جست‌وجوی استاد و پژوهشگر

Ann Marie Youngمشاهده پروفایل

دانشیار

• Initial Teacher Education
• School Placement
• Physical Education Curriculum Development
• +۳ مورد دیگر

Ann Marie Young is an Associate Professor at the School of Education, University of Limerick, where she serves as Academic Director of School Placement and School Placement Coordinator. Her work centers on initial teacher education, school placement processes, and physical education curriculum development. Her educational background includes: BSc in Sports Science from St Mary's University PGCE in Physical Education from Canterbury Christ Church University PhD from University of Limerick Dr. Young's research focuses on initial teacher education with particular emphasis on school placement supervision frameworks. She investigates stakeholder roles in developing student teachers, advocates for structured supervision approaches, and explores curriculum development in Physical Education. Her work extends to teacher educator identity and assessment practices, aligning with UN Sustainable Development Goals for quality education. Her recent publications (2024-2025) demonstrate strong international collaboration, examining critical reflection in global citizenship education, cooperating teacher challenges in Ireland, and professional learning needs of physical education teacher educators in China. These works reveal consistent themes in teacher educator identity, school placement dynamics, and cross-cultural educational practices. Dr. Young has received research funding from the Teaching Council for her PhD work and maintains active professional engagement through memberships in the Physical Education Association of Ireland, PE-PAYS Research Centre, Educational Studies Association of Ireland, and AIESEP. She leads school placement coordination at UL, developing formal supervision frameworks that enhance teacher preparation quality. Her work with international collaborators and professional organizations positions her as a significant contributor to teacher education research and practice globally.

Tom O'Deaمشاهده پروفایل

مدرس

• Digital Media
• Computational Societies
• Art and Technology
• +۷ مورد دیگر

Tom O'Dea is a Lecturer in Sculpture and Expanded Practice at the National College of Art and Design (NCAD) in Dublin. He is also a Research Fellow at CONNECT, Ireland's SFI Centre for Future Networks at Trinity College Dublin, and co-chairs the Network Ecologies research theme. His work explores the intersection of computation, knowledge production, and societal transformation through mixed-media sculpture, social practice, and interdisciplinary collaboration. Education: PhD in Visual Art Practice (TCD), Master's in Digital Media (Huston School of Film & Digital Media, NUIG), Bachelor's in Mechanical Engineering (UCD) His research examines how computational systems shape human agency, environmental sustainability, and political structures, with a focus on platform capitalism, telepresence, and digital materialities. He co-founded the Orthogonal Methods Group (OMG) and the Dublin Art and Technology Association (DATA), fostering dialogues between engineering and artistic methodologies. O'Dea's practice spans exhibitions, workshops, and essays, including the peer-learning platform Memory, Loss and the essay After Measurement . Recent collaborations include Tírdreacha/Krajobrazy/Landschaften/مناظر الطبیعة and Counter-Infrastructures , addressing themes of connectivity and activism. Scientific Awards: Arts Council Visual Arts Bursary Award (2023, 2020) Arts Council Agility Award (2022) Visual & Performing Arts Fund awards (2018, 2014) Dublin Art & Technology Association showcase (2013) He has exhibited internationally, with notable works such as A Séance for Pierre Méchain , Totem , and Chatter , interrogating the material and ethical dimensions of digital infrastructures. He also contributes to educational initiatives like the CONNECT 2019 Summer School AI/ML Ethics strand.

Bruno M. Xavierمشاهده پروفایل

دانشیار

• machine learning
• software-defined networking
• programmable data planes
• +۱ مورد دیگر

Bruno M. Xavier serves as an Associate Professor in the Department of Information Systems at the Federal Institute of Espirito Santo, Campus Cachoeiro de Itapemirim, Brazil, while concurrently working as a Research Assistant at Trinity College Dublin's CONNECT Centre on 4G/5G network optimization projects. He is pursuing his Ph.D. in Computer Science at the Federal University of Espirito Santo through collaboration with the Núcleo de Estudos em Redes Definidas por Software Lab. His educational background includes: Doctor of Philosophy (Ph.D.) in Computer Science (in progress), Federal University of Espirito Santo Dr. Xavier's research integrates artificial intelligence with telecommunications infrastructure, specializing in machine learning applications for software-defined networking (SDN) and programmable data planes. His work focuses on AI-Driven Network Customization techniques to enhance 4G/5G network performance, aiming to develop adaptive communication systems through algorithmic optimization of network resources and traffic management. He maintains active research affiliations with the Núcleo de Estudos em Redes Definidas por Software Lab (Software Defined Networks Research Lab) at the Federal University of Espirito Santo and the CONNECT Centre at Trinity College Dublin, contributing to next-generation network optimization initiatives. No information is available regarding scientific awards, student advising activities, or research grant funding.

