively with international researchers and institutions, contributing to advancements in dialogue systems, speech technology, and AI evaluation frameworks. His publications emphasize practical applications, such as Swiss German dialect processing and misinformation detection in social media.

• Artificial Intelligence
• Bioinformatics
• Natural Language Processing
• +3 more

Dr. Ahmad Aghaebrahimian is a researcher at the ZHAW School of Life Sciences and Facility Management, affiliated with the Institute of Computational Life Sciences. He specializes in computational methods applied to healthcare, natural language processing (NLP), and bioinformatics. His work integrates deep learning, ontology-based systems, and signal processing to address challenges in healthcare informatics, biomedical research, and security systems. Research Projects: Project Leader: Advancing Information Accessibility in Hospitals (LLMs) Project Leader: Multi-document Patient Records Summarization Project Leader: Plant Cell Cultures with Deep Learning Deputy Leader: Automatic Supply Chain Monitoring Research Interests: His research focuses on AI-driven solutions for healthcare, including ontology-aware relation extraction, medical text mining, and robust signal processing systems. He also explores NLP applications in question answering, entity disambiguation, and parallel corpus creation. Recent work includes drone detection using CNNs in low SNR environments and computational methods for natural products discovery. Publications Trends: Over the past decade, his publications emphasize interdisciplinary approaches combining machine learning with bioinformatics and medical informatics. Key themes include deep learning model optimization, biomedical knowledge graph construction, and practical applications of NLP in healthcare systems. Grants & Collaboration: Leads research initiatives on AI in colorectal cancer classification and supply chain monitoring, demonstrating expertise in securing project leadership roles within academic-industry collaborations.

• Machine Learning
• Natural Language Processing
• Topic Modeling
• +4 more

Wray L. Buntine is a faculty member at Monash University in Melbourne, Australia, specializing in machine learning, natural language processing, and Bayesian methods. His research bridges theoretical foundations and practical applications, with a strong focus on NLP innovations, topic modeling, and efficient learning techniques. His research interests span: Machine Learning : Bayesian neural networks, active learning, and low-resource model optimization. Natural Language Processing : Topic modeling, machine translation, LLM evaluation, and dialogue systems. AI Applications : Healthcare (e.g., medication recommendation), education (e.g., dialogue classification), and graph-based anomaly detection. Recent publications (2023–2025) demonstrate a shift toward LLM-centric research, including automatic evaluation of topic models, uncertainty-aware language agents, and logical verification frameworks. His work frequently integrates Bayesian approaches with deep learning, emphasizing model interpretability and data efficiency. While no awards or grants are detailed in the source text, Buntine leads collaborative projects across NLP and ML, often co-authoring with researchers at Monash University and international institutions. Labs or teams are not explicitly referenced.

Levent ArslanView profile

Professor

• Speaker Recognition
• Voice Conversion
• Robust Speech Recognition
• +5 more

Levent Arslan is a full-time Professor at Boğaziçi University, focusing on speech processing, machine learning, and artificial intelligence. His research interests include speaker recognition, voice conversion, robust speech recognition, and natural language processing. He has contributed extensively to the development of systems for spoken language identification, automated training, and customer experience analytics. His work bridges technical innovations with business applications, such as analyzing corporate strategies in industries like steel manufacturing. Research Highlights: Speaker verification, deep learning for intent detection, cross-cultural business ethics, and automated error correction in NLP. Key Contributions: Over 50 publications since 2001, spanning speech enhancement, voice conversion systems, and educational technology. His recent studies emphasize leveraging transformer models for domain adaptation and addressing data imbalance in NLP tasks. Arslan’s analytical frameworks are applied in call center operations, fraud detection, and enterprise success metrics analysis. While no explicit awards or grants are cited, his work reflects a strong focus on practical solutions for real-world challenges.

• Computer Graphics
• 3D Modeling
• Computer Animation
• +7 more

Marie-Paule Cani is a Professor of Computer Science at École Polytechnique (Institut Polytechnique de Paris), where she serves as Dean of the Master of Science and Technology program and leads the STREAM research team at LIX Laboratory (CNRS/IP Paris). Her research bridges computer graphics, HCI, and AI, focusing on expressive 3D modeling, animation, and virtual environments. Education: 1987: M.Sc. in Computer Science, École Normale Supérieure & University Paris XI 1990: Ph.D. in Computer Graphics, University Paris XI 1995: Habilitation in Computer Science, Institut National Polytechnique de Grenoble Research Interests: She pioneers user-centered tools for 3D content creation, combining gesture-based interfaces (sketching, sculpting) with knowledge-enhanced procedural models. Key areas include implicit surfaces, physical simulation, AI-driven animation, and accessible tools for non-experts. Her work enables intuitive design of complex shapes, terrains, and dynamic scenes. Publication Trends: Recent work (2023–2025) emphasizes AI-integrated graphics, including controllable natural phenomena (volcanoes, erosion), sketch-based bio-visualization, reinforcement learning for animation, and real-time character control. Cross-disciplinary applications span geology, biology, and cinematography. Awards & Honors: ACM Steven A. Coons Award (2023) French Academy of Sciences (2020) ACM SIGGRAPH Academy (2019) ERC Advanced Grant EXPRESSIVE (2012–2017) CNRS Silver Medal (2012) Leadership & Grants: She founded research teams (STREAM, Imagine, Evasion) and secured major funding: ERC Advanced Grant, Google-École Polytechnique AI Chair (2018–2021), Horizon 2020 project CLIPE (2020–2024), and Hi!Paris Creative AI Fellowship (2021–2024). She mentors researchers in geometric modeling, animation, and AI. Labs & Teams: Directs the Modeling, Simulation & Learning pole at LIX (2019–2023). Founded STREAM (Structure Representation for Animation/Modeling) and Imagine (Inria/Grenoble teams), advancing real-time graphics and procedural content.