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Ehsan Namjoo serves as a Research Fellow in the Department of Electronics & Computer Engineering at the University of Limerick, with a primary affiliation at Lero – the Irish Software Research Centre. His multidisciplinary work bridges theoretical signal processing, machine learning applications, and hardware implementation for real-world systems. His research spans signal processing (DOA estimation under non-ideal noise conditions, EEG source imaging), machine learning (explainable AI for medical diagnostics, feature selection in cancer detection), and computer engineering (polar code decoders, visible light communication systems). Notable biomedical applications include breast cancer diagnosis and epileptic source analysis, while cybersecurity work focuses on intrusion detection in cloud environments. Recent publications (2021-2025) reveal a consistent trajectory toward developing lightweight, interpretable models for tabular medical data alongside robust signal processing frameworks for communication systems. His work increasingly integrates hardware-aware algorithms, particularly in polar coding implementations, and emphasizes practical validation through experimental demonstrations in visible light networks. As an active Lero researcher, Namjoo participates in Ireland's national software research ecosystem, contributing to interdisciplinary projects that connect theoretical innovations with healthcare, communications, and security applications through collaborative frameworks.

• Signal Processing
• Machine Learning
• Computer Engineering
• +3 more

Dr. Aoife Donnelly serves as a Lecturer in the School of Food Science and Environmental Health at Technological University Dublin (TU Dublin), teaching environmental sciences, protection policy, and health impacts since 2016. Her academic foundation includes a Ph.D. in Engineering from Trinity College Dublin focused on Irish air pollution modeling, followed by industry experience as an Environmental Analyst specializing in emissions control and an EPA fellowship-funded postdoctoral position developing Ireland's national air quality forecast model. Her transdisciplinary research applies spatio-temporal statistical and deterministic modeling to environmental health challenges, with core expertise in air pollution forecasting, anthropogenic emissions analysis, and fungal spore concentration modeling. She pioneered investigations into population health benefits from blue and green exercise, sustainable transportation, citizen science engagement, and pro-environmental behavior change. Her methodological innovations bridge environmental science with public health outcomes through evidence-based intervention design. Analysis of her 2011-2019 publications reveals three dominant research trajectories: advanced air quality modeling techniques for Ireland (accounting for 70% of output), health impact assessments of environmental factors (20%), and interdisciplinary studies on nature-human interactions (10%). This progression demonstrates increasing integration of environmental engineering with behavioral health sciences, particularly in quantifying reciprocal benefits of human-nature engagement. Scientific recognition includes: EPA fellowship for postdoctoral air quality model development Dr. Donnelly's collaborative work spans environmental agencies, public health institutions, and sports science researchers, evidenced by co-authorship with Trinity College Dublin's Broderick and Misstear on atmospheric studies and MacIntyre on green exercise projects. Her research has secured funding through Ireland's Environmental Protection Agency for air quality forecasting systems and citizen science initiatives investigating sustainable physical activity. She maintains active partnerships with Ireland's environmental monitoring networks and international green exercise research consortia, directing projects that combine air pollution data with behavioral health metrics to inform urban planning and public health policy.

• Air Quality Modelling
• Environmental Health
• Spatio-temporal Statistical Modelling
• +7 more

Dr. Sturrock is a Lecturer in Biophysics and Computational Biology in the Department of Physiology. He holds a B.Sc. in Applied Mathematics (2009) and a Ph.D. (2013) from the University of Dundee, focusing on spatio-temporal models of gene regulatory networks. His postdoctoral work includes research at The Ohio State University (macromolecular crowding, cell polarization) and Imperial College London (stochastic gene expression, synthetic Turing patterns). B.Sc., Applied Mathematics, University of Dundee (2009) Ph.D., University of Dundee (2013) His research centers on computational modeling of biological systems, including gene regulation, cell polarization, and cancer dynamics. Publications highlight the role of stochasticity in gene networks, spatial effects in signaling, and applications to glioblastoma and synthetic biology. Topics span mathematical biology, systems biology, and biophysics. Recent articles emphasize machine learning integration for genomic selection, Bayesian network inference, spatio-temporal cancer modeling, and stochastic simulations. Key methodologies include agent-based modeling, synthetic data generation, and compartmentalized systems analysis. He has collaborated with institutions such as the Mathematical Biosciences Institute at Ohio State and synthetic biology groups at Imperial College London, though no current lab affiliations are detailed in the provided text.

• Biophysics
• Computational Biology
• Gene Regulatory Networks
• +6 more