Ali Intizarمشاهده پروفایل

استادیار

• Data Analytics
• Internet of Things (IoT)
• Stream Query Processing
• +۳ مورد دیگر

Ali Intizar is an Assistant Professor at the School of Electronic & Computer Engineering , Dublin City University (DCU). Previously, he held roles as an Adjunct Lecturer, Research Fellow, and Research Unit Leader at the Data Science Institute, National University of Ireland, Galway. He earned his PhD (with distinction) in 2011 from Vienna University of Technology, Austria. Research interests: Ali specializes in Data Analytics , Internet of Things (IoT) , Stream Query Processing , Data Integration , Distributed and Federated Machine Learning , and Knowledge Graphs . His work applies these technologies to domains such as Smart Cities, Smart Manufacturing, Smart Farming, Environmental Monitoring, and e-Health. Funding & Collaborations: He has secured grants as principal investigator and funded investigator from the European Commission, Science Foundation Ireland, Enterprise Ireland, and industry partners. His research has resulted in over 100 publications in top-tier journals and international conferences. Education: PhD (with distinction), Vienna University of Technology, Austria (2011) Labs & Teams: Ali has contributed to the Data Science Institute at National University of Ireland, Galway, as a Research Unit Leader, and now collaborates with DCU's School of Electronic & Computer Engineering in advancing IoT and distributed machine learning applications.

Thompson Gyedu Kwarkyeمشاهده پروفایل

عضو هیئت علمی

• AI Ethics and Governance
• Digital Humanities
• Public Policy
• +۴ مورد دیگر

Thompson Gyedu Kwarkye is an anthropologist and Postdoctoral Researcher at the School of Information and Communication Studies , University College Dublin , where since November 2023 he has been developing micro-credential modules on AI ethics and governance. Previously he held a post-doctoral appointment at the Faculty of Law, University of Oxford . His work is inherently interdisciplinary, bridging anthropology, public policy, digital humanities and socio-technical studies. Research Interests AI governance, ethics and policy, particularly in African contexts Digital humanities and media culture Gendered traditional leadership and human security in Ghana North–South techno-political asymmetries Local governance, chieftaincy and customary law Across more than a decade of scholarship his publications have consistently examined how emerging technologies intersect with indigenous institutions, gendered authority and public policy, producing nuanced analyses that move fluidly between village-level ethnography and continental AI strategy. Scientific Impact & Recognition No specific awards or grants are mentioned in the provided text; his scholarly footprint is evidenced instead by a steady stream of peer-reviewed outputs in high-impact venues. Advising & Collaborative Work While no formal student supervision data are supplied, his current role involves curriculum design and micro-credential development, signalling ongoing educational engagement within UCD and the Insight Centre for Data Analytics.

Susan Leavyمشاهده پروفایل

استادیار

• Artificial Intelligence
• Text Mining
• Digital Humanities
• +۶ مورد دیگر

Susan Leavy is an Assistant Professor at the School of Information and Communication, University College Dublin, affiliated with the Insight Centre for Data Analytics. Her research bridges artificial intelligence, text mining, and digital humanities, focusing on bias mitigation in machine learning algorithms and cultural analytics. PhD in Artificial Intelligence & Bias Detection, Trinity College Dublin MPhil in Gender and Women’s Studies MSc in Artificial Intelligence BA in Philosophy and English Literature Her work spans gender bias in AI , ethical data curation , multimodal bias analysis , and algorithmic transparency . Recent publications highlight interdisciplinary approaches to auditing generative models, mitigating bias through inclusive language, and socio-technical frameworks for AI safety. Key trends in her research include: cross-disciplinary methods for bias detection, ethical AI design informed by feminist theory, and security applications of machine learning for content moderation and network protection. She has developed tools like CURATR for historical text analysis and ARTAI for societal risk assessment in recommender systems, while advocating for feminist epistemology in data-centric AI.

• Artificial Intelligence
• Deep Learning
• Machine Learning
• +۱۷ مورد دیگر

Majjed Al-Qatf is a Researcher at the University of Galway , collaborating with Prof. Edward Curry. His work focuses on data spaces, knowledge graphs for data sharing, large language models, and retrieval augmented generation for question answering. Education: B.S. in Network Technology and Computer Security (Sana’a University, 2013), M.S. in Computer Science and Technology (Central South University, 2019), Ph.D. in Computer Science and Technology (University of Science and Technology of China, 2023) His research spans artificial intelligence, particularly deep learning , machine learning , NLP , and computer vision , with applications in network intrusion detection , image captioning , activity recognition , and explainability . Prior work includes image enhancement , knowledge graphs , and federated learning . Publications appear in journals such as IEEE Transactions on Multimedia , ACM Transactions on Multimedia Computing, Communications and Applications , and conferences like the IEEE International Conference on Big Data and International Conference on Software and Computer Applications .

