Dr. Barry Sheehan is an Associate Professor in Risk and Finance at the Kemmy Business School , University of Limerick . He serves as Course Director for interdisciplinary programs including the award-winning MSc in Machine Learning for Finance , MSc in Computational Finance , and Grad. Dip. in Artificial Intelligence in Finance . A member of the Emerging Risk Group (ERG) and Lero – The Irish Software Research Centre , he specializes in estimating risk profiles for emerging technologies through machine learning. Interdisciplinary research bridging finance, insurance, and technology Contributing to UN Sustainable Development Goals (SDGs) through risk analysis Active in EU-funded consortia: PROTECT , VI-DAS , Cloud-LSVA His research spans Cybersecurity , Autonomous Vehicles , and Quantitative Finance , with publications focusing on Bayesian network modeling and systematic risk reviews. Current work emphasizes data availability challenges and actuarial implications of smart mobility systems.
Dr. Ekin Ozer is an Assistant Professor at University College Dublin's School of Civil Engineering. His research focuses on vibration-based structural health monitoring (SHM), earthquake engineering, and mobile sensor technologies. He holds a PhD from Columbia University (2016) and has prior experience in academia (Middle East Technical University) and industry (Novum Structures). His work emphasizes smartphone and participatory sensing for bridge and building monitoring, with contributions to Bayesian risk assessment and machine learning applications. Education: BSc/MSc in Civil Engineering from Bogazici University, MPhil/PhD from Columbia University. Grants include the FLAME project (UCD SATLE) for 3D learning tools and transnational university initiatives. Key research trends in his articles include smartphone-driven SHM innovations, seismic risk assessment frameworks, and integration of cyber-physical systems for infrastructure resilience. He actively supervises PhD students and teaches modules like Structural Analysis, Bridge Engineering, and Case Studies in Infrastructure Design.
Dr. Joshua Alley is an Assistant Professor in the School of Politics and International Relations at University College Dublin (UCD), and a core member of the Connected_Politics Lab. His research focuses on international relations, particularly alliance politics, the political economy of security, and civil conflict. He holds a PhD from Texas A&M University (2020) and a BA from Gettysburg College (2015), with postdoctoral experience at the University of Virginia. His research investigates how alliances influence military spending, democratic foreign policy dynamics, and public opinion on political violence. Key works include analyses of U.S. military alliances' financial impacts, elite influence on public attitudes, and the effectiveness of nuclear threats. His teaching includes modules on international relations, security, and research methods. Alley’s work appears in journals like International Studies Quarterly , Journal of Conflict Resolution , and Security Studies . He actively contributes to public discourse through media outlets like The Irish Independent and maintains a GitHub repository for open-access research replication.
Professor Anil Kokaram is a distinguished academic and researcher in Electronic Engineering at Trinity College Dublin (TCD), Ireland. He holds a PhD in Signal Processing from the University of Cambridge (1993). As a Fellow of Engineers Ireland and recipient of an Academy Award (Oscar) for his work in video processing, he is renowned for contributions to digital video restoration, multimedia forensics, and video compression. From 2011–2017, he led the Media Algorithms Team at YouTube/Google, advancing cloud-based video transcoding and enhancement technologies. His research bridges academia and industry, with innovations in Bayesian inference, motion estimation, and neural network applications for video processing. **Education**: PhD in Signal Processing, University of Cambridge (1993). **Key Roles**: Former Associate Editor of IEEE Transactions on Video Technology and Image Processing. Founded GreenParrotPictures (acquired by Google), producing video enhancement software. **Research Focus**: Video compression artifacts, perceptual quality metrics (e.g., ViSQOL), and adaptive streaming algorithms. **Notable Projects**: Developed frameworks for automated sports broadcasting, noise reduction in medical imaging, and synchronization of user-generated videos. **Awards**: 2007 Science & Engineering Academy Award (Oscar), 2007 Fellow of Engineers Ireland. **Labs/Teams**: Leads the Signal Media Algorithms group at TCD, collaborating with industry partners like Google on large-scale video analysis systems. His work emphasizes practical applications of signal processing in creative industries, including film post-production and virtual production.