Devishree Pillaiمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Devishree Pillai is a Research Assistant at the Insight Centre for Data Analytics at the University of Galway, working under the supervision of Dr. Paul Buitelaar. She collaborates with industry leaders such as Fidelity Investments, Accenture, and Huawei Technologies on advanced research projects. Current focus: Enhancing question-answering capabilities of large language models (LLMs) using domain-specific knowledge graphs Past projects: Dependency parsing-based relation extraction for Fidelity Investments, multilingual social media analysis for the EU-funded PANDEM-2 project, and integration of LIME-based explainable AI (XAI) techniques into intent classification models for Huawei Technologies Research Interests include: Natural Language Processing (NLP) Explainable AI (XAI) for model transparency Knowledge Graph integration with language models Fake News Detection using deep learning architectures Education : Master's in Data Analytics (2021) from University of Galway Bachelor's in Computer Science Engineering from Mumbai University

Simon Sarkarمشاهده پروفایل

پژوهشگر

• Data Analytics
• Natural Language Processing
• Machine Learning
• +۳ مورد دیگر

Simon Sarkar is a Researcher at the Insight Centre for Data Analytics within the University of Galway. His work focuses on explainable AI systems, particularly knowledge graph-based recommendation systems for the Fidelity project (Phase 5, Work Package 2), and semantic similarity analysis for user queries in collaboration with Huawei. Education: MSc in Data Analytics from National College of Ireland (2020) Bachelor’s in Computer Applications Research interests include Knowledge Graphs , Natural Language Processing , Reinforcement Learning , and Machine Learning , with a focus on optimization in continuous action spaces and HR analytics applications. Labs/Teams: Insight Centre for Data Analytics Unit for Natural Language Processing (supervised by Dr. Paul Buitelaar)

• Natural Language Processing
• Knowledge Extraction
• Semantic-based Information Access
• +۱۲ مورد دیگر

Paul Buitelaar is a Professor in Data Analytics and Deputy Director of the Data Science Institute at the University of Galway. He leads the Multimodal Data Analysis research program through the Insight SFI Research Centre for Data Analytics, focusing on Natural Language Processing (NLP) for knowledge extraction and semantic information access. Co-Director of SFI Centre for Research Training in AI Co-PI of Insight SFI Research Centre for Data Analytics Collaborates with industry partners like Fidelity Investments, Huawei, and Irish Times His research spans ontology learning, linguistic linked data, and social media analysis, particularly in legal and healthcare domains. He developed the Saffron framework for knowledge extraction and contributed to EU-funded projects such as Monnet and MixedEmotions. His publications emphasize NLP applications in legal text analysis, taxonomy generation, and health content categorization. Projects like Pret-a-LLod and MixedEmotions highlight his interdisciplinary approach combining NLP with computer vision and sensor analysis. Paul's work integrates knowledge graphs and back-translation techniques to enhance machine translation, alongside unsupervised methods for analyzing social media health data.

• Machine Learning
• Deep Learning
• Recommender Systems
• +۷ مورد دیگر

Dr. Ruihai Dong is an Assistant Professor at the School of Computer Science, University College Dublin, affiliated with the Insight Centre for Data Analytics. His research bridges Machine Learning, Deep Learning, and Recommender Systems with significant applications in finance and medical imaging. Develops AI-driven solutions for financial markets and healthcare Collaborates with industry partners like Eagle Alpha and Samsung Funded by Enterprise Ireland for commercialization studies Research focuses on: Recommender systems (news, finance, conversational AI) Graph neural networks for financial risk modeling Medical imaging under limited labeling constraints Algorithmic transparency and ethical AI applications 3D CNNs & transformers for seismic analysis Large language models for multilingual evaluation Recent publications emphasize: Hybrid architectures for multimodal data Explainable AI techniques in financial and news domains Geometric deep learning for microstructure and seismic data Curriculum strategies in active learning Media bias mitigation frameworks Latent space modeling for asset embeddings Scientific contributions recognized through: Outstanding Research Award 2018 by UCD School of Computer Science Industry collaborations include work with: Eagle Alpha (financial analytics) SkillPages (data-driven platforms) Samsung (technology innovation)

• Latent Variable Models
• Mixture Models
• Rank Data Models
• +۷ مورد دیگر

Claire Gormley is an Associate Professor of Statistics at University College Dublin (UCD) and a Funded Investigator at the Insight Centre for Data Analytics. She joined UCD in 2006 as an Assistant Lecturer, was promoted to Assistant Professor in 2008, and to Associate Professor in 2017. Her research group specializes in Machine Learning & Statistics with applications spanning genetics, agriculture, and medical sciences. Education PhD in Statistics, Trinity College Dublin (2007) Visiting Scholar, Department of Statistics/Centre for Statistics and the Social Sciences, University of Washington Seattle (2006) Research Expertise Professor Gormley develops advanced statistical methodologies including latent variable models, mixture models, and Bayesian approaches for high-dimensional data analysis. Her work addresses dimensionality challenges in diverse fields such as metabolomics, orthopaedics, and social science, with current projects focusing on model-based clustering for mixed-type high-dimensional datasets. Methodological innovations are consistently applied to real-world problems involving large-scale biological and agricultural data. Publication Trends Her recent publications (2023-2025) demonstrate strong interdisciplinary impact across genetics (tuberculosis, dairy cattle), agricultural science (nitrogen utilization), and medical research (neonatal sepsis). Methodologically, she pioneers mixture models and latent variable frameworks for complex data structures, particularly in multi-omics integration and network analysis. A clear trajectory shows increasing focus on computationally intensive solutions for biological big data, with applications directly addressing food security and healthcare challenges. Research Leadership As a Funded Investigator at the Insight Centre, Dr. Gormley leads a dynamic research group securing competitive grants for interdisciplinary projects. Her team collaborates with veterinary scientists, geneticists, and medical researchers on grant-funded initiatives including tuberculosis genomics and metabolomics data analysis. The group maintains strong industry partnerships in agricultural technology and healthcare analytics, with recent projects developing predictive models for dairy cattle health monitoring and clinical diagnostics.

• Machine Learning
• Statistics
• Actuarial Science
• +۳ مورد دیگر

Dr. Adrian O'Hagan is a Lecturer in Statistics and Actuarial Science at University College Dublin (UCD) School of Mathematics and Statistics, with a focus on machine learning and statistical modeling. He completed his PhD in Statistics at UCD in 2012 and holds an MSc in Statistics from UCD (2006). As a funded investigator at the Insight Centre, his work bridges computational statistics with practical applications in insurance, healthcare, and manufacturing. Education: PhD Statistics, UCD (2012) MSc Statistics, UCD (2006) Bachelor of Actuarial and Financial Studies, UCD Research Interests span machine learning, Bayesian inference, network analysis, and actuarial science. His recent work includes: Developing probabilistic models for network analysis and EHR-based phenotyping Advancing clustering algorithms with uncertainty quantification and optimization Applying statistical methods to insurance risk, manufacturing analytics, and data compression Publications highlight his expertise in variational Bayes, Gaussian mixtures, and multivariate claim modeling, with interdisciplinary impacts in healthcare and finance. He collaborates on real-world data analysis and contributes to open-source actuarial tools like mvClaim .

Eric Wolsztynskiمشاهده پروفایل

مدرس ارشد

• Statistical Learning
• Machine Learning
• Computational Statistics
• +۳ مورد دیگر

Eric Wolsztynski is a Senior Lecturer in Statistics at the School of Mathematical Sciences , University College Cork (UCC), and a Funded Investigator with the SFI Insight Centre for Data Analytics . He serves as Head of Discipline (Statistics) at UCC. Affiliation : School of Mathematical Sciences, UCC Email : e.wolsztynski@ucc.ie, eric.w@ucc.ie Research Interests focus on statistical and machine learning methods for healthcare, particularly multi-omics and radiomics in oncology, fairness in ML for insurance, and renewable energy data analysis. His work emphasizes predictive modeling, 3D spatial analysis of PET imaging, and development of non-invasive biomarkers for tumor characterization. Recent Publications (2025-2011) span Annals of Intensive Care , PLOS ONE , and IEEE Transactions , with themes in tumor heterogeneity, mRNA-based prognosis, and offshore wind energy perception. Articles highlight integration of structural and textural PET data, fairness in insurance modeling, and clinical collaborations in Ireland and the USA. Teaching & Supervision : Supervised 4 PhD students and 40+ MSc projects, including work on feature selection in sarcoma, PET imaging analysis, vessel speed clustering, and late-life mortality modeling. Software Development : Created R packages mia (Medical Imaging Analysis) and volumetrics (3D Uptake Modeling), available via GitHub.

Andy Donaldمشاهده پروفایل

پژوهشگر ارشد

• Artificial Intelligence
• Machine Learning
• Explainable AI
• +۳ مورد دیگر

Andy Donald is a Research Fellow and lead of the Applied Innovation Unit at Insight, University of Galway. His work focuses on automating AI/ML processes, explainable AI methods, surrogate modeling for computational systems, and real-world applications in cloud environments. Research Expertise Explainability & Ethics in AI/ML Multimodal Data Applications High-Volume Stream Analytics Knowledge Graph Construction Surrogate Modeling Industry Collaboration Leadership Andy collaborates with industry partners including Fidelity , Genesys , Connacht Rugby , Avaya , and Aró Digital to bridge academic research with scalable solutions.