Fei Chen is a Research Fellow in the School of Mathematics at Trinity College Dublin. Their work focuses on interdisciplinary research at the intersection of mathematics, neuroscience, and biomedical engineering. Current research interests include predictive coding models in auditory perception, Bayesian inference frameworks for phantom perception, and applications of machine learning in diagnosing hearing-related disorders. Fei's recent publications explore topics such as auditory illusion modeling, chronic pain mechanisms through predictive processing lenses, and systematic reviews of autoimmune-related hearing loss. Their work combines advanced mathematical modeling with clinical data analysis to advance understanding of sensory perception disorders. Advisees/PhD students: None listed at this time. No scientific awards mentioned in available records. Research activities include collaboration with clinical teams to investigate neural networks involved in auditory processing anomalies and developing computational tools for hearing diagnostics.
Yuansong (John) Qiao is a Research Fellow at the Software Research Institute (SRI), Technological University of the Shannon: Midlands Midwest. His work spans cybersecurity, blockchain, and reinforcement learning, contributing to technologies like decentralized edge environments, intrusion detection systems, and immersive 360° video analytics. He supervises PhD students and actively explores applications in robotics, digital twins, and IoT. Recent publications highlight his focus on multi-view deep learning for anomaly detection , blockchain integration with AI , and ROS-based reinforcement learning . These works address challenges in cyber threat identification, decentralized finance, and smart manufacturing. His methodological innovations include knowledge graphs for security analytics and spatial audio analysis for VR environments. Qiao’s research aligns with UN Sustainable Development Goals, particularly in Quality Education (through supervised student projects) and Industry Innovation (via tools like Containerchain and UniROS). His collaborations span cybersecurity frameworks, decentralized robotics, and privacy-preserving systems for smart cities.
Mehran Hossein Zadeh Bazargani is a Marie Curie Post Doctoral Fellow at the School of Mathematics and Statistics , University College Dublin. His research focuses on brain-inspired artificial neural networks, anomaly detection in medical data, and interpretable machine learning. He has contributed to the MED-I consortium and founded the educational platform MLDawn . Education: PhD in Machine Learning (University College Dublin) Research Interests: Developing artificial neural networks for perceptual learning and decision-making, anomaly detection in time-series (ECG, EEG) and medical images (fMRI, X-ray), and computational neuroscience applications under the Free Energy Principle. Teaching Activities: Founder of MLDawn (2018–Present), lecturer at Queens University Belfast (2020), teaching assistant at UCD (2017–2020), and instructor in Iran (2013–2015). Scientific Contributions: 8 publications across anomaly detection, medical image analysis, and molecular communication. Key works include the D-RBFDD network and de-identification frameworks for medical data. Emails: mehran.hosseinzadehbazargani@ucd.ie, mldawn2018@gmail.com
Keefe Murphy is a Lecturer in Statistics within the Department of Mathematics and Statistics at Maynooth University , Faculty of Science & Engineering, and is affiliated with the Hamilton Institute . He is an active researcher in statistical machine learning, Bayesian nonparametrics, and clustering/classification of complex, high-dimensional data. Education: PhD in Statistics, University College Dublin MSc in Statistics, University College Dublin BSc in Economics & Mathematics, University of Limerick Research Interests: His work centres on developing and extending statistical methodologies for supervised and unsupervised learning , with emphasis on mixture models, latent variable models, Bayesian nonparametrics, and computational statistics . He actively contributes novel algorithms and software implementations, including the R packages IMIFA , MoEClust , and MEDseq available on CRAN. Current projects include extensions to Bayesian Additive Regression Trees (BART) , handling missing data , modelling multivariate count data , and variable selection in model-based clustering. Publication Profile: His recent publications (2021–2025) demonstrate a clear trajectory in advancing Bayesian machine learning methods, with contributions to Gaussian process BART models , sparse factor analysis , and educational data mining . Collaborative work spans learning analytics and multi-omic prostate cancer biomarker discovery , illustrating broad interdisciplinary impact. Awards & Recognition: Distinguished Dissertation Award (The Classification Society, 2020) Service & Advising: He serves as Associate Editor for Statistical Analysis and Data Mining and on departmental committees (Course Committee, PR Committee). He has successfully supervised PhD student Mateus Maia (graduated 2024) and currently teaches modules such as Advanced R Programming , Introduction to Data Science , and Nonparametric Statistics . Labs & Collaborations: He is affiliated with the Hamilton Institute , which fosters interdisciplinary research in applied mathematics and statistics, providing a collaborative environment for advancing computational and methodological statistics.
Fangzhe Qiu is an Associate Professor at University College Dublin's School of Irish, Celtic Studies and Folklore. He leads the ERC-funded project 'FLEXI', investigating late medieval Irish legal texts using computational methods. His research focuses on historical linguistics, Old Irish law, and corpus linguistics, with interdisciplinary interests in Turcology and language rights advocacy. Qiu holds a PhD in Early and Medieval Irish from University College Cork (2015), an MPhil in Celtic Studies from Oxford (2011), and a BA in Law and Philosophy from Peking University (China). He is fluent in multiple languages, including Cantonese and Uyghur, and actively promotes Irish culture in Chinese-speaking audiences through books like Medieval Irish Legends (2022) and translations of Irish poetry. Teaching responsibilities include courses on Early Irish language, medieval law, and literature. He has secured significant grants, including the Ad Astra Fellowship (2020–2024), and coordinates modules like 'Law & Society in Early Ireland' and 'Introduction to Early Irish.' His publications span top journals in Celtic Studies, edited volumes, and popular works. Current projects emphasize text reuse in legal digests and software development for early Irish text analysis.
Eleni Mangina is a Full Professor at the School of Computer Science, University College Dublin (UCD), and Vice Principal (International) for the College of Science. Her research focuses on applied artificial intelligence (AI), robotics, unmanned aerial vehicles (UAVs), and extended reality (XR) technologies with interdisciplinary applications in energy systems and education. She holds a PhD from the University of Strathclyde (UK), an MSc in Artificial Intelligence from the University of Edinburgh, and an MSc in Agricultural Science from the Agricultural University of Athens. Education : PhD, University of Strathclyde (UK), 2001 MSc in Artificial Intelligence, University of Edinburgh (UK) MSc in Agricultural Science, Agricultural University of Athens (Greece) HDip in University Teaching & Learning, UCD Research Interests : AI-driven optimization for energy and materials Xr applications in healthcare and education Citizen science and open data practices Robotics in early childhood education Smart city technologies Awards & Honors : 2022 CEN/CENELEC Standards Innovation Award 2021 Athena SWAN Bronze Award (School of Computer Science) 2020 UCD President's Teaching Award 2022 StandICT.eu Fellowship Grants & Projects : Coordinator of EU H2020 projects: ARETE, AHA, and FANTASIA Principal Investigator in SFI Energy Systems Integration Programme Lead on multiple XR and energy-related grants (2017-2025) Labs & Teams : Her lab develops XR solutions for education and energy, collaborating with EU and international partners. Current focuses include ethical XR standards and AI integration with metaverse platforms.
Liliana Pasquale is an Associate Professor at the School of Computer Science, University College Dublin (UCD), and a funded investigator at Lero – the SFI Research Centre for Software. She holds a PhD in Information and Communication Technology from Politecnico di Milano (2011) and has conducted research at IBM TJ Watson Research Center (2008). Her research focuses on requirements engineering, adaptive security, forensic readiness, and GDPR compliance in cyber-physical systems, with applications in transportation networks, industrial control systems, and smart spaces. **Education**: PhD in Information and Communication Technology (Politecnico di Milano, 2011); Professional Certificates in University Teaching & Learning (UCD). **Research Interests**: She investigates adaptive security mechanisms, forensic readiness for software systems, and runtime models for complex systems. Key areas include vulnerability assessment of transportation networks, stealthy attack detection in industrial systems, and human-centric cybersecurity for smart homes. **Grants & Awards**: Recipient of the Lero Research Award (2024), Runner-Up for IEEE Best Paper Award (2023), and numerous best reviewer recognitions. Active in grant initiatives such as the €1.2M 'Towards Forensic-Ready Software Systems' (2018–2019). **Teaching**: Coordinates UCD's MSc in Cybersecurity, including modules like 'Secure Software Engineering' and 'Leadership in Security'. Develops blended learning strategies for professional learners. **Professional Activities**: Serves on program committees for ICSE, SEAMS, and FSE. Co-chaired the Student Volunteer Committee for ESEC/FSE 2024 and participates in industry collaborations through UCD’s IT Strategy Group. **Lab/Teams**: Leads the SPARE research group, focusing on secure software engineering and adaptive systems. Collaborates with Lero and industry partners on cybersecurity challenges.
Aline Melo is an Assistant Professor at the School of Earth Sciences, University College Dublin (UCD). She holds a PhD in Geophysics from the Colorado School of Mines (2018) and prior academic appointments at Universidade Federal de Minas Gerais (Brazil). Her research focuses on integrating geophysical methods (magnetic, gravity, electrical) with machine learning to address geological challenges in mineral exploration and subsurface characterization. She specializes in inverse theory applications, 3D modeling, and uncovering geology under sedimentary cover. Education: B.S. in Geology, Universidade de Brasília (2008) M.Sc. in Geophysics, Universidade de Brasília (2012) Ph.D. in Geophysics, Colorado School of Mines (2018) Professional Diploma in University Teaching & Learning, UCD (2020) Research Interests: Applied geophysics for mineral exploration Multi-physics data integration Inverse theory and machine learning applications 3D subsurface modeling Tectonostratigraphic evolution analysis Awards & Honors: Mendenhall Prize for Outstanding Ph.D. Student (2018) SEG Best Student Paper Award (2015) Grants: Ad Astra Start-Up Grant (2020–2024) Teaching & Supervision: Coordinates modules on Geophysical Methods and Team-Based Modeling Supervises PhD students in applied geophysics and mineral exploration Professional Activities: Co-founder of Brazilian Association of Women in Geosciences (ABMGeo) Organized SEG workshops on machine learning and diversity in geophysics
Dr. David McGovern is an Assistant Professor at the School of Psychology, Dublin City University , specializing in sensory neuroscience and perceptual decision-making. He earned his PhD in Visual Neuroscience from the University of Nottingham and holds prior degrees in Cognitive Science from University College Dublin. Teaching: Modules in Cognition, Perception, and Behavioural Neuroscience Methods across four programs (BSc/MSc Psychology, Psychology & Mathematics, Psychology & Disruptive Technologies). Research: Investigates multisensory integration, aging effects on perceptual decision-making, and computational modeling. Uses psychophysics, EEG, and simulations. Selected Article Trends: Focus on sensory adaptation, age-related neural changes, multisensory dynamics, and computational approaches to cognition. Recent work links perceptual training to improved temporal integration and explores decision-making in sports and AI. Honors: Government of Ireland Postdoctoral Fellowship (2013) Brain Travel Scholarship (2011) Universitas 21 Scholarship (2009) University of Nottingham Research Scholarship (2006) Projects: Principal Investigator for Evaluating the Role of Sensory Perception in Elite Soccer (2024–2028) and Neurally-Informed Modeling of Adult ADHD (2022–2026).
Jian Cao is an Assistant Professor in the Department of Economics at Trinity College Dublin. He holds a Ph.D. in Economics from Florida State University (2018) and has served as a Postdoctoral Scholar at the California Institute of Technology (Caltech) from 2019 to 2021. His research focuses on computational economics, econometric methodologies, and election integrity, with notable contributions to Bayesian analysis of voter registration databases and dynamic social media monitoring. Cao has also led interdisciplinary projects funded by the ERC (€2 million) analyzing conflict emergence patterns using multi-source datasets. His work bridges economics, political science, and data science, producing tools like the dsc R package for enhanced synthetic control methods and spike for Twitter monitoring infrastructure. Education: Ph.D. in Economics, Florida State University, 2018 M.S. in Economics, Florida State University, 2016 M.S. in Financial Engineering, China University of Mining & Technology, 2014 B.A. in Economics, Henan University of Economics & Law, 2010 Research Highlights: Developed probabilistic matching methods for election auditing in California and Florida Deployed large-scale Twitter monitoring systems handling 4.5B+ tweets Advanced methods for multiple imputation in multi-scale datasets Grants & Awards: ERC Grant (€2M) for conflict emergence research
Associate Professor Stephanie Dornschneider-Elkink is affiliated with the School of Politics and International Relations at University College Dublin . Her research bridges conflict studies and political psychology , focusing on the cognitive and emotional foundations of political dissent , particularly in the Arab world and post-conflict societies. She employs computational methods to analyze ethnographic interviews, revealing how individuals reason about resistance under repression. Education: PhD in International Relations and Political Science from the Graduate Institute of International and Development Studies (Geneva), MA in International Relations and Middle East Studies from the American University in Cairo, Magister Artium in American Literature from Universität Hamburg Her work identifies positive emotions (hope, solidarity) and tit-for-tat reasoning as critical drivers of dissent, challenging traditional models that emphasize negative emotions or rational choice. She has conducted fieldwork in Lebanon (2022–2023) and authored computational frameworks for analyzing belief systems and inference chains in protest behavior. Scientific awards include the COFUND Junior Research Fellow at Durham University and pre-/postdoctoral fellowships from the Swiss National Science Foundation and German Academic Exchange Service . Her methodological contributions span agent-based modeling , cognitive mapping , and sentiment analysis of political speech